Professor Kate Smith-Miles
At last count, I had 300 publications (plus other papers under review), including 2 books, 5 edited volumes, 21 book chapters, 119 refereed journal articles, and 153 refereed conference papers.
Refereed journal papers
119. Liu, C. K., Smith-Miles, K. A., Wauters, T., and Costa, A. M., "Instance Space Analysis for 2D Bin Packing Mathematical Models", European Journal of Operational Research, in press 2024.
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118. Alipour, H., Muñoz, M. A. and Smith-Miles, K., "On the impact of initialisation strategies on Maximum Flow algorithm performance", Computers and Operations Research, vol. 163, article 106492, 2024.
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117. Grey, V., Smith-Miles, K., Fletcher, T. B., Hatt, B. and Coleman, R. A., "Empirical evidence of climate change and urbanization impacts on warming stream temperatures", Water Research, Volume 247, article 120703, 2023.
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116. Zhen, Y., Smith-Miles, K., Fletcher, T. B., Burns, M. J., and Coleman, R. A., "Multi-objective optimization in real-time operation of rainwater harvesting systems", EURO Journal on Decision Processes, vol. 11, article 100039, 2023.
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115. Weeratunge, W., Robe, D., Menzel, A., Phillips, A. W., Kirley, M., Smith-Miles, K. and Hajizadeh, E., "Bayesian Coarsening: Rapid Tuning of Polymer Model Parameters", Rheologica Acta, vol. 62, pp. 477–490, 2023.
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114. Pereira, J. L. J., Smith-Miles, K., Muñoz, M. A., and Lorena, A. C., "Optimal selection of benchmarking datasets for unbiased machine learning algorithm evaluation", Data Mining and Knowledge Discovery, https://doi.org/10.1007/s10618-023-00957-1, 2023.
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113. Kandanaarachchi, S. and Smith-Miles, K., "Comprehensive
Algorithm Portfolio Evaluation using Item Response Theory", Journal of Machine Learning Research, vol. 24, no. 177, pp. 1-52, 2023.
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112. Smith-Miles, K. and Muñoz, M. A., "Instance Space Analysis for Algorithm Testing: Methodology and Software Tools", ACM Computing Surveys, vol. 55, no, 12, 2023.
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111. Neelofar, Smith-Miles, K., Muñoz, M. A. and Aleti, A., "Instance Space Analysis of Search-Based Software Testing", IEEE Transactions on Software Engineering, vol. 49, no. 4, pp. 2642-2660, 2023.
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110. Alipour, H., Muñoz, M. A. and Smith-Miles, K., "Enhanced Instance Space Analysis for the Maximum Flow Problem", European Journal of Operational Research, vol. 304, no. 2, pp. 411-428, 2023.
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109. Shireen, Z., Weeratunge, H., Menzel, A., Phillips, A., Larson, R., Smith-Miles, K. and Hajizadeh, E., "A machine learning enabled hybrid optimization framework for efficient coarse-graining of a model polymer", Nature Computational Materials, vol. 8, article 224, 2022.
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108. Yap, E., Muñoz, M. A. and Smith-Miles, K., "Informing multi-objective optimisation benchmark construction through Instance Space Analysis", IEEE Transactions on Evolutionary Computation, vol. 26, no. 6, pp. 1246-1260, 2022.
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107. Smith-Miles, K. and Muñoz, M. A., "Optimal construction of montages from mathematical functions on a spectrum of order-disorder preference", Journal of Mathematics and the Arts, vol. 16, no. 4, pp. 347-373, 2022.
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106. Paiva, P., C. C. Moreno, Smith-Miles , K., M. G. Valerian and Lorena, A. C., "Relating instance hardness to classification performance in a dataset: a visual approach", Machine Learning, vol. 111, no. 8, pp. 3085-3123, 2022.
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105. Andrés-Thió, N., Muñoz, M. A. and Smith-Miles, K., "Bi-fidelity Surrogate Modelling: Showcasing the need for new test instances", INFORMS Journal on Computing, vol. 34, no. 6, pp. 3007-3022, 2022.
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104. Xu, W. D., Burns, M. J, Cherqui, F., Smith-Miles, K. and Fletcher, T. D., "Coordinated control can deliver synergies across multiple rainwater storages", Water Resources Research, vol. 58, no. 2, e2021WR030266, February 2022.
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103. De Coster, A. Musliu, N., Schaerf, A., Schoisswohl, J. and Smith-Miles, K., "Algorithm Selection and Instance Space Analysis for Curriculum-based Course Timetabling", Journal of Scheduling, vol. 25, pp. 35–58, 2022.
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102. Smith-Miles, K. A. and Geng, X., “Revisiting Facial Age Estimation with New Insights from Instance Space Analysis” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 44, no. 5, pp. 2689-2697, 2022.
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101. Muñoz, M. A., Kirley, M. and Smith-Miles, K.,"Analyzing randomness effects on the reliability of Exploratory Landscape Analysis", Natural Computing, vol. 2, pp. 131-154, 2022.
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100. Yap, E., Muñoz, M. A. and Smith-Miles, K., "On the Diversity and Robustness of Parameterised Multi-Objective Test Suites", Applied Soft Computing, vol. 110, article 107613, 2021.
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99. dos Santos Fernandes, L. H. , Lorena, A. C. and Smith-Miles, K. "Towards Understanding Clustering Problems and Algorithms: an Instance Space Analysis", Algorithms, vol. 13, no. 3, article 95, 2021.
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98. Smith-Miles, K., Christiansen, J. and Muñoz, M. ., "Revisiting "Where are the Hard Knapsack Problems?" via Instance Space Analysis", Computers and Operations Research, vol. 128, article 105184, 2021.
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97. Muñoz, M. A., Yan, T., Leal, M. R., Smith-Miles, K., Lorena, A. C., Pappa, G. L. and Rodrigues, R. M., "An Instance Space Analysis of Regression Problems", ACM Transactions on Knowledge Discovery from Data, vol. 15, no. 2, article 28, 2021.
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96. Talagala, P. D., Hyndman, R. J. and Smith-Miles, K., "Anomaly Detection in High Dimensional Data", Journal of Computational and Graphical Statistics, vol. 30, no. 2, pp. 360-374, 2021.
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95. Kletzander, L., Musliu, N. and Smith-Miles, K., "Instance Space Analysis for a Personnel Scheduling Problem", Annals of Mathematics and Artificial Intelligence, vol. 89, pp. 617–637, 2021.
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94. Edwards, S. J., Baatar, D., Smith-Miles, K. and Ernst, A., "Symmetry breaking of identical projects in the high-multiplicity RCPSP/max", Journal of the Operational Research Society, vol. 72, no. 8, pp. 1822-1843, 2021.
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93. Kandanaarachchi, S., Hyndman,R. J. and Smith-Miles, K., "Early classification of spatio-temporal events using partial information", PLOS ONE, vol. 15, no. 8, e0236331, 2020.
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92. Flegg, M. B., Muñoz, M. A., Smith-Miles, K., Yuen, W. S., Flegg, J. A. and Carroll. J. G., "Parameter estimation for a point-source
diffusion-decay morphogen model", Journal of Mathematical Biology, vol. 80, pp. 2227–2255, 2020.
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91. Abbasi, B., Babaei, T., Hosseinifard, Z., Smith-Miles, K. and Dehghani, M., "Predicting Solutions of Large Scale Optimization Problems via Machine Learning: A Case Study in Blood Supply Chain Management", Computers & Operations Research, vol. 119, article 104941, 2020.
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90. Baniasadi, P., Foumani, M., Smith-Miles, K. and Ejov V., "A Transformation Technique for the Clustered Generalized Traveling Salesman Problem with Applications to Logistics", European Journal of Operational Research, vol. 285, no. 2, pp. 444-457, 2020.
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89. Kandanaarachchi, S., Muñoz, M. A., Hyndman, R. and Smith-Miles, K., "On normalization and algorithm selection for unsupervised outlier detection" , Data Mining and Knowledge Discovery, vol. 34, pp. 309-354, 2020.
88. Talagala, P. D., Hyndman, R. J., Smith-Miles, K., Kandanaarachchi, S. and Muñoz, M.A. "Anomaly Detection in Streaming Nonstationary Temporal Data", Journal of Computational and Graphical Statistics, vol. 29, no. 1, pp. 13-27, 2020.
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87. Bowly, S., Smith-Miles, K., Baatar, D. and Mittelmann, H., "Generation techniques for linear programming instances with controllable properties", Mathematical Programming Computation, vol. 12, pp. 389–415, 2020.
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86. Muñoz, M. A. and Smith-Miles, K. A., "Generating New Space-Filling Test Instances for Continuous Black-Box Optimization", Evolutionary Computation, vol. 28, no. 3, pp. 379-404, 2020.
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85. Foumani, M., Razeghi, A. and Smith-Miles, K., "Stochastic optimization of two-machine flow shop robotic cells with controllable inspection times: from theory toward practice", Robotics and Computer-Integrated Manufacturing, vol. 61, article 101822, 2019.
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84. Foumani, M., Smith-Miles, K., "The Impact of Various Carbon Reduction Policies on Green Flowshop Scheduling", Applied Energy, vol. 249, pp. 300-315, 2019.
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83. Talagala, P. D., Hyndman, R., Leigh, C., Mengersen, K. and Smith-Miles, K., "A feature-based procedure for detecting technical outliers in water-quality data from in situ sensors", Water Resources Research, vol. 55, pp. 8547-8568, 2019.
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82. Lewis, R. and Smith-Miles, K., "A Heuristic Algorithm for Finding Cost-Effective Solutions to Real-World School Bus Routing Problems", Journal of Discrete Algorithms, vol. 52, pp. 2-17, 2018.
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81. Guimares, C., Aleti, Al, Grunske, L. and Smith-Miles, K., "Mapping the Effectiveness of Automated Test Suite Generation Techniques", IEEE Transactions on Reliability, vol. 67, no. 3, pp. 771-785, 2018.
