首页> 外文会议>Proceedings of the 2007 International Conference on Machine Learning and Cybernetics >A NEW ALGORITHM BASED ON IMMUNE ALGORITHM AND HOPFIELD NEURAL NETWORK FOR MULTIMODAL FUNCTION OPTIMIZATION
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A NEW ALGORITHM BASED ON IMMUNE ALGORITHM AND HOPFIELD NEURAL NETWORK FOR MULTIMODAL FUNCTION OPTIMIZATION

机译:基于免疫算法和霍菲尔神经网络的多模态函数优化新算法

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This paper analyzes immune theory and Hopfield Neural Network (HNN), and then proposes a new algorithm for multimodal function.This new algorithm uses the advantages of both HNN and immune algorithm, and it appears excellent characteristic in optimal problems of multimodal function.In detail, we obtain a group of solutions with variety by immune algorithm (IA) first; and then the solutions are partitioned into some clusters.Finally we take cluster centroids returned by clustering algorithm as the initial value of each HNN, and run the Hopfield neural networks to obtain all minima.
机译:本文对免疫理论和Hopfield神经网络(HNN)进行了分析,提出了一种新的多峰函数算法,该算法兼具HNN和免疫算法的优点,在多峰函数的最优问题中表现出优异的特性。 ,我们首先通过免疫算法(IA)获得了一组具有多样性的解决方案;最后,将聚类算法返回的聚类质心作为每个HNN的初始值,并运行Hopfield神经网络来获得所有最小值。

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