Radial basis function network based on time variant multi-objective particle swarm optimization for medical diseases diagnosis

Applied Soft Computing - Tập 11 - Trang 1427-1438 - 2011
Sultan Noman Qasem1, Siti Mariyam Shamsuddin1
1Soft Computing Research Group, Faculty of Computer Science and Information System, Universiti Teknologi Malaysia, Skudai, 81310 Johor, Malaysia

Tài liệu tham khảo

Broomhead, 1988, Multivariable functional interpolation and adaptive networks, Complex Systems, 2, 321 Leonard, 1991, Radial basis function networks for classifying process faults, Control Systems Magazine, 11, 31, 10.1109/37.75576 Yao, 1999, Evolving artificial neural networks, Proceedings IEEE, 87, 1423, 10.1109/5.784219 Fieldsend, 2005, Pareto evolutionary neural networks, IEEE Transaction Neural Networks, 16, 338, 10.1109/TNN.2004.841794 Coello Coello, 2000, An updated survey of GA-based multi-objective optimization techniques, ACM Computing Surveys, 32, 109, 10.1145/358923.358929 Ceollo Coello, 2002 Garcia-Perdrajas, 2001, Introducing multi-objective optimization in cooperative coevolution of neural networks, 645 Garcia-Perdrajas, 2002, Multi-objective cooperative coevolution of artificial neural networks, Neural Networks, 15, 1259, 10.1016/S0893-6080(02)00095-3 Liu, 1999, Multi-objective criteria for neural networks structure selection and identification of nonlinear systems using genetic algorithms, Proceedings Institute of Electrical Engineering: Control Theory and Applications, 146, 373, 10.1049/ip-cta:19990501 de Lacerda, 2000, Evolutionary optimization of RBF networks, 219 Gonzalez, 2003, Multi-objective evolutionary optimization of the size, shape, and position parameters of radial basis function networks for function approximation, IEEE Transactions on Neural Network, 14, 1478, 10.1109/TNN.2003.820657 Abbass, 2001, Simultaneous evolution of architectures and connection weights in ANNs, 16 Abbass, 2001, A memetic pareto evolutionary approach to artificial neural networks, 1 Abbass, 2002, An evolutionary artificial neural networks approach for breast cancer diagnosis, Artificial Intelligence in Medicine, 25, 265, 10.1016/S0933-3657(02)00028-3 Abbass, 2003, Speed up backpropagation using multi-objective evolutionary algorithms, Neural Computation, 15, 2705, 10.1162/089976603322385126 Abbass, 2003, Pareto neuro-evolution: constructing ensemble of neural networks using multi-objective optimization, 2074 Jin, 2004, Neural network regularization and ensembling using multi-objective evolutionary algorithms, 1 Jin, 2006, Alleviating catastrophic forgetting via multi-objective learning, 3335 Graning, 2006, Generalization improvement in multi-objective learning, 4839 Jin, 2005, vol. 3410 Kokshenev, 2008, A multi-objective approach to RBF network learning, Neurocomputing, 71, 203, 10.1016/j.neucom.2007.11.021 Yen, 2006, 16 Kondo, 2006, Pattern classification by evolutionary RBF networks ensemble based on multi-objective optimization, 2919 Lefort, 2006, vol. 3871 Gonzalez, 2001, vol. 2084 Kondo, 2007, Nonlinear dynamic system identification based on multi-objectively selected RBF networks, 112 Ferreira, 2005, Evolutionary multi-objective design of radial basis function networks for greenhouse environmental control Bai, 2002, Genetic algorithm based self-growing training for RBF neural networks, 840 Wenbo, 2002, The structure optimization of radial basis probabilistic neural networks based on genetic algorithms, 1086 Kennedy, 1995, Particle Swarm Optimization, 1942 Shi, 1998, A modified particle swarm optimizer, 69 Coello, 2002, MOPSO: a proposal for multiple objective particle swarm optimization, 1051 Ratnaweera, 2004, Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients, IEEE Transactions on Evolutionary Computation, 8, 240, 10.1109/TEVC.2004.826071 Deb, 2002, Elitist Multi-objective Genetic Algorithm: NSGA-II, IEEE Transactions on Evolutionary Computation, 6, 182, 10.1109/4235.996017 Coello, 2004, Handling multi-objectives with particle swarm optimization, IEEE Transactions on Evolutionary Computation, 8, 256, 10.1109/TEVC.2004.826067 Tripathi, 2007, Multi-Objective Particle Swarm Optimization with time variant inertia and acceleration coefficients, International Journal of Information Sciences, 177, 5033, 10.1016/j.ins.2007.06.018 Raquel, 2005, An effective use of crowding distance in multiobjective particle swarm optimization, 257 Shahin, 2004, Application of Neural Networks in Foundation Engineering Asuncion, 2007 Goh, 2008, Hybrid multiobjective evolutionary design for artificial neural networks, IEEE Transactions on Neural Networks, 19, 1531, 10.1109/TNN.2008.2000444 Jin, 2008, Pareto based approach to machine learning: an overview and case studies, IEEE Transactions on Systems, Man, and Cybernetics, Part C, 38, 397, 10.1109/TSMCC.2008.919172 Mangasarian, 1990, Cancer diagnosis via linear programming, SIAM News, 23, 1