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80. Foumani, M., Moeini, A., Haythorpe, M. and Smith-Miles, K., "A Cross Entropy Method for Optimizing Robotic Automated Storage and Retrieval Systems", International Journal of Production Research, vol. 56, pp. 6450-6472, 2018.
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79. Muñoz, M. A., Villanova, L., Baatar, D. and Smith-Miles, K. A., "Instance Spaces for Machine Learning Classification", Machine Learning, vol. 107, no. 1, pp. 109-147, 2018.
78. Foumani, M., Smith-Miles. K. and Gunawan, I., "Scheduling of two-machine robotic rework cells: In-process, post-process and in-line inspection scenarios", Robotics and Autonomous Systems, vol. 91, pp. 210-225, 2017.
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77. Foumani, M., Smith-Miles. K. A., Gunawan. I., and Moeini, A., "Stochastic scheduling of an automated two-machine robotic cell with in-process inspection system", Computers & Industrial Engineering, vol. 112, pp. 492-502, 2017.
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76. Kang, Y., Hyndman, R. and Smith-Miles, K., "Visualising Forecasting Algorithm Performance using Time Series Instance Spaces", International Journal of Forecasting, vol. 33, no. 2, pp. 345-358, 2017.
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75. Muñoz, M. A. and Smith-Miles, K. A., "Performance analysis of continuous black-box optimization algorithms via footprints in instance space", Evolutionary Computation, vol. 25. no. 4, pp. 529-554, 2017.
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74. Steponavice, I., Hyndman, R., Smith-Miles, K., and Villanova, L., "Dynamic algorithm selection for pareto optimal set approximation", Journal of Global Optimization, vol. 67, no. 1, pp. 263-282, 2017.
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73. Foumani, M., Gunawan, I. and Smith-Miles, K., "Increasing Throughput for a Class of Two-Machine Robotic Cells Served by a Multifunction Robot", IEEE Transactions on Automation Science and Engineering, vol. 14, no. 2, pp. 1150-1159, 2017.
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72. Lahda, S., Smith-Miles, K., Chandran, S. "Realistic Projection on Casual Dual-Planar Surfaces with Global Illumination Compensation", International Journal of Image and Graphics, vol. 16, no. 3, 1650014, 29 pages, 2016.
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71. Smith-Miles, K. A. and Bowly, S., "Generating New Test Instances by Evolving in Instance Space", Computers & Operations Research, vol. 63, pp. 102-113, 2015.
70. Foumani, M., Gunawan, I., Smith-Miles, K. and Ibrahim, M. Y., "Notes on Feasibility and Optimality Conditions of Small-Scale Multifunction Robotic Cell Scheduling Problems With Pickup Restrictions", IEEE Transactions on Industrial Informatics, vol. 11, no. 3, pp. 821-829, 2015.
69. Kang, Y., Belusic, D. and Smith-Miles, K., "Classes of Structures in the Stable Atmospheric Boundary Layer", Quarterly Journal of the Royal Meteorological Society, vol. 141, pp. 2057-2069, 2015.
68. Wu, Q., Smith-Miles, K. and Tian, T., "Approximate Bayesian computation schemes for parameter inference of discrete stochastic models using simulated likelihod density", BMC Bioinformatics, vol. 15 (Suppl. 12), S3, 2014.
67. Kang, Y., Belusic, D. and Smith-Miles, K., "A note on the relationship between turbulent coherent structures and phase correlation", Chaos, vol. 24, article 023114, June 2014.
66. Adenso-Diaz, B., Lozano, S., Garcia-Carbajal, S. and Smith-Miles, K., “Modelling route planning with horizontal cooperation across supply chains”, Transportation Research – A, vol. 66, pp. 268-279, 2014.
65. Smith-Miles, K. A., Baatar, D., Wreford, B. and Lewis, R., “Towards Objective Measures of Algorithm Performance across Instance Space”, Computers and Operations Research, vol. 45, pp. 12-24, 2014.
64. Kang, Y., Belusic, D. and Smith-Miles, K., "Detecting and Classifying Events in Noisy Time Series", Journal of the Atmospheric Sciences, vol. 71, pp. 1090-1104, 2014.
63. Gailis, R., Gunatilaka, A., Lopes, L., Skortsov, A. and Smith-Miles, K., “Managing uncertainty in early estimation of epidemic behaviours using scenario trees”, IIE Transactions, vol. 46, no. 8, pp. 828-842, 2014. Awarded Best Applications Paper in 2014/2015 journal awards.
62. Smith-Miles, K., Baatar, D., “Exploring the role of graph spectra in graph coloring algorithm performance”, Discrete Applied Mathematics, vol. 176, pp. 107-121, 2014.
61. Tian, T. and Smith-Miles, K., “Mathematical modeling of GATA-switching for regulating the differentiation of hematopoietic stem cell”, BMC Systems Biology, vol. 8, Suppl. 1: S8, 2014.
60. Lopes, L. and Smith-Miles, K., “Generating Applicable Synthetic Instances for Branch Problems”, Operations Research, vol. 61, no. 3, pp. 563-577, 2013.
59. Elgindy, K., Smith-Miles, K. and Miller, B., "Fast, Accurate, and Small-Scale Direct Trajectory Optimization using a Gegenbauer Transcription Method", Journal of Computational and Applied Mathematics, vol. 251, pp. 93-116, 2013.
58. Elgindy, K. and Smith-Miles, K., “Solving boundary value, integral, and integro-differential equations using a Gegenbauer integration matrices”, Journal of Computational and Applied Mathematics, vol. 237, no. 1, pp. 307-325, 2013.
57. Elgindy, K. and Smith-Miles, K., “Optimal Gegenbauer Quadrature Over Arbitrary Integration Nodes”, Journal of Computational and Applied Mathematics, vol. 242, pp. 82–106, 2013.
56. Wu, Q., Smith-Miles, K., Zhou, T. and Tian, T., “Stochastic modelling of biochemical systems of multi-step reactions using a simplified two-variable model”, BMC Systems Biology, vol. 7, no. 4, article 14, 13pp. 2013.
55. Elgindy, K. and Smith-Miles, K., “On the optimization of Gegenbauer operational matrix of integration”, Advances in Computational Mathematics, vol. 39, no.3-4, pp. 511-524, 2013.
54. Smith-Miles, K. A., and Lopes, L. B., “Measuring Instance Difficulty for Combinatorial Optimization Problems”, Computers and Operations Research, vol. 39, no. 5, pp. 875-889, 2012.
53. Duff, C., Smith-Miles, K., Lopes, L. and Tian, T., "Mathematical Modelling of Stem Cell Differentiation: the PU.1-GATA-1 Interaction", Journal of Mathematical Biology, vol. 64, no. 3, pp. 449-468, 2012.
52. Halley, J.D, Smith-Miles, K., Winkler, D., Kalkan, T. Huang, S. and Smith, A. “Self-organizing circuitry and emergent computation in mouse embryonic stem cells”, Stem Cell Research, vo. 8, pp. 324-333, 2012.
51. Phua, C., Smith-Miles, K. A., Lee, V., and Gayler, R., “Resilient Identity Crime Detection”, IEEE Transactions on Knowledge and Data Engineering, vol. 24, no. 3, pp. 533-546, 2012.
50. Smith-Miles, K. and van Hemert, J. “Discovering the Suitability of Optimisation Algorithms by Learning from Evolved Instances”, Annals of Mathematics and Artificial Intelligence, vol. 61, no. 2, pp. 87-104, 2011.
49. Geng, X., Smith-Miles, K. A., Zhou, Z. H., and Wang, L., “Face Image Modeling by Multilinear Subspace Analysis with Missing Values “,IEEE Transactions On Systems, Man and Cybernetics, Part B, vol. 41, no. 3, pp. 881-892, 2011.
48. Carta D., Villanova L., Costacurta S., Patelli A., Poli I., Vezzù S., Scopece P., Smith-Miles K., Hyndman R. J., Hill A., Falcaro P. “Optimization of a hybrid amino-methyl-silane sol-gel coating for microarray applications using an evolutionary model-based approach”, Analytical Chemistry, vol. 83, no. 16, pp. 6373–6380, 2011.
47. Donald E. Brown, Fazel Famili, Gerhard Paass, Kate Smith-Miles, Lyn C. Thomas, Richard Weber, Ricardo Baeza-Yates, Cristián Bravo, Gaston L’Huillier and Sebastian Maldonado (2011): Future trends in business analytics and optimization. Intelligent Data Analysis, vol.15, pp. 1001–1017, 2011.
46. Geng, X., Smith-Miles, K. A., Wang, L., Li, M., and Wu, Q., "Context-Aware Fusion: A Case Study on Fusion of Gait and Face for Human Identification in Video", Pattern Recognition, vol. 43, pp. 3660-3673, 2010.
45. Wang, X., Smith, K. A., and Hyndman, R., "Rule induction for forecasting method selection: meta-learning the characteristics of univariate time series", Neurocomputing, vol. 72, no. 10-12, pp. 2581-2594, 2009.
44. Phua, C., Lee, V. C. S., Gayler, R, Smith-Miles, K., “On the Communal Analysis Suspicion Scoring for Identity Crime in Streaming Credit Applications”, European Journal of Operational Research, vol. 195, pp. 595-612, 2009.
43. Sturmberg, J., Siew, E. G., Churilov, L. and Smith-Miles, K. A., “Identifying patterns in primary care consultations: a cluster analysis”, Journal of Evaluation in Clinical Practice, vol. 15, pp. 558-564, 2009.
42. Geng, X., Zhou, Z. H., and Smith-Miles, K., “Individual Stable Space: An Approach to Face Recognition under Uncontrolled Conditions”, IEEE Transactions on Neural Networks, vol. 19, no. 8, pp. 1354-1368, 2008.
