BP Network Optimization Based on Improved Genetic Algorithm

机译：基于改进遗传算法的BP网络优化

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In view of the virtue and shortage of genetic algorithm and BP network, this paper proposes a new BP network training method based on improved genetic algorithm (IGA-BP). This algorithm uses hierarchical code, adaptive crossover and mutation, pruning similar chromosomes, dynamic supply new chromosomes and other operations, so the network structure and weight are optimized at the same time and the "premature" phenomenon is avoided. The simulation results show that the IGA-BP network architecture is simple, the convergence rate is quick, and has good approximation and generalization ability.

机译：鉴于遗传算法和BP网络的缺点，本文提出了一种基于改进遗传算法（IGA-BP）的新型BP网络训练方法。该算法使用分层代码，自适应交叉和突变，修剪类似的染色体，动态供应新的染色体和其他操作，因此网络结构和重量同时优化，避免了“早期”现象。仿真结果表明，IGA-BP网络架构简单，收敛速度快，具有良好的近似和泛化能力。

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《MSIT 2012》|2012年||共7页
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作者
Weiwei Sun; Yunfei Yao; Chunsheng Wang; Yegang Hu;
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中图分类 628.1/6837;
关键词
Adaptive; BP Network; Genetic Algorithm (GA); Hierarchical Code; Pruning;

机译：自适应;BP网络;遗传算法（GA）;分层代码;修剪;

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BP Network Optimization Based on Improved Genetic Algorithm

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