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基于遗传算法和BP神经网络的数据融合方案的应用

Application of Data Fusion Based on Genetic Algorithm and BP Neural Network in WSN
作者:Xu YiLi ZhaoxiangLiu Jiaojiao 作者单位:College of computer Science and TechnologyWuhan University of Technology Wuhan,China;College of computer Science and TechnologyWuhan University of Technology Wuhan,China 加工时间:2014-07-18 信息来源:科技报告(Other) 索取原文[5 页]
关键词:数据融合;遗传算法;BP人工神经网络
摘 要:Energy-saving is one of the inevitable problems of the routing design in WSN,while Data Fusion technology is widely utilized in energy constraint WSN to reduce the amount of messages exchanged between sensor nodes.This paper proposes a new algorithm based on Integrated Genetic and BP Neural Network(IGBP),IGBP uses the global search capability of GA to remedy the deficiency of BP artificial neural network.First,IGBP generates the best individuals in different networks by GA algorithm.Then it chooses the most optimize individual measure by Mean Squared Error to construct the BP network which was supplied to train of the WSN.Using the optimize individual nodes as initialization value training the BP network,it will enhance the learning rates of convergence and avoid falling into the local minimums.The simulation results show that the IGBP algorithm has made great progress in balancing the consumption of energy so as to prolong the network lifetime.
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