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Selection of initial weights and thresholds based on the Genetic Algorithm with the optimized Back-Propagation neural network

机译:基于遗传算法和优化反向传播神经网络的初始权重和阈值选择

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The Genetic Algorithm (GA) has been used for artificial neural network optimization of initial weights and thresholds matrix. The initial weights and thresholds which has been optimized is equivalent to set up a reference range for artificial neural network to search optimization, therefore the performance of improved artificial neural network could be enhanced. Matlab2010 has been used as a platform for experiments. With the actual case, the error between the algorithm of individual using the BP (Back-Propagation) network and the optimized GA-BP (Genetic Algorithm and Back-Propagation) neural network with the genetic algorithm has been carefully analyzed. Results show that all indicators improved for the latter.
机译:遗传算法(GA)已用于初始权重和阈值矩阵的人工神经网络优化。优化后的初始权重和阈值相当于为人工神经网络建立搜索优化的参考范围,因此可以提高改进后的人工神经网络的性能。 Matlab2010已用作实验平台。结合实际情况,已经仔细分析了使用BP(反向传播)网络的个体算法与使用遗传算法优化的GA-BP(遗传算法和反向传播)神经网络之间的误差。结果表明,后者的所有指标均得到改善。

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