41. Smith-Miles, K. A., “Cross-disciplinary perspectives on meta-learning for algorithm selection”, ACM Computing Surveys, vol. 41, no. 1, article 6, 2008.
40. Geng, X., Zhou, Z.-H., and Smith-Miles, K. A., “Automatic Age Estimation Based on Facial Aging Patterns”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol 29, no. 12, pp. 2234-2240, 2007.
39. Wickramasinghe, K., Alahakoon, D. and Smith-Miles, K., “A Novel Episodic Associative Memory Model for Enhanced Classification Accuracy”, Pattern Recognition Letters, vol. 28, no. 10, pp. 1193-1202, 2007.
38. Ali, S. and Smith, K. A., “On Optimal Degree Selection for Polynomial Kernel with Support Vector Machines: Theoretical and Empirical Investigations”, International Journal of Knowledge-Based and Intelligent Engineering Systems, vol. 11, pp.1-18, 2007.
37. Ashrafi, M.Z., Taniar, D. and Smith, K., “Redundant association rules reduction techniques”, International Journal of Business Intelligence and Data Mining, vol. 2, no. 1, pp. 29-63, 2007.
36. Wang, X., Smith, K. A., Hyndman, R., “Characteristic-based Clustering for Time Series Data", Data Mining and Knowledge Discovery, vol. 13, no. 3, pp. 335-364, 2006.
35. Ali, S. and Smith-Miles, K. A., "A meta-learning approach to automatic kernel selection for support vector machines", Neurocomputing, vol. 70, pp. 173-186, 2006.
34. Tan, L., Taniar, D., Smith, K. A., “Maximum entropy estimated distribution classification model”, International Journal of Hybrid Intelligent Systems, vol. 3, no. 1, pp. 1-10, 2006.
33. Ali, S. and Smith, K. A., "On learning algorithm selection for classification", Applied Soft Computing, vol. 6, no. 2, pp. 119-138, 2006.
32. Tan, L., Taniar, D., Smith, K. A., “A clustering algorithm based on an estimated distribution model”, International Journal of Business Intelligence and Data Mining, vol. 1, no. 2, pp. 229-245, 2005.
31. Ali, S. and Smith, K. A., "Kernel width selection for SVM classification: a meta learning approach", International Journal of Data Warehousing and Mining, vol. 1, pp. 78-97, 2005.
30. Kwok, T. and Smith, K. A., "Optimization via Intermittency with a Self-Organizing Neural Network", Neural Computation, vol. 17, pp. 2454-2481, 2005.
29. Churilov, L., Siew, E. G., Smith, K. A., and Wassertheil, J., “Towards data-driven acute in-patient classification schemes: a hospital management perspective”, Central European Journal of Operations Research, vol. 13, no. 4, pp. 365-392, 2005.
28. Churilov, L., Bagirov, A., Schwartz, D., Smith, K. A., Dally, M., “Data mining with combined use of optimisation techniques and self-organizing maps for improving risk grouping rules”, Journal of Management Information Systems, vol. 21, no. 4, pp. 85-100, 2005.
27. Ashrafi, M. Z., Taniar, D. and Smith K.A., "PPDAM: Privacy-preserving distributed association rule mining algorithm", International Journal of Intelligent Information Technologies, vol. 1, no. 1, pp. 49-69, 2005.
26. Ashrafi, M. Z., Taniar, D. and Smith K.A, “ODAM: An Optimized Distributed Association Rule Mining Algorithm”, IEEE Distributed Systems Online, IEEE Computer Society, vol. 5, no. 3, pp 1-18, 2004.
25. Wang X., Abraham A., and Smith K.A., "Web Traffic Mining Using a Concurrent Neuro-Fuzzy Approach", Journal of Network and Computer Application, Elsevier Science, Volume 28, Issue 2, pp. 147-165, 2004.
24. Black, J., Benke, G., Smith K.A., and Fritsch, L., "Artificial Neural Networks and Job-specific Modules to Assess Occupational Exposure", Annals of Occupational Hygiene, vol. 48, no. 7, pp. 595-600, 2004.
23. Kwok, T. and Smith, K. A., "A noisy self-organizing neural network with bifurcation dynamics for combinatorial optimization", IEEE Transactions on Neural Networks, vol. 15, no. 1, pp. 84-98, 2004.
22. Beh, C., Smith, K. A. and Webley, P. A., "The VSA process for oxygen enrichment - process description and dynamic modelling using neural networks", International Journal of Smart Engineering System Design, vol. 5, no. 1, pp. 1-9, 2003.
21. Smith, K. A. and Ng, A., "Web page clustering using a self-organizing map of user navigation patterns ", Decision Support Systems Journal, special issue on web data mining, vol. 35, no. 2, pp. 245-256, 2003.
20. Yeo, A. C. and Smith, K. A., "Implementing a data mining solution for an automobile insurance company: reconciling theoretical benefits with practical considerations", Annals of Cases in Information Technology, vol. 5, pp. 63-73, 2003.
19. Smith, K. A., Abramson, D. and Duke, D., “Hopfield Neural Networks for Timetabling: Formulations, Methods, and Comparative Results”, International Journal of Computers and Industrial Engineering, vol. 44, no. 2 pp 283 – 305, 2003.
18. Domingues, J. J., Lozano, S., Calle, M. and Smith, K. A., "A new method for combinatorial optimization: genetic neighbourhood search", Neural Network World, vol. 6, pp. 533-547, 2002.
17. Guerrero, F., Lozano, S., Smith, K., and Kwok, T., "Manufacturing cell formation using a new self-organising neural network", International Journal of Computers and Industrial Engineering, vol. 42, no. 2-4, pp. 377-392, 2002.
16. Yeo, A. C., Smith, K. A., Willis, R. J. and Brooks, M., "A mathematical programming approach to optimise insurance premium pricing within a data mining framework", Journal of the Operational Research Society, vol. 53, no. 11, pp. 1197-1203, 2002.
15. Smith, K. A., Potvin, J-Y., and Kwok, T., "Neural network models for combinatorial optimization: deterministic, stochastic and chaotic approaches", Control and Cybernetics, vol. 31, no. 2, pp. 183-216, 2002.
14. Yeo, A. C., Smith, K. A., Willis, R. J. and Brooks, M., "Clustering technique for risk classification and prediction of claim cost in the automobile insurance industry", International Journal of Intelligent Systems in Accounting, Finance and Management, vol. 10, pp. 39-50, 2001.
13. Kwok, T. and Smith, K. A., "Experimental Analysis of Chaotic Neural Network Models for Combinatorial Optimization under a Unifying Framework", Neural Networks, vol. 13, no. 7, pp. 731-744, 2000.
12. Smith, K. A. and Gupta, J. N. D., "Neural Networks in Business: Techniques and Applications for the Operations Researcher", Computers and Operations Research, vol. 27, no. 11, pp. 1023-1044, 2000.
11. Smith, K. A., Willis, R. J., and Brooks, M., "An Analysis of Customer Retention and Insurance Claim Patterns Using Data Mining: A Case Study", Journal of the Operational Research Society, vol. 51, no. 5, pp. 532-541, 2000.
10. Smith, K., Kim, B. and Sargent, G., "Intelligent approaches to channel assignment in real wireless communication networks", International Journal of Smart Engineering System Design, vol. 2, pp. 89-107, 1999.
9. Kwok, T. and Smith, K. A., "A Unified Framework for Chaotic Neural Network Approaches to Combinatorial Optimisation", IEEE Transactions on Neural Networks, vol. 10, no. 4, pp. 978-981, 1999.
8. Smith, K. "Neural Networks for Combinatorial Optimisation: A review of more than a decade of research", INFORMS Journal on Computing, vol. 11, no. 1, pp. 15-34, 1999.
7. Wang, L. and Smith, K., "On Chaotic Simulated Annealing", IEEE Transactions on Neural Networks, vol. 9, no. 4, pp. 716-718, 1998.
6. Smith, K., Palaniswami, M. and Krishnamoorthy, M., "Neural Techniques for Combinatorial Optimisation with Applications", IEEE Transactions on Neural Networks, vol. 9, no. 6, pp. 1301-1318, 1998.
5. Smith, K, and Palaniswami, M., "Static and Dynamic Channel Assignment using Neural Networks", IEEE Journal on Selected Areas in Communications, vol. 15, no. 2, pp. 238-249, 1997.
4. Smith, K., Krishnamoorthy, M. and Palaniswami, M., "Neural versus Traditional Approaches to the Location of Interacting Hub Facilities", Location Science, vol. 4, no. 3, pp. 155-171, 1996.
3. Smith, K., Palaniswami, M. and Krishnamoorthy, M., “Traditional Heuristic versus Hopfield Neural Network Approaches to a Car Sequencing Problem”, European Journal of Operational Research, vol. 93, no. 2, pp. 300-316, 1996.
2. Smith, K., Palaniswami, M. and Krishnamoorthy, M., “A Hybrid Neural Approach to Combinatorial Optimisation”, Computers and Operations Research, vol. 23, no. 6, pp. 597-610, 1996.
1. Smith, K., “An argument for abandoning the Travelling Salesman Problem as a neural network benchmark”, IEEE Transactions on Neural Networks, vol. 7, no. 6, pp. 1542-1544, 1996.
Books
2. Smith, K. A. and Gupta, J. N. D (eds.), Neural Networks in Business: Techniques and Applications, Idea Group Publishing, Hershey, Pennsylvania, 2002 (ISBN 1-930708-31-9).
1. Smith, K. A., Introduction to Neural Networks and Data Mining for Business Applications, Eruditions Publishing, Emerald, Victoria, 1999 (ISBN 1-86491-004-6).
Edited Proceedings or Special Issues of Journals
5. Weber, R. and Smith-Miles, K. A. (eds.), Intelligent Data Analysis, Special Issue on Business Analytics and Optimization, Elsevier Science, Elsevier Science, vol. 18, no. 1, 2014.
