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Volume 19 Issue 2
Mar.  1997
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Mu Wenquan, Liao Xiaofeng, Yu Juebang. A HYBRID NEURAL NETWORK TRAINING ALGORITHM BASED ON GENETIC ALGORITHM AND BP ALGORITHM[J]. Journal of Electronics & Information Technology, 1997, 19(2): 190-194.
Citation: Mu Wenquan, Liao Xiaofeng, Yu Juebang. A HYBRID NEURAL NETWORK TRAINING ALGORITHM BASED ON GENETIC ALGORITHM AND BP ALGORITHM[J]. Journal of Electronics & Information Technology, 1997, 19(2): 190-194.

A HYBRID NEURAL NETWORK TRAINING ALGORITHM BASED ON GENETIC ALGORITHM AND BP ALGORITHM

  • Received Date: 1995-07-18
  • Rev Recd Date: 1996-01-04
  • Publish Date: 1997-03-19
  • Neural network BP training algorithm based on gradient descend technique may lead to entrapment in local optimum so that the network inaccurately classifies input patterns. This paper presents a hybrid training algorithm GA-QP combined to genetic algorithm with BP algorithm. Experiments show that the hybrid algorithm outperforms BP algorithm. Satisfactory experimental results are obtained.
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  • Rumelhare D, McCelland J. Parallel distributer processing: Exploration in the microstructure of cognition. Cambridge: MIT Press, 198fi, 423-443, 472-486.[2]Madysstha R, et al. An algorithm for training multilayer perceptrons for data classification and[3]function interpolation. IEEE Trans. on CAS, 1994, CAS-41(12): 866-875.[4]Szu H. Non convex optimization. Proc. SPIE. San Diego: 1986, Real Time Signal Processing IX 698, 59-65.[5]Fahlman S E. test-learning variation on back-propagation: An empirical study. Proceedings of 1958[6]Cflnnectionist Models Summer School. San Msteo, CA: 1988, Morgan Kaufmann Publishers, 38-51.[7]Yaon B, et al. Efficient genetic algorithms for training layered feadforward neural network[J].Information Science.1994, 76(1):67-85[8]Kitano H. Empirical studies on the speed of convergence of neural network training using genetic algorithms. Proc. AAAI-90, 1990, MIT press, 789-795.[9]Goldberg D. Genetic Algorithms in Search, Optimization and Machine Learning. 13.eading: Addison Weaey Publishing Company, 19$9, Chapter 1-3.[10]DeJong K A. Genetic algorithms: A 10 year perspective. Proceedings of an International Conference[11]on Genetic Algorithms and Their Applications. Pittsburgh: 1985, Lawrence Erlbaum Associates Publishers, 169-177.[12]Bac F Q, Perov V L. Optimization problems[J].Biological Cybernetics.1993, 69(3):229-234[13]Anbati B, et al. Heuristic combinatorial optimisation by simulated Darwinian evoltion: a polynomial time algorithms for traveling salesman problem, Biological cybernetica, 1991, 85(1): 31-35.
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