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Application of Neural Network based on the Immune Genetic Algorithm in Failure Diagnosis

机译:神经网络在基于免疫遗传算法的故障诊断中的应用

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This paper designs the multilayer feed-forward neural network based on the immune genetic algorithm to solve the problem that BP algorithm is prone to get the local minimum in the failure diagnosis system. It is of both the learning ability and robustness of the neural network, as well as the strong global random searching ability of the immune genetic algorithm. The simulation results indicate the neural network can fulfill failure diagnosis of the complicated production better.
机译:本文基于免疫遗传算法设计多层前馈神经网络,解决了BP算法在故障诊断系统中易于获得局部最小值的问题。它是神经网络的学习能力和鲁棒性,以及免疫遗传算法的强大全球随机搜索能力。仿真结果表明神经网络可以更好地满足复杂生产的故障诊断。

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