4. Abraham, A., Smith, K. A., Jain, R., and Jain, L., (eds.), Journal of Computer and Network Applications, Special Issue on Network and Information Security: A Computational Intelligence Approach, Elsevier Science, vol. 30, no. 1, 2007.
3. Ong, K. L., Smith-Miles, K. A., Lee, V. C. S., and Ng W. K., Proceedings International Workshop on Integrating AI and Data Mining (AIDM'06), IEEE Computer Society Press, 2006.
2. Smith, K. A. (ed.), Computers and Operations Research, Special Issue on Applications of Neural Networks, Elsevier Science, vol. 32, no. 10, 2005.
1. Gupta, J. N. D and Smith, K. A. (eds.), Computers and Operations Research, Special Issue on Neural Networks in Business, Elsevier Science, vol. 27, no. 11-12, 2000 (ISSN 0305-0548).
Edited Proceedings or Special Issues of Journals
Book Chapters
21. Steponavice, I., Shirazi-Manesh, M., Hyndman, R. J., Smith-Miles, K. and Villanova, L., “On Sampling Methods for Costly Multiobjective Black-box Optimization” in Advances in Stochastic and Deterministic Global Optimization (P.M. Pardalos, A. Zhigljavsky, J. Zilinskas, eds.), Springer Optimization and Its Applications, vol. 107, p. 273-296, Springer, 2016.
20. Smith-Miles, K., Wreford, B., Lopes, L. and Insani, N., “Predicting metaheuristic performance on graph coloring problems using data mining”, in E. Talbi (ed.), Hybrid Metaheuristics, Springer Series in Computational Intelligence, Springer, 2013. ISBN 978-3-642-30670-9
19. Smith-Miles, K. A., “Exploratory Data Analysis”, International Encyclopedia of Statistical Sciences, pp. 486-488, ISBN 978-3-642-04897-5, Springer-Verlag Berlin 2011.
18. Smith-Miles, K. A., and Islam, R. M. D., “Meta-learning of instance selection for data summarization”, in W. Duch, K. Grabczewski, N. Jankowski (eds.), Meta-learning in Computational Intelligence, Studies in Computational Intelligence, Springer, Berlin, vol. 358, pp. 77-95, 2011.
17. Geng, X. and Smith-Miles, K. A., “Incremental Learning”, in Stan Z. Li (ed.), Encyclopedia of Biometrics, Springer, NY, USA, pp. 731-735, 2009.
16. Phua, C. Lee, V., Smith-Miles, K., “The Personal Name Problem and a Data Mining Solution”, in Wang, J. (ed.), Encyclopaedia of Data Warehousing and Mining - 2nd Edition, vol. 3, Information Science Publishing, 2009.
15. Smith, K. A., "Neural Networks for Prediction and Classification", in Wang, J.(ed.), Encyclopaedia of Data Warehousing and Mining, Information Science Publishing, vol. 2, pp. 865-869, 2006.
14. Ashrafi, M. Z., Taniar, D., Smith, K., “An Efficient Compression Technique for Vertical Mining Methods”, in D.Taniar (ed.), Research and Trends in Data Mining Technologies and Applications (Advances in Data Warehousing and Mining), Chapter 6, Idea Group Publishing, Hershey PA, 2007. (ISBN 1-59904-271-1).
13. Ali, S. and Smith, K.A., "Kernel width selection for SVM classification: a meta-learning approach", in G. Felici and C. Vercellis (eds.), Mathematical Methods for Knowledge Discovery and Data Mining, pp. 101-115, IGI Global, 2007. (ISBN 1-59904-528-1) .
12. Ashrafi, M. Z., Taniar, D., Smith-Miles, K. “Towards Distributed Association Rule Mining Privacy”, in V. Sugumaran (ed.), Application of Agents and Intelligent Information Technologies (Advances in Intelligent Information Technologies), Chapter 11, Idea Group Press, Hershey PA, 2006. (ISBN 1-59904-265-7)
11. Ashrafi, M.Z., Taniar, D., and Smith, K.A., "Distributed Association Rule Mining", in Wang, J.(ed.), Encyclopedia of Data Warehousing and Mining, Information Science Publishing, vol. 1, pp. 403-407, 2006.
10. Siew, E. G., Smith, K. A., Churilov, L. and Wassertheil, J., "A longitudinal comparison of supervised and unsupervised learning approaches to iso-resource grouping for acute healthcare in Australia ", in Saman Halgamuge and Lipo Wang (Eds.), Classification and Clustering for Knowledge Discovery, Chapter 21, Studies in Computational Intelligence, Vol. 4, Springer-Verlag, (ISBN: 3-540-26073-0), 2005.
9. Wang, X., Abraham, A. and Smith, K. A., "Soft Computing Paradigms for Web Access Pattern Analysis ", in Saman Halgamuge and Lipo Wang (Eds.), Classification and Clustering for Knowledge Discovery, Chapter 15, Studies in Computational Intelligence, Vol. 4, Springer-Verlag, (ISBN: 3-540-26073-0), 2005.
8. Dale, M. and Smith, K. A., "A Porter Framework for Understanding the Strategic Potential of Data Mining for the Australian Banking Industry", H. Nemati and C. Barko (eds.), Organizational Data Mining: Leveraging Enterprise Data Resources for Optimal Performance, Idea Group Publishing, Hershey, Pennsylvania, Chapter 3, pp. 25-45, 2004.
7. Yeo, A. C. and Smith, K. A., "An Integrated Data Mining Approach to Premium Pricing for Automobile Insurance Industry", A. Shapiro and L. Jain (eds.), Intelligent Techniques In The Insurance Industry: Theory and Applications, World Scientific Press, Singapore, Chapter 5, pp. 199-228, (ISBN: 981-238-718-8), 2003.
6. Yeo, A. C., Smith, K. A., Willis, R. J. and Brooks, M. "A comparison of soft computing and traditional approaches for risk classification and claim cost prediction in the automobile insurance industry", L. Reznik and V. Kreinovich (eds.), Soft Computing in Measurement and Information Acquisition, Studies in Fuzziness and Soft Computing, vol. 127, Springer-Verlag, Chapter 18, pp. 249-261, 2003.
5. Bedingfield, S. and Smith, K. A., "Evolutionary rule generation and its application to credit scoring", L. Reznik and V. Kreinovich (eds.), Soft Computing in Measurement and Information Acquisition, Studies in Fuzziness and Soft Computing, vol. 127, Springer-Verlag, Chapter 19, pp. 262-276, 2003.
4. Potvin, J.-Y. and Smith, K. A., "Artificial Neural Networks", in F. Glover and G. Kochenberger (eds.), Handbook of Metaheuristics, Chapter 15, Kluwer Academic Publishers, Boston, 2003. (ISBN 1-4020-7263-5)
3. Smith, K. A. and Lokmic, L., "Combining Supervised and Unsupervised Neural Networks for Improving Cash Flow Forecasting", in Smith, K. A. and Gupta, J. N.D (eds.), Neural Networks in Business: Techniques and Applications, Idea Group Publishing, Hershey, Pennsylvania, Chapter 15, pp. 236-244, 2002.
2. Yeo, A. C., Smith, K. A., Willis, R. J., and Brooks, M., "Using Neural Networks to Model Premium Price Sensitivity of Automobile Insurance Customers", in Smith, K. A. and Gupta, J. N. D (eds.), Neural Networks in Business: Techniques and Applications, Idea Group Publishing, Hershey, Pennsylvania, Chapter 3, pp. 41-54, 2002.
1. Smith, K. A., "Neural Networks for Business: An Introduction", in Smith, K. A. and Gupta, J. N. D (eds.), Neural Networks in Business: Techniques and Applications, Idea Group Publishing, Hershey, Pennsylvania, Chapter 1, pp. 1-24, 2002.
Refereed conference papers
153. Chen, Z., Liu, Y., Gong, M., Du, B., Qian, G., and Smith-Miles, K., "Generating Dynamic Kernels via Transformers for Lane Detection", International Conference on Computer Vision, in press, 2023.
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152. dos Santos Fernandes, L. H. , Lorena, A. C. and Smith-Miles, K., "Generating Diverse Clustering Datasets with Targeted Characteristics", Proceedings of the International Joint Conference on Neural Networks, BRACIS conference, 2022.
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151. Smith-Miles, K., Bista, S. and Jiang, L., "An instance space analysis of combat simulations to understand the impact of force and information advantage on survival ratios", Proceedings of the 24th International Congress on Modelling and Simulation (MODSIM), Sydney, December 2021.
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150. Yap, E., Munoz, M. A., Smith-Miles, K. and Liefooghe, A., "Instance Space Analysis of Combinatorial Multi-objective Optimisation Problems", Proceedings of the World Congress on Computational Intelligence, 2020.
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149. Kletzander, L., Musliu, N., and Smith-Miles, K., "Instance Space Analysis for a Personnel Scheduling Problem", Proceedings of the International Joint Conference on Artificial Intelligence, workshop on Data Science Meets Optimisation, Macao, 2019.
148. Kandanaarachchi, S., Munoz, M. A., and Smith-Miles, K., "Instance Space Analysis for Unsupervised Outlier Detection", SIAM International Conference on Data Mining, workshop on Evaluation and Experimental Design in Data Mining and Machine Learning, May 1-3, Calgary, 2019.
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147. Chan, C., Aleti, A., Heger, A. and Smith-Miles, K., "Evolving Stellar Models to Find the Origins of Our Galaxy", Proceedings of GECCO'19, July 13–17, 2019, Prague, 2019.
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146. Segovia, C. and Smith-Miles, K., ""Integrating Game Theory and Data Mining for Dynamic Distribution of Police to Combat Crime", in Proceedings of the Workshop on Data Science for Crime Analytics, International Conference on Web Intelligence, Santiago, 2018.
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145. Edwards, S., Baatar, D., Ernst, A. and Smith-Miles, K., "The Liquid Handling Robot Scheduling Problem", Proceedings of the 28th International Conference on Automated Planning and Scheduling, workshop on Scheduling and Planning Applications, Delft, pp. 18-26, 2018.
