DocumentCode
1828997
Title
Solving ability of Hopfield Neural Network with scale-rule noise for QAP
Author
Tada, Yoshifumi ; Uwate, Yoko ; Nishio, Yoshifumi
Author_Institution
Dept. of Electr. & Electron. Eng., Tokushima Univ., Tokushima