Lambda-gamma learning with feedforward neural networks using particle swarm optimization
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[1] R. W. Dobbins,et al. Computational intelligence PC tools , 1996 .
[2] Etienne Barnard,et al. Avoiding false local minima by proper initialization of connections , 1992, IEEE Trans. Neural Networks.
[3] J. Kennedy,et al. Population structure and particle swarm performance , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).
[4] Andries Petrus Engelbrecht,et al. Global optimization algorithms for training product unit neural networks , 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.
[5] James Kennedy,et al. The particle swarm: social adaptation of knowledge , 1997, Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97).
[6] Russell C. Eberhart,et al. A new optimizer using particle swarm theory , 1995, MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science.
[7] John Fulcher,et al. Computational Intelligence: An Introduction , 2008, Computational Intelligence: A Compendium.
[8] Yuval Davidor,et al. Epistasis Variance: A Viewpoint on GA-Hardness , 1990, FOGA.
[9] Frans van den Bergh,et al. An analysis of particle swarm optimizers , 2002 .
[10] Paulo Cortez,et al. Particle swarms for feedforward neural network training , 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).
[11] R. Eberhart,et al. Comparing inertia weights and constriction factors in particle swarm optimization , 2000, Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512).
[12] Andries Petrus Engelbrecht,et al. Overfitting by PSO trained feedforward neural networks , 2010, IEEE Congress on Evolutionary Computation.
[13] R. Salomon. Re-evaluating genetic algorithm performance under coordinate rotation of benchmark functions. A survey of some theoretical and practical aspects of genetic algorithms. , 1996, Bio Systems.
[14] John C. Platt. A Resource-Allocating Network for Function Interpolation , 1991, Neural Computation.
[15] Jacek M. Zurada. Lambda learning rule for feedforward neural networks , 1993, IEEE International Conference on Neural Networks.
[16] Andries Petrus Engelbrecht,et al. Automatic Scaling using Gamma Learning for Feedforward Neural Networks , 1995, IWANN.
[17] Michael Y. Hu,et al. Effect of data standardization on neural network training , 1996 .
[18] Andries Petrus Engelbrecht,et al. Comparing PSO structures to learn the game of checkers from zero knowledge , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..
[19] Nelis Franken,et al. Visual exploration of algorithm parameter space , 2009, 2009 IEEE Congress on Evolutionary Computation.
[20] Yue Shi,et al. A modified particle swarm optimizer , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).
[21] Klaus-Robert Müller,et al. Efficient BackProp , 2012, Neural Networks: Tricks of the Trade.