基于进化规划的BP神经网络学习
The Learning of BP Neural Network Based on Evolutionary Programming
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摘要: 通过对将传统的BP算法和遗传算法应用到BP神经网络的学习的研究和分析,指出它们存在的缺陷。 提出一个改进的进化规划算法,并将其应用于BP神经网络的权值优化。取XOR问题和4奇偶性问题的实验对 传统的进化规划算法和改进的进化规划算法进行实验对比。实验结果表明,本文中提出的改进的进化规划算法 优于前2个算法。Abstract: The shortcomings of the traditional methods are point out through the analysis of BP algorithm and genetic algorithm which are commonly applied to BP neural networks. A modified evolutionary programming is proposed to optimize the weight of BP neural network. The simulating results for XOR problem and four-parity problem are given through comparison among BP algorithm, traditional evolutionary algorithm and the proposed modified evolutionary algorithm. The result indicates that the modified evolutionary algorithm proposed in this paper is superior to other two algorithms.
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Key words:
- neural networks /
- algorithms /
- optimization
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