Presentation 2008-02-01
Hopfield NN Using Scaling Law for Quadratic Assignment Problem
Yoshifumi TADA, Yoko UWATE, Yoshifumi NISHIO,
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Abstract(in English) If the scale of the combinatrial optimization problem becomes large, the problem can not be solved by method of searching all solutions. Hopfield Neural Network is one of the important tool of solving combinatorial optimization problem. However, the network finds a local minimum, and can not escape from there. Many researchers proposed the method adding some kinds of noises to the Hopfield Neural Network. In this study, we propose the injecting scaling law noise to Hopfield Neural Network for improvement of the ability. We investigate effective search with Hopfield Neural Network using scaling law for quadratic assignment problem.
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Keyword(in English) Hopfield NN / Chaos noise / QAP / Scaling law
Paper # NLP2007-148
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Conference Information
Committee NLP
Conference Date 2008/1/25(1days)
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Paper Information
Registration To Nonlinear Problems (NLP)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Hopfield NN Using Scaling Law for Quadratic Assignment Problem
Sub Title (in English)
Keyword(1) Hopfield NN
Keyword(2) Chaos noise
Keyword(3) QAP
Keyword(4) Scaling law
1st Author's Name Yoshifumi TADA
1st Author's Affiliation Faculty of Engineering, Tokushima University()
2nd Author's Name Yoko UWATE
2nd Author's Affiliation Faculty of Engineering, Tokushima University
3rd Author's Name Yoshifumi NISHIO
3rd Author's Affiliation Faculty of Engineering, Tokushima University
Date 2008-02-01
Paper # NLP2007-148
Volume (vol) vol.107
Number (no) 478
Page pp.pp.-
#Pages 4
Date of Issue