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Computation Method of Processing Time Based on BP Neural Network and Genetic Algorithm

机译:基于BP神经网络和遗传算法的加工时间计算方法。

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Looking-up standard processing time table is a commonly used and important determination method of processing time. However, the large error in nonstandard nodes brings adverse effect on its accuracy. In view of the problem, a computation method of processing time based on back propagation neural network (BPNN) and genetic algorithm (GA) is proposed. Several key technologies of BPNN based on Matlab, including computation of the number of neurons in hidden layer, determination of training algorithm, and affecting factors of generalization ability, are researched in depth. In order to improve the training efficiency of BPNN, GA is used to optimize its connection weights and thresholds. The encoding method, selection operation, crossover, and mutation operation of GA are discussed in detail. The higher computation precision and faster operation speed of the proposed method is demonstrated through application cases.
机译:查找标准处理时间表是处理时间的一种常用且重要的确定方法。但是,非标准节点中的大误差对其精度造成不利影响。针对该问题,提出了一种基于BP神经网络和遗传算法的处理时间计算方法。深入研究了基于Matlab的BPNN关键技术,包括隐层神经元数量的计算,训练算法的确定以及泛化能力的影响因素。为了提高BPNN的训练效率,GA被用来优化其连接权重和阈值。详细讨论了遗传算法的编码方法,选择操作,交叉和变异操作。通过应用实例证明了该方法的更高的计算精度和更快的运算速度。

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