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144. Lewis, R., Smith-Miles, K., and Phillips, K., "The School Bus Routing Problem: An Analysis and Algorithm", International Workshop on Combinatorial Algorithms, Lecture Notes in Computer Science, vol. 10765, pp. 287-298, 2018. https://doi.org/10.1007/978-3-319-78825-8_24
143. Edwards, S., Baatar, D., Bowly, S., & Smith-Miles, K. (2017). "Symmetry breaking in a special case of the RCPSP / max". In Proceedings of the 8th Multidisciplinary International Conference on Scheduling : Theory and Applications (MISTA 2017), 05 - 08 Dec 2017, Kuala Lumpur, Malaysia, pp. 315-318, 2017.
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142. Muñoz, M. A. and Smith-Miles, K. "Generating custom classification datasets by targeting the instance space", in Proceedings of
GECCO ’17 Companion, Berlin, Germany, July 15-19, 2017. DOI: http://dx.doi.org/10.1145/3067695.3082532
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141. Muñoz, M. A. and Smith-Miles, K. "Non-parametric model of the space of continuous black-box optimization problems", in Proceedings of
GECCO ’17 Companion, Berlin, Germany, July 15-19, 2017.
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140. Foumani, M., Gunawan, I. and Smith-Miles, K., "Resolution of deadlocks in a robotic cell scheduling problem with post-process inspection system: avoidance and recovery scenarios", in Proceedings of the IEEE International Conference on Industrial Engineering and Engineering Management, pp. 1107 - 1111, 2015.
139. Foumani, M., Gunawan, I. and Smith-Miles, K., "Stochastic Scheduling of an Automated Two-Machine Robotic Cell with In-Process Inspection System", in Proceedings of the 45th Computers & Industrial Engineering Conference, pp. 528-536, 2015.
138. Munoz, M. and Smith-Miles, K., "Effects of function translation and dimensionality reduction on landscape analysis", in Proceedings of the 2015 IEEE Congress on Evolutionary Computation (CEC2015), pp. 1336 - 1342, 2015.
137. Ryan, S., Kandanaarachchi, S. and Smith-Miles, K., "Support Vector Machines for Characterising Whipple Shield Performance", in Proceedings of the 2015 Hypervelocity Impact Symposium, Boulder CO, April 2015 - Procedia Engineering, vol. 103, pp. 522-529, 2015.
136. Steponavice, I., Hyndman, R., Smith-Miles, K. and Villanova, L., “Efficient Identification of the Pareto Optimal Set”, Learning and Intelligent Optimization conference, Springer Lecture Notes in Computer Science, vol. 8426, pp. 341 - 352, 2014.
135. Wu, Q., Smith-Miles, K. and Tian, T., “Approximate Bayesian Computation using the simulated likelihood density for estimating rate constants in biochemical reaction systems”, 2013 IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2013), pp. 416-421, 2013.
134. Yanfei Kang, Kate Smith-Miles and Danijel Belusic, “How to Extract Meaningful Shapes from Noisy Time-Series Subsequences?”, 2013 IEEE Symposium on Computational Intelligence and Data Mining (CIDM), vol., no., pp.65-72, 16-19 April 2013.
133. Ladha, S., Agarwal, A., Chandran, S. and Smith-Miles, K., “Multi-User Natural Interaction with Sensor on Activity”, Workshop on User-Centred Computer Vision, UCCV 2013, Winter Vision Meetings, Clearwater Beach, Florida, Jang, D., Mase, K. (eds), IEEE press, pp. 25-30, 2013.
132.Insani, N., Smith-Miles, K. and Baatar, D., “Selecting suitable solution strategies for classes of graph coloring instances using data mining”, ICITEE 2013 - The 5th International Conference on Information Technology and Electrical Engineering, Yogyakarta, Indonesia.
131. Wu, Q. Smith-Miles, K., and Tian, T., “A two-variable model for stochastic modelling of chemical events with multi-step reactions”, in Proceedings of the 2012 IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2012), pp. 270-275, IEEE Press, 2012.
130.Elgindy, K., Smith-Miles, K., Miller, B., “Solving optimal control problems using a Gegenbauer transcription method”, in Proceedings of the 2012 Australian Control Conference, pp. 417-424, Engineers Australia, 2012.
129. Smith-Miles, K. and Tan, T. “Measuring Algorithm Footprints in Instance Space”, in Proceedings of the 2012 IEEE Congress on Evolutionary Computation, pp. 3446-3453, 2012.
128. Gunnersen, S., Smith-Miles, K. and Lee, V. C. S. “Towards Objective Data Selection in Bankruptcy Prediction”, in Proceedings of the 2012 IEEE Congress on Evolutionary Computation, pp. 201-208, 2012.
127. Smith-Miles, K. A., and Lopes, L. B., “Generalising Algorithm Performance in Instance Space: A timetabling case study”, Proceedings of the 5th Learning and Intelligent Optimization workshop, Lecture Notes in Computer Science, vol. 6683, pp. 524-539, Springer, 2011.
126. Gunnersen, S., Smith-Miles, K. A., and Lee, V. C. S., “SpecVCMV: Improving Cluster Visualisation”, in Proceedings of the 37th Annual Conference of the IEEE Industrial Electronics Society, 2011.
125. Ladha, S., Chandra, S. and Smith-Miles, K. A., “Projection Defocus Correction using Adaptive Kernel Sampling and Geometric Correction in Multi-planar Environments”, in Proceedings IEEE Computer Vision and Pattern Recognition (CVPR), Colorado Springs, 2011.
124. Geng, X. Fang, E. and Smith-Miles, K. “Fusion of Face and Voice for Automatic Human Age Estimation”, International Conference on Computer Design and Applications”, In: Proceedings of the 3rd International Conference on Computer Design and Applications, (ICCDA’11), Xi’an, China, 2011, pp. 451-456.
123.Smith-Miles, K. A., van Hemert, J., Lim, Y., “Understanding TSP Difficulty by Learning from Evolved Instances”, Proceedings of Learning and Intelligent Optimization, LION 4, Lecture Notes in Computer Science, vol. 6073, pp. 266-280, 2010.
122. Lopes, L. B. and Smith-Miles, K. A., “Pitfalls in Instance Generation for Udine Timetabling”, Proceedings of Learning and Intelligent Optimization, LION 4, Lecture Notes in Computer Science, vol. 6073, pp. 299-302, 2010.
121. Villanova, L., Falcaro, P., Carta, D., Poli, I., Hyndman, R. and Smith-Miles, K., “Functionalization of Microarray Devices: Process Optimization Using a Multiobjective PSO and Multiresponse MARS Modeling”, WCCI2010, in press.
120. Smith-Miles, K. and Islam, R., “Meta-learning for Data Summarization Based on Instance Selection Method”, WCCI 2010, in press.
119. Geng, X., Smith-Miles, K., Zhou, Z. H., "Facial Age Estimation by Learning from Label Distributions", AAAI 2010, in press.
118. Smith-Miles, K. A., James, R. J. W., Giffin, J. W. and Tu, Y., “A Knowledge Discovery Approach to Understanding Relationships between Scheduling Problem Structure and Heuristic Performance”, in Stutzle, T. (ed.), Selected papers of the Third International Conference on Learning and Intelligent Optimization, LION 3, Lecture Notes in Computer Science, vol. 5851, pp. 89-103, 2009.
117. Geng, X., Smith-Miles, K. A., Zhou, Z. H., Liang, W. “Face Image Modeling by Multilinear Subspace Analysis with Missing Values”, Proceedings of the 17th ACM International Conference on Multimedia, Beijing, China, pp. 629-632, 2009.
116. Geng, X. and Smith-Miles, K. A. “Facial age estimation by multilinear subspace analysis”, IEEE International Conference on Acoustics, Speech and Signal Processing, 2009. ICASSP 2009, Taipei, pp. 865-868, 2009.
115. Smith-Miles, K. A., James, R. J. W., Giffin, J. W. and Tu, Y., “Discovering Relationships between Scheduling Problem Structure and Heuristic Performance”, Proceedings of the 2009 Operations Research Society of New Zealand conference, 2009.
114. Geng, X., Smith-Miles, K. and Zhou, Z. H., “Facial Age Estimation by Nonlinear Aging Pattern Subspace”, Proceedings of the 16th ACM International Conference on Multimedia, pp. 721-724, 2008.
113. Phua, C., Lee, V. C. S., Gayler, R. and Smith-Miles, K., “Utility of Real-time Decision-making in Commercial Data Stream Mining Domains”, 5th International Conference on Service Systems and Service Management (ICSSSM'08).
112. Smith-Miles, K. A., "Towards insightful algorithm selection for optimisation using meta-learning concepts", International Joint Conference on Neural Networks, Workshop on Hybrid Systems, Ensembles, and Meta-Learning Algorithms, pp. 4118-4124, 2008.
111. Geng, X., Wang, L., Li, M., Wu, Q. and Smith-Miles, K., “Adaptive Fusion of Gait and Face for Human Identification in Video”, Proceedings IEEE 2008 Workshop on Application of Computer Vision, Colorado, USA, pp.1-6, January 2008.
110. Siew, E. G., Churilov, L. Smith-Miles, K.A. and Sturmberg, J. P., “Using supervised and unsupervised techniques to determine groups of patients with different continuity of care”, In Proceedings of PAKDD 2008, pp. 715-722, 2008.
109. Smith-Miles, K. A., “Generalizing meta-learning for algorithm selection via Rice’s framework”, in Giraud-Carrier, C. and Vilalta, R. (eds.), Proceedings of the Meta-learning Workshop, International Joint Conference on Neural Networks, pp. 19-23, 2007 (invited paper).
