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《电子科学学刊》 1997-02
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A HYBRID NEURAL NETWORK TRAINING ALGORITHM BASED ON GENETIC ALGORITHM AND BP ALGORITHM

Mu Wenquan Liao Xiaofeng Yu Juebang ( University of Electronic Science and Technology of China, Chengdu 610054)  
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.
【Fund】: 国家教委博士点专项基金9361403号;; 中科院自动化所国家模式识别重点实验室基金
【CateGory Index】: TP18
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