A Modified Hopfield Neural Network for Solving TSP Problem

被引：0

作者：

Li, Rong ^{[1
,2
]}

Qiao, Junfei ^{[1
]}

Li, Wenjing ^{[1
]}

机构：

[1] Beijing Univ Technol, Sch Elect Informat & Control Engn, Beijing 100124, Peoples R China

[2] Beijing Vocat Coll Agr, Dept Informat Technol, Beijing, Peoples R China

来源：

PROCEEDINGS OF THE 2016 12TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA) | 2016年

关键词：

OPTIMIZATION PROBLEMS; ALGORITHM;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In view of the problem that Hopfield neural network is easy to fall into local minimum, this paper proposes a modified Hopfield neural network to overcome this problem. By adjusting the connection weights which is governed by the objective function, the energy function decreases until to the global minimum. The modified Hopfield neural network is used for solving TSP problem, and the experimental results show that the network will escape the local minimum. The validity and feasibility of the modified Hopfield neural network is proved.

引用

页码：1775 / 1780

页数：6

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