108. Smith-Miles, K.A. “Generalising meta-learning concepts: from machine learning to meta-heuristics”, in Proceedings of the 7th Meta-heuristics International Conference (MIC’07), Montreal, June 25-29th, 2007.
107. Smith-Miles, K. A., “Meta-Learning: From Classification to Forecasting, to Optimization, and Beyond”, Proceedings of the 6th IEEE/ACIS International Conference on Computer and Information Science (ICIS 2007), IEEE Computer Society, p. 2, 2007 (keynote address).
106. Phua, C. Lee, V., Smith-Miles, K. and Gayler, R., “Adaptive Communal Detection in Search of Adversarial Identity Crime”. 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'07), Workshop on Domain Driven Data Mining (DDDM'07), pp. 1-10, 2007.
105. Phua, C. Smith-Miles, K. Lee, V. and Gayler, R., “Adaptive Spike Detection for Resilient Data Stream Mining”, In Christen, P., Kennedy, P.J., Li, J., Kolyshkina, I. and Williams, G.J., (Eds.), Proc. Sixth Australasian Data Mining Conference, CRPIT, vol. 70. pp. 181-188, 2007.
104. Geng, X., Wang, L., Li, M., Wu, Q. and Smith-Miles, K., “Distance-driven Fusion of Gait and Face for Human Identification in Video”, Proceedings of Image and Vision Computing New Zealand Conference (ICVNZ’07), pp. 19-24, 2007.
103. Bedingfield S. and Smith-Miles, K., “Two stage partial classification for inconsistent and imbalanced classes”, R Munasinghe (ed), 2nd International Conference on Information and Automation 2006 (ICIA 2006), Colombo, Sri Lanka, 14-17 December 2006, IEEE Sri Lanka Section, Colombo, Sri Lanka, ISBN: 1-4244-0555-6, pp 167-171, 2006.
102. Amarasiri, R, Alahakoon, D, Smith-Miles, K.A, “Clustering Massive High Dimensional Data with Dynamic Feature Maps”, Proc. ICONIP, Lecture Notes in Computer Science, vol. 4233, pp. 814-823, 2006.
101. Ali, S., and Smith-Miles, K., “Improved Support Vector Machine Generalisation Using Normalized Input Space”, Proceedings of the 19th Australian Joint Conference on Artificial Intelligence 2006, Lecture Notes in Artificial Intelligence, vol. 4304, pp. 362-371, 2006.
100. Phua, C., Gayler, R., Smith-Miles, K., and Lee, V., “Communal Detection of Implicit Personal Identity Streams”, Proc. 6th IEEE International Conference on Data Mining, workshop on Mining Evolving and Streaming Data, IEEE Computer Society 2006, ISBN 0-7695-2702-7, pp. 620-625, 2006.
99. Chau, R., Yeh, C. H., Smith-Miles, K., "Fuzzy-neuro Web-Based Multilingual Knowledge Management" Proc. ICONIP, Lecture Notes in Computer Science, vol. 4223, pp. 1229-1238, 2006.
98. Chau, R. Smith-Miles, K., Yeh, C. H., “Ontology learning from text: a soft computing paradigm”, ICONIP’06, Lecture Notes in Computer Science, vol. 4234, pp. 295-301, 2006.
97. Phua, C., Lee, V., Gayler, R., and Smith, K. A., “Temporal Representation in Spike Detection of Sparse Personal Identity Streams”, Proceedings of the PAKDD 2006 , Lecture Notes in Computer Science, Springer-Verlag, vol. 3917, pp. 115-126, 2006.
96. Mafruz Zaman Ashrafi, David Taniar, Kate Smith, Redundant Association Rules Reduction Techniques, Proceedings AI2005, pp. 254-263, 2005.
95. Phua C, Gayler R, Lee V and Smith K., “Empirical Scoring of Anomalous Credit Applications with pair-wise matching”, Proceedings of Credit Scoring and Credit Control IX, 2005.
94. Wickramasinghe, L.K., Alahakoon, L.D. and Smith, K.A., “Computation of Meta-Learning Classifiers in Distributed Data Mining using a Novel Cognitive Memory Model”. IEEE/WIC International Conference on Intelligent Agent Technology IAT-2005, September 19-22, France, pp. 180 – 186, 2005.
93. Amarasiri, R, Alahakoon, D, Premaratne, M, Smith, K.A., “HDGSOMr: A High Dimensional Growing Self Organizing Map using Randomness for Efficient Web and Text Mining”, Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence, France, pp. 215-221, 2005.
92. Amarasiri, R, Alahakoon, D, Premaratne, M, Smith, K.A., “Enhancing Clustering Performance of Feature Maps Using Randomness”, Workshop on Self Organizing Maps (WSOM) 05, Paris, France, 2005.
91. X. Wang, K. A. Smith, and R. J. Hyndman, “Characteristic-based Forecasting for Time-series Data”, Proceeding of the 25th International Symposium on Forecasting, San Antonio, Texas June 12-15, 2005.
90. X. Wang, K. A. Smith, and R. J. Hyndman, “Dimension Reduction for Clustering Time Series Using Global Characteristics”, Proceedings of the International Conference on Computing Science 2005, Lecture Notes in Computer Science, Springer-Verlag, Berlin, Heidelberg, vol. 3516, pp. 792-795, May 22-25, Atlanta, 2005.
89. Ashrafi, M.Z., Taniar, D., and Smith, K., "An Efficient Compression Technique for Frequent Itemset Generation in Association Rule Mining", PAKDD 2005, Lecture Notes in Computer Science, Volume 3518, pp. 125-135, Springer-Verlag, 2005.
88. Chau, R., Yeh, C-H., Smith, K.A., "A Personalized Multilingual Web Content Miner: PMWebMiner. ", In O. Gervasi, M.L. Gavrilova, V. Kumar (Eds.), Computational Science and its Application (ICCSA 2005), Lecture Notes in Computer Science, Vol. 3481, Springer-Verlag, Berlin, Heidelberg, Germany, 956-965, 2005.
87. Chau, R., Yeh, C-H., Smith, K.A., "A Neural Network Model for Hierarchical Multilingual Text Categorization", In J. Wang, X. Liao, Z, Yi (Eds.), Advances in Neural Networks (ISNN 2005), Second International Symposium on Neural Networks, Lecture Notes in Computer Science, Vol. 3497, Springer-Verlag, Berlin, Heidelberg, Germany, 238-245, 2005.
86. Amarasiri, R, Alahakoon, D and Smith, K.A., "HDGSOM: A Modified Growing Self-Organizing Map for High Dimensional Data Clustering", Proceedings of Hybrid Intelligent Systems, pp. 216-221, 2004.
85. Amarasiri, R, Alahakoon, D & Smith, K A, "Applications of the Growing Self Organizing Map on High Dimensional Data", Proceedings of the 6th International Information Technology Conference, Sri Lanka, vol. 1, no. 1, pp. 169-174, 2004. Won best paper award.
84. Siew, E-G, Churilov, L, Smith, K A & Sturmberg, J "Using data mining techniques to identify groups of patients with different consultation satisfaction in general practice", Proceedings The Sixth International Conference on Optimization: Techniques and Applications (ICOTA6 2004) , Ballarat, vol. 1, no. 1, pp. 1-12, 2004.
83. Bedingfield, S E & Smith, K A "An Optimisation Methodology for Multi Parameter Heuristics", Proceedings IEEE 4th International Conference on Intelligent Systems Design and Application, vol.1, no.1, pp457-460, 2004.
82. Chau, R, Yeh, C-H & Smith, K A "Personalized Multilingual Web Content Mining", Lecture Notes in Artificial Intelligence, vol. 3213, pp. 155-163, 2004.
81. Ashrafi, M Z, Taniar, D & Smith, K A, "A New Approach of Eliminating Redundant Association Rules'", Lecture Notes in Computer Science , vol. 3180, no. 1, pp. 465-474, 2004.
80. Ashrafi, M Z, Taniar, D & Smith, K A, "Reducing Communication Cost in a Privacy Preserving Distributed Association Rule Mining ", Lecture Notes in Computer Science , vol. 2973, no. 1, pp. 381-392, 2004.
79. Wang, X., Alahakoon, D. and Smith, K. A., "Neural Network Based Analysis of Temporal Search Topic Changes in Query Logs", Proceedings of the 2004 International Conference on Intelligent Agents, Web Technologies, and Internet Commerce, , vol.1, no.1, pp396-407, 2004.
78. Churilov, L., Bagirov, A. M., Schwartz, D., Smith, K. A. and Dally, M., "Improving risk grouping rules for prostate cancer patients with optimization", Proceedings of the 37th Annual Hawaii International Conference on Systems Sciences, vol.1, no.1, pp1-9, 2004.
77. Ashrafi, M. Z., Taniar, D. and Smith, K. A., "A cache-based association rule mining algorithm", Proceedings of 4th International Conference on Intelligent Technologies, pp. 586-596, 2003.
76. Tan, L., Taniar, D. and Smith, K. A., "Adaptive estimation of distribution algorithm with maximum entropy principle", Proceedings of 4th International Conference on Intelligent Technologies, 2003, pp. 597-606, 2003.
75. Bedingfield, S. E. and Smith, K. A., “Predicting bad credit risk: an evolutionary approach", IWANN 2003, Lecture Notes in Computer Science, vol. 2714, pp. 1081-1088, Springer, 2003.
74. Siew, E-G., Smith, K. A., Churilov, L. and Wassertheil, J. "A Comparison of Patient Classification Using Data Mining in Acute Health Care", in A. Abraham, K. Franke, and M. Koppen (eds), Intelligent Systems Design and Applications, Advances in Soft Computing, pp. 599-609, Springer, 2003.
73. Ashrafi, M. Z., Taniar, D. and Smith, K. A., "Towards privacy preserving distributed association rule mining", Proceedings of IWDC 2003, Lecture Notes in Computer Science, 2003, to appear.
72. Ali, S. and Smith, K. A., "Automatic parameter selection for polynomial kernal", Proceedings of the IEEE International Conference on Information Reuse and Integration, 2003, to appear.
