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[230] J Eggers, D Feillet, S Kehl, MO Wagner, and B Yannou Optimization of the Keyboard Arrangement Problem using an Ant Colony Algorithm European Journal of Operational Research, 148(3):672 686, 2003 [231] A E Eiben and C A Schippers On Evolutionary Exploration and Exploitation Fundamenta Informaticae, 35(1-4):35 50, 1998 [232] AE Eiben, P-E Rau , and Z Ruttkay Genetic Algorithms with Multi-parent e Recombination In Y Davidor, H-P Schwefel, and R M nner, editors, Proa ceedings of the Parallel Problem Solving from Nature Conference, pages 78 87, Berlin, 1994 Springer [233] AE Eiben, CHM van Kemenade, and JN Kok Orgy in the Computer: Multi-Parent Reproduction in Genetic Algorithms Technical Report CS-R9548, Centrum voor Wiskunde en Informatica, 1995 [234] AI El-Gallad, ME El-Hawary, AA Sallam, and A Kalas Enhancing the Particle Swarm Optimizer via Proper Parameters Selection In Proceedings of the Canadian Conference on Electrical and Computer Engineering, pages 792 797, 2002 [235] MY El-Sharkh and AA El-Keib Maintenance Scheduling of Generation and Transmission Systems using Fuzzy Evolutionary Programming IEEE Transactions on Power Systems, 18(2):862 866, 2003 [236] JL Elman Distributed Representations, Simple Recurrent Networks, and Grammatical Structure Machine Learning, 7(2/3):195 226, 1991 [237] AP Engelbrecht Data Generation using Sensitivity Analysis In Proceedings of the International Symposium on Computational Intelligence, 2000 [238] AP Engelbrecht A New Pruning Heuristic Based on Variance Analysis of Sensitivity Information IEEE Transactions on Neural Networks, 12(6), 2001 [239] AP Engelbrecht Sensitivity Analysis for Selective Learning by Feedforward Neural Networks Fundamenta Informaticae, 45(1):295 328, 2001 [240] AP Engelbrecht and I Cloete A Sensitivity Analysis Algorithm for Pruning Feedforward Neural Networks In Proceedings of the IEEE International Conference in Neural Networks, volume 2, pages 1274 1277, 1996 [241] AP Engelbrecht and I Cloete Feature Extraction from Feedforward Neural Networks using Sensitivity Analysis In Proceedings of the International Conference on Systems, Signals, Control, Computers, volume 2, pages 221 225, 1998 [242] AP Engelbrecht and I Cloete Selective Learning using Sensitivity Analysis In IEEE World Congress on Computational Intelligence, Proceedings of the International Joint Conference on Neural Networks, pages 1150 1155, 1998 [243] AP Engelbrecht and I Cloete Incremental Learning using Sensitivity Analysis In Proceedings of the IEEE International Joint Conference on Neural Networks, volume 2, pages 1350 1355, 1999 [244] AP Engelbrecht, I Cloete, J Geldenhuys, and JM Zurada Automatic Scaling using Gamma Learning for Feedforward Neural Networks In J Mira and F Sandoval, editors, Proceedings of the International Workshop on Artificial Neural Networks, Lecture Notes in Computer Science, volume 930, pages 374 381, 1995
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[245] AP Engelbrecht, I Cloete, and JM Zurada Determining the Signi cance of Input Parameters using Sensitivity Analysis In J Mira and F Sandoval, editors, International Workshop on Artificial Neural Networks, Lecture Notes in Computer Science, volume 930, pages 382 388, 1995 [246] AP Engelbrecht, L Fletcher, and I Cloete Variance Analysis of Sensitivity Information for Pruning Feedforward Neural Networks In Proceedings of the IEEE International Joint Conference on Neural Networks, 1999 [247] AP Engelbrecht and A Ismail Training Product Unit Neural Networks Stability and Control: Theory and Applications, 2(1-2):59 74, 1999 [248] AP Engelbrecht, S Rouwhorst, and L Schoeman A Building Block Approach to Genetic Programming for Rule Discovery In HA Abbass, RA Sarker, and CS Newton, editors, Data Mining: A Heuristic Approach, pages 174 189 Idea Group Publishing, 2002 [249] TM English Learning to Focus Selectively on Possible Lines of Play in Checkers In Proceedings of the IEEE Congress on Evolutionary Computation, volume 2, pages 1019 1024, 2001 [250] LJ Eshelman, RA Caruana, and JD Scha er Biases in the Crossover Landscape In JD Scha er, editor, Proceedings of the Third International Conference on Genetic Algorithms, pages 10 19, 1989 [251] LJ Eshelman and JD Scha er Real-Coded Genetic Algorithms and Interval Schemata In D Whitley, editor, Foundations of Genetic Algorithms, volume 2, pages 187 202, San Mateo, 1993 Morgan Kaufmann [252] S Fahlman and C Lebiere The Cascade-Correlation Learning Architecture Technical Report CMU-CS-90-100, Carnegie Mellon University, 1990 [253] SE Fahlman Fast Learning Variations on Back-Propagation: An Empirical Study In DS Touretzky, GE Hinton, and TJ Sejnowski, editors, Proceedings of the 1988 Connectionist Summer School, pages 38 51 Morgan Kaufmann, 1988 [254] H-Y Fan A Modi cation to Particle Swarm Optimization Algorithm Engineering Computations, 19(7-8):970 989, 2002 [255] J Farmer, N Packard, and A Perelson The Immune System, Adaptation and Machine Learning Physica D, 22:187 204, 1986 [256] M Fathi-Torbaghan and L Hildebrand Model-Free Optimization of Fuzzy Rulebased System using Evolution Strategies IEEE Transactions on Systems, Man, and Cybernetics, 27(2):270 277, 1997 [257] J Favilla, A Machion, and F Gomide Fuzzy Tra c Control: Adaptive Strategies In Proceedings of the IEEE Symposium on Fuzzy Systems, 1993 [258] V Feoktistov and S Janaqi Generalization of The Strategies in Di erential Evolution In Proceedings of the Eighteenth Parallel and Distributed Processing Symposium, page 165, 2004 [259] JE Fieldsend and S Singh A Multi-Objective Algorithm Based upon Particle Swarm Optimisation In Proceedings of the UK Workshop on Computational Intelligence, pages 37 44, 2003 [260] W Finno , F Hergert, and HG Zimmermann Improving Model Selection by Nonconvergent Methods Neural Networks, 6:771 783, 1993
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