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[138] I Cloete and J Ludik Delta Training Strategies In IEEE World Congress on Computational Intelligence, Proceedings of the International Joint Conference on Neural Networks, volume 1, pages 295 298, 1994 [139] I Cloete and J Ludik Incremental Training Strategies In Proceedings of the International Conference on Artificial Neural Networks, volume 2, pages 743 746, 1994 [140] G Coath and SK Halgamuge A Comparison of Constraint-Handling Methods for The Application of Particle Swarm Optimization to Constrained Nonlinear Optimization Problems In Proceedings of the IEEE Congress on Evolutionary Computation, volume 4, pages 2419 2425, 2003 [141] HG Cobb An Investigation into The Use of Hypermutation as An Adaptive Operator in Genetic Algorithms having Continuous, Time-Dependent Nonstationary Environments Technical Report AIC-90-001, Naval Research Laboratory, Washington, DC, 1990 [142] JP Coelho, PB De Moura Oliveira, and J Boa Ventura Cunha Non-Linear Concentration Control System Design using A New Adaptive PSO In Proceedings of the 5th Portuguese Conference on Automatic Control, 2002 [143] JP Coelho, PM Oliveira, and JB Cunha Greenhouse Air Temperature Control using the Particle Swarm Optimisation Algorithm In Proceedings of the Fifteenth Triennial World Congress of the International Federation of Automatic Control, 2002 [144] CA Coello Coello Self-Adaptive Penalties for GA-Based Optimization In Proceedings of the IEEE Congress on Evolutionary Computation, volume 1, 1999 [145] CA Coello Coello and RL Becerra Constrained Optimization using an Evolutionary Programming-based Cultural Algorithm In IC Parmee, editor, Proceedings of the Fifth International Conference on Adaptive Computing in Design and Manufacture, volume 5, pages 317 328 Springer-Verlag, 2002 [146] CA Coello Coello and RL Becerra Evolutionary Multiobjective Optimization using a Cultural Algorithm In Proceedings of the IEEE Swarm Intelligence Symposium, pages 6 13, 2003 [147] CA Coello Coello and MS Lechuga MOPSO: A Proposal for Multiple Objective Particle Swarm Optimization In Proceedings of the IEEE Congress on Evolutionary Computation, volume 2, pages 1051 1056, 2002 [148] CA Coello Coello, G Toscano Pulido, and M Salazar Lechuga An Extension of Particle Swarm Optimization that can Handle Multiple Objectives In Workshop on Multiple Objective Metaheuristics, 2002 [149] CA Coello Coello, DA van Veldhuizen, and GB Lamont Evolutionary Algorithms for Solving Multi-Objective Problems Plenum US, 2002 [150] CA Coello Coello, DA Van Veldhuizen, and GB Lamont Evolutionary Algorithms for Solving Multi-Objective Problems Kluwer Academic Publishers, 2002 [151] D Cohn, L Atlas, and R Ladner Improving Generalization with Active Learning Machine Learning, 15:201 221, 1994 [152] D Cohn and G Tesauro Can Neural Networks do Better than the VapnikChervonenkis Bounds In R Lippmann, J Moody, and DS Touretzky, editors, Advances in Neural Information Processing Systems, volume 3, pages 911 917, 1991.

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