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作者:

Li, Rong (Li, Rong.) | Qiao, Junfei (Qiao, Junfei.) (学者:乔俊飞) | Li, Wenjing (Li, Wenjing.)

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CPCI-S

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.

关键词:

作者机构:

  • [ 1 ] [Li, Rong]Beijing Univ Technol, Sch Elect Informat & Control Engn, Beijing 100124, Peoples R China
  • [ 2 ] [Qiao, Junfei]Beijing Univ Technol, Sch Elect Informat & Control Engn, Beijing 100124, Peoples R China
  • [ 3 ] [Li, Wenjing]Beijing Univ Technol, Sch Elect Informat & Control Engn, Beijing 100124, Peoples R China
  • [ 4 ] [Li, Rong]Beijing Vocat Coll Agr, Dept Informat Technol, Beijing, Peoples R China

通讯作者信息:

  • [Li, Rong]Beijing Univ Technol, Sch Elect Informat & Control Engn, Beijing 100124, Peoples R China;;[Li, Rong]Beijing Vocat Coll Agr, Dept Informat Technol, Beijing, Peoples R China

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来源 :

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

年份: 2016

页码: 1775-1780

语种: 英文

被引次数:

WoS核心集被引频次: 4

SCOPUS被引频次:

ESI高被引论文在榜: 0 展开所有

万方被引频次:

中文被引频次:

近30日浏览量: 2

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