71. Ali, S., Smith, K. A., "Matching SVM Kernel’s Suitability to Data Characteristics Using Tree by Fuzzy C-means Clustering", in A. Abraham, M. Koppen, K. Franke (eds.), Design and Application of Hybrid Intelligent Systems, pp. 553-562, IOS Press, Amsterdam, 2003.
70. Schwartz, D., Smith, K. A., Churilov, L., Dally, M., Weber, R., "Improving Risk Grouping Rules for Prostate Cancer Patients Using Self-Organizing Maps", in A. Abraham, M. Koppen, K. Franke (eds.), Design and Application of Hybrid Intelligent Systems, pp. 126-135, IOS Press, Amsterdam, 2003.
69. Kwok, T., Smith, K. A. "A Self-Organising Neural Network with Intermittent Switching for Combinatorial Optimisation", in A. Abraham, M. Koppen, K. Franke (eds.), Design and Application of Hybrid Intelligent Systems, pp. 13-21, IOS Press, Amsterdam, 2003.
68. Calle, M., Lozano, S., Smith, K. A. and Villa, G., "An XML Schema Definition for an Operations Research Modeling Language", in A. Abraham, M. Koppen, K. Franke (eds.), Design and Application of Hybrid Intelligent Systems, pp. 311-320, IOS Press, Amsterdam, 2003.
67. Kwok, T. and Smith, K. A., "Performance-enhancing bifurcations in a self-organising neural network ", Computational Methods in Neural Modeling, Lecture Notes in Computer Science, vol. 2686, Springer-Verlag, Berlin, Part 1, pp. 390-397, 2003.
66. Ashrafi, M. Z., Taniar, D. and Smith, K.A., "A compress-based association mining algorithm for large datasets", Computational Science - ICCS 2003, Lecture Notes in Computer Science, Springer-Verlag, Berlin, vol. 2660, Part IV, pp. 978-987, 2003.
65. J.A. Parejo, J. Racero, F. Guerrero, T. Kwok, and K.A. Smith, "FOM: A framework for metaheuristic optimization", Computational Science - ICCS 2003, Lecture Notes in Computer Science, Springer-Verlag, Berlin, vol. 2660, Part IV, pp. 886-895, 2003.
64. Calle, M., Lozano, S., Smith, K.A., Kwok, T. and Domínguez, J., "A DTD for an XML-based Mathematical Modeling Language", Computational Science – ICCS 2003, Lecture Notes in Computer Science, Springer-Verlag, Berlin, vol. 2660, Part IV, pp. 968-977, 2003.
63. Chau, R., Yeh, C. H., and Smith, K. A., "Developing a personal multilingual Web space", Proceedings of IASTED International Conference on Applied Informatics, pp. 145-150, 2003.
62. Wang, X., Alahakoon, D. and Smith, K. A., "Improved web searching through neural network based index generation", Computational Science - ICCS 2003, Lecture Notes in Computer Science, Springer-Verlag, Berlin, vol. 2659, Part III, pp. 151-158, 2003.
61. Bedingfield, S. and Smith, K. A., "Evolutionary Rule Classification and its Application to Multi-Class Data", Computational Science - ICCS 2003, Lecture Notes in Computer Science, Springer-Verlag, Berlin, vol. 2660, Part IV, pp. 868-876, 2003.
60. Tan, L., Taniar, D., and Smith, K. A., "A Taxonomy for Inter-Model Parallelism in High Performance Data Mining", Proceedings of the International Conference On Enterprise Information Systems, volume 1, pp. 534-539, Ciudad Real, Spain, 2002.
59. Tan, L., Taniar, D., and Smith, K. A., "Parametric Optimization in Data Mining incorporated with GA-based Search", Computational Science, Lecture Notes in Computer Science vol. 2329, Springer-Verlag, pp. 582-591, 2002.
58. Garcia, J. M., Smith, K. A., Lozano, S., Guerrero, F. "A comparison of GRASP and an exact method for solving a production and delivery scheduling problem", in A. Abraham and M. Koppen (eds.), Hybrid Information Systems, Physica-Verlag, Heidelberg, pp. 431-448, 2002.
57. Smith, K. A., Chuan, S. and van der Putten, P., "Determining the validity of clustering for data fusion", in A. Abraham and M. Koppen (eds.), Hybrid Information Systems, Physica-Verlag, Heidelberg, pp. 627-636, 2002.
56. Smith, K. A., Woo, F., Ciesielski, V. and Ibrahim, R., "Matching data mining algorithm suitability to data characteristics using a self-organising map", in A. Abraham and M. Koppen (eds.), Hybrid Information Systems, Physica-Verlag, Heidelberg, pp. 169-180, 2002.
55. Siew, E., Smith, K. A. and Churilov, L., "A neural clustering approach to iso-resource grouping for acute healthcare in Australia", Proceedings of the 35th Annual Hawaii International Conference on Systems Sciences, 2002.
54. Kwok, T. and Smith, K. A., "Chaotic dynamics of the self-organising neural network with weight normalisation for combinatorial optimisation", Proceedings of the Third International NAISO Symposium on Engineering of Intelligent Systems (EIS’2002), Workshop on Chaos and Computation, Spain, paper no. 112. 2002.
53. Ashrafi, M. Z., Taniar, D. and Smith, K. A., "A data mining architecture for clustering environment", Applied Parallel Computing, Lecture Notes in Computer Science, vol. 2346, Springer-Verlag, pp. 89-98, 2002.
52. Kwok, T., Smith, K. A., Lozano, S., Taniar, D., "Parallel Fuzzy c-Means Clustering for Large Data Sets.", Burkhard Monien and Rainer Feldmann (eds.) Euro-Par 2002, Parallel Processing, Proceedings of the 8th International Euro-Par Conference, Paderborn, Germany, Lecture Notes in Computer Science, vol. 2400, Springer-Verlag, pp. 365-374. ISBN 3-540-44049-6. 2002.
51. Ashrafi, M. Z., Taniar, D. and Smith, K. A., "A data mining architecture for distributed environment", Applied Parallel Computing, Lecture Notes in Computer Science, vol. 2346, Springer-Verlag, pp. 27-38, 2002.
50. Garcia, J. M., Lozano, S., Guerrero, F., Smith, K. A., and Calle, M., "Coordinated scheduling of production and delivery from multiple plants", 12th International Conference on Flexible Automation and Intelligent Manufacturing, Dresden, accepted for publication, 2002.
49. Tan, L., Taniar, D., and Smith, K.A., "A New Parallel Genetic Algorithm", Proceedings of The Sixth International Symposium on Parallel Architectures, Algorithms, and Networks (I-SPAN'02), IEEE Computer Society Press, pp. 321-326, 2002.
48. Garcia, J. M., Smith, K. A., Lozano, S., Guerrero, F., Calle, M., "Production and Delivery Scheduling problem with time windows", Proceedings of the 30th International Conference on Computers and Industrial Engineering, pp. 263-268, 2002.
47. Chau, R., Yeh, C.H., and Smith, K.A., "Multilingual text mining for global knowledge discovery using self-organising maps", Proceedings of the 2002 International Conference on Information and Knowledge Engineering, pp. 65-71, 2002.
46. Siew, E., Smith, K. A., Churilov, L., Wassertheil, J. "A comparison of supervised and unsupervised approaches to iso-resource grouping for acute healthcare in Australia", Proceedings of the International Conference on Fuzzy Systems and Knowledge Discovery, vol. 2, pp. 601-605, 2002.
45. Chand, P., Sugianto, L. F., and Smith, K. A., "An overview of the Australian energy market and ancillary services", Proceedings of the AUPEC Conference, 2002.
44. Kwok, T. and Smith, K. A., "Characteristic updating-normalisation dynamics of a self-organising neural network for enhanced combinatorial optimisation", Proceedings of the 9th International Conference on Neural Information Processing, vol. 3, pp. 1146-1152, 2002.
43. Garcia, J. M., Lozano, S., Smith, K. A., Kwok, T. and Villa, G., "Coordinated Scheduling of Production and Delivery From Multiple Plants and with Time Windows Using Genetic Algorithms", Proceedings of the 9th International Conference on Neural Information Processing (ICONIP’2002), Singapore, vol. 3, pp. 1153-1158, 2002.
42. Wang, X., Abraham, A. and Smith, K. A., "Web traffic mining using a concurrent neuro-fuzzy approach", Proceedings of the 2nd International Conference on Hybrid Intelligent Systems, Chile, Soft Computing Systems: Design, Management and Applications, IOS Press Amsterdam, The Netherlands, pp. 853-862, 2002.
41. Wang, X., and Smith, K. A., "Clustering web user interests using self-organizing maps", Proceedings of the 2nd International Conference on Hybrid Intelligent Systems, Chile, Soft Computing Systems: Design, Management and Applications, IOS Press Amsterdam, The Netherlands, pp. 843-852, 2002.
40. Wang, X., Abraham, A. and Smith, K. A., "Soft computing paradigms for web access pattern analysis", Proceedings of the International Conference on Fuzzy Systems and Knowledge Discovery, vol. 2, pp. 631-635, 2002.
39. Ashrafi, M. Z., Taniar, D. and Smith, K. A., "An association mining algorithm for distributed information sources", Proceedings of the 4th Asia-Pacific Conference on Simulated Evolution and Learning, 2002.
38. Garcia, J. M., Lozano, S., Guerrero, F., Calle, M. and Smith, K. A., "Production and vehicle scheduling for ready-mix operations", Proceedings of the 29th International Conference on Computers and Industrial Engineering, pp. 70-76, 2001.
37. Guerrero, F., Lozano, S., Canca, D., Garcia, J. M. and Smith, K. A., "A new self-organising neural network for solving the travelling salesman problem", C. Dagli et al. (Eds.), Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Data Mining, and Complex Systems, ASME Press, vol. 11, pp. 865-870, 2001.
36. Beh, C. C. K., Smith, K. A. and Webley, P. A., "Dynamic modelling using neural networks. Case study - pilot scale VSA process for oxygen production", C. Dagli et al. (Eds.), Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Data Mining, and Complex Systems, ASME Press, vol. 11, pp. 551-556, 2001.
35. Holl, S. J., Flitman, A. M., and Smith, K. A., "Hierarchical neural networks for reducing systematic prediction errors", C. Dagli et al. (Eds.), Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Data Mining, and Complex Systems, ASME Press, vol. 11, pp. 775-780, 2001.
34. Smith, K. A., Spithill, T., Coppel, R. and Smooker, P., "Neural network classification of malaria protein sequences", C. Dagli et al. (Eds.), Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Data Mining, and Complex Systems, ASME Press, vol. 11, pp. 783-788, 2001.
33. Smith, K. A., Woo, F., Ciesielski, V. and Ibrahim, R., "Modelling the relationship between problem characteristics and data mining algorithm performance using neural networks", C. Dagli et al. (Eds.), Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Data Mining, and Complex Systems, ASME Press, vol. 11, pp. 357-362, 2001.
32. Yeo, A. C., Smith, K. A., Willis, R. J. and Brooks, M., “Modelling the Effect of Premium Changes on Insurance Customer Retention Rates Using Neural Networks", Computational Science, Lecture Notes in Computer Science, vol. 2074, Springer-Verlag, Berlin, pp. 390-399, 2001.
31. Lozano, S., Dominguez, J. J., Guerrero, F. and Smith, K. A., “Genetic line search", Computational Science, Lecture Notes in Computer Science, vol. 2074, Springer-Verlag, Berlin, pp. 318-326, 2001.
30. Kwok, T. and Smith, K. A., "Nonlinear system dynamics in the normalisation process of a self-organising neural network for combinatorial optimisation", Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence, Lecture Notes in Computer Science, vol. 2084, Springer-Verlag, Berlin, pp. 733-740, 2001.
29. Smith, K. A. and Gupta, J. N. D., “Continuous function optimisation via gradient descent on a neural network approximation function”, Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence, Lecture Notes in Computer Science, vol. 2084, Springer-Verlag, Berlin, pp. 741-748, 2001.
28. Canca, D., Guerrero, F., Smith, K. A. and Lozano, S., "Facility location in a competitive environment using metaheuristics", Proceedings of the 5th on-line World Conference on Soft Computing in Industrial Applications, pp. 258-263, 2000.
27. Kwok, T. and Smith, K. A., "Improving the Optimisation Properties of a Self-organising Neural Network with Weight Normalisation", Proceedings of the ICSC Symposia on Intelligent Systems and Applications, paper 1513-285, 2000.
26. Ng, A. and Smith, K. A., “Web usage mining by a self-organizing map”, C. Dagli et al. (Eds.), Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Data Mining, and Complex Systems, ASME Press, vol. 10, pp. 495-500, 2000 - Nominated, Best Applications Paper at Conference.
25. Kwok, T. and Smith, K. A., "A self-organisation neural network with attractor nodes for combinatorial optimisation”, C. Dagli et al. (Eds.), Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Data Mining, and Complex Systems, ASME Press, vol. 10, pp. 209-216, 2000.
24. Lozano, S., Guerrero, F., Canca, D. and Smith, K. A., “Generation of route timetables using self-organizing feature maps”, C. Dagli et al. (Eds.), Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Data Mining, and Complex Systems, ASME Press, vol. 10, pp. 1063-1068, 2000.
23. Bedingfield, S. and Smith, K. A., "A Comparison of Fitness Functions for Evolutionary Rule Generation", in M. Mohammadian (ed.), Advances in Intelligent Systems: Theory and Applications, IOS Press, pp. 102-109, 2000.
22. Lokmic, L. and Smith, K. A., "Cash flow forecasting using supervised and unsupervised neural networks", International Joint Conference on Neural Networks, vol. 6, pp. 343-347, 2000.
21. Guerrero, F., Lozano, S., Smith, K. and Eguia, I., "Facility Location using Neural Networks", in Y. Suzuki, S. Ovaska, T. Furuhashi, R. Roy, and Y. Dote (eds.), Soft Computing in Industrial Applications, Springer-Verlag, London, pp.171-179, 2000.
20. Kwok, T. and Smith, K. A., "A Performance Comparison of Chaotic Simulated Annealing Models for Solving the N-Queen Problem", in Y. Suzuki, S. Ovaska, T. Furuhashi, R. Roy, and Y. Dote (eds.), Soft Computing in Industrial Applications, Springer-Verlag, London, pp.447-458, 2000.
19. Bedingfield, S. and Smith, K. A., "Evolutionary Rule Generation in an Information System", in C. Dagli et al. (Eds.), Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Data Mining, and Complex Systems, ASME Press, vol. 9, pp. 485-492, 1999 - Nominated, Best Applications Paper at Conference.
18. Smith, K. A., Siew, E. G., Milne, B. and Luxford, K., "Neural networks for software metrics estimation", in C. Dagli et al. (Eds.), Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Data Mining, and Complex Systems, ASME Press, vol. 9, pp. 1073-1078, 1999.
17. Smith, K. A., Abramson, D. and Duke, D., "Efficient Timetabling Formulations for Hopfield Neural Networks", in C. Dagli et al. (Eds.), Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Data Mining, and Complex Systems, ASME Press, vol. 9, pp. 1027-1032, 1999.
16. Guerrero, F., Lozano, S., Smith, K. and Kwok, T., "Manufacturing cell formation using a new self-organizing neural network", International Conference on Computers and Industrial Engineering, vol. 1, pp. 668-672, 1999.
15. Smith, K. A., "A data-driven rule-based neural network model for classification", Proceedings 6th International Conference on Neural Information Processing, IEEE Press, vol. 3, pp. 855-860, 1999.
14. Kwok, T. and Smith, K., "Optimisation by chaotic simulated annealing: a comparative study", Proceedings International Workshop on Soft Computing in Industry, pp. 275-280, 1999.
13. Guerrero, F., Smith, K. and Lozano, S., "Self-organising neural approach for solving the quadratic assignment problem", Proceedings International Workshop on Soft Computing in Industry, pp. 13-18, 1999.
12. Lozano, S., Guerrero, F., Eguia, I. and Smith, K., "Cell Formation using Two Neural Networks in Series", in C. Dagli et al. (Eds.), Intelligent Engineering Systems Through Artificial Neural Networks: Neural Networks, Fuzzy Logic, Evolutionary Programming, Data Mining, and Rough Sets, ASME Press, vol. 8, pp. 341-346, 1998.
11. Smith, K. and Gupta, J., "Integrating Feedforward and Feedback Neural Networks for Optimisation", in C. Dagli et al. (Eds.), Intelligent Engineering Systems Through Artificial Neural Networks: Neural Networks, Fuzzy Logic, Evolutionary Programming, Data Mining, and Rough Sets, ASME Press, vol. 8, pp. 69-74, 1998. - Nominated, Best Theoretical Paper Award at Conference.
10. Kwok, T., Smith, K. and Wang, L., "Solving combinatorial optimization problems by chaotic neural networks", in C. Dagli et al. (Eds.), Intelligent Engineering Systems Through Artificial Neural Networks: Neural Networks, Fuzzy Logic, Evolutionary Programming, Data Mining, and Rough Sets, ASME Press, vol. 8, pp. 317-322, 1998.
9. Abramson, D., Smith, K., Logethetis, P. and Duke, D., "FPGA Based Implementation of a Hopfield Neural Network for Solving Constraint Satisfaction Problems", Proceedings EuroMicro Workshop on Computational Intelligence, pp. 688-693, 1998.
8. Guerrero, F., Lozano, S., Canca, D. and Smith, K., "Machine Grouping in Cellular Manufacturing: A Self-Organizing Neural Network", in A. B. Bulsari et al (eds.) Engineering Benefits from Neural Networks: Proceedings of the 4th International Conference on Engineering Applications of Neural Networks, Systems Engineering Association, Turku, Finland, pp. 374-377, 1998.
7. Smith, K., Kim, B. and Sargent, G., "Minimising Channel Interference in Real Cellular Radio Networks", IEEE Global Communications Conference, vol. 4, pp. 2192-2197, 1998.
6. Smith, K., “A genetic algorithm for the Channel Assignment Problem”, IEEE Global Communications Conference, vol. 4, pp. 2013-2017, 1998.
5. Kwok, T., Smith, K. and Wang, L., “Incorporating Chaos into Hopfield Neural Networks for Combinatorial Optimisation”, in N. Callaos, O. Omolayole and L. Wang (eds.), Proceedings World Multiconference on Systemics, Cybernetics and Informatics, vol.1, pp.659-665, 1998.
4. Wang, L. and Smith, K., “Chaos in the Discretized Analog Hopfield Neural Network and Potential Applications to Optimization”, IEEE International Conference on Neural Networks, pp. 1679-1684, 1998.
3. Smith, K. "Optimal Airport Hub Location Using Neural Networks", in C. Dagli et al. (eds.), Intelligent Engineering Systems Through Artificial Neural Networks: Neural Networks, Fuzzy Logic, Data Mining and Evolutionary Programming, volume 7, ASME Press, pp. 911-916, 1997.
2. Smith, K. and Palaniswami, M., "An Improved Hopfield Network Approach to Channel Assignment in a Cellular Mobile Communications Network", in C. Dagli et al. (eds.), Intelligent Engineering Systems Through Artificial Neural Networks: Neural Networks, Fuzzy Logic and Evolutionary Programming, volume 6, ASME Press, pp. 977-982, 1996.
1. Smith, K., "Solving the Generalised Quadratic Assignment Problem using a Self-Organising Process", Proceedings of the IEEE International Conference on Neural Networks (ICNN), vol. 4, pp. 1876-1879, 1995. Best Paper Award at Conference