基于改进遗传算法的BP神经网络及应用
기우개진유전산법적BP신경망락급응용
Back propagation neural network based on modified genetic algorithm and its application
  • 万方数据
    华中师范大学学报(自然科学版) 화중사범대학학보(자연과학판)
    JOURNAL OF CENTRAL CHINA NORMAL UNIVERSITY
    2007年 1期 51-54 ,共4页

    何方国%齐欢

    하방국%제환

    遗传算法%BP神经网络%时间序列%用电预测 遺傳算法%BP神經網絡%時間序列%用電預測
    유전산법%BP신경망락%시간서렬%용전예측
    Genetic algorithm%BP neural network%time series%power consumption prediction
    结合遗传算法及神经网络各自的优点,利用改进遗传算法对BP神经网络的连接权进行优化,并提出了一种新的编码方式.通过与时间序列模型对比,基于改进遗传算法的BP模型效果更好.
    결합유전산법급신경망락각자적우점,이용개진유전산법대BP신경망락적련접권진행우화,병제출료일충신적편마방식.통과여시간서렬모형대비,기우개진유전산법적BP모형효과경호.
    This paper mainly studies the optimization of BP neural network by applying modified genetic algorithm, and proposes a combined GA-ANN algorithms by the merging of modified genetic algorithms (GA) and artificial neural network. (ANN). At the same time, a coding method is presented for genetic algorithms. The experimental result shows that the algorithm can improve network generation ability and accuracy for forecasting.
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