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基于遺傳算法和BP算法的多層感知機雜交訓練算法

穆文全 廖曉峰 虞厥邦

穆文全, 廖曉峰, 虞厥邦. 基于遺傳算法和BP算法的多層感知機雜交訓練算法[J]. 電子與信息學報, 1997, 19(2): 190-194.
引用本文: 穆文全, 廖曉峰, 虞厥邦. 基于遺傳算法和BP算法的多層感知機雜交訓練算法[J]. 電子與信息學報, 1997, 19(2): 190-194.
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.

基于遺傳算法和BP算法的多層感知機雜交訓練算法

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

  • 摘要: 基于梯度下降的神經網絡訓練算法易于陷入局部最小,從而使網絡不能對輸入模式進行準確分類。本文提出綜合遺傳算法和BP算法的雜交算法GA-QP,它結合遺傳算法的全局搜索特性和BP的局部收斂特性,實現(xiàn)對神經網絡的有效訓練。實驗表明該算法優(yōu)于BP算法,實驗結果令人滿意。
  • 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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出版歷程
  • 收稿日期:  1995-07-18
  • 修回日期:  1996-01-04
  • 刊出日期:  1997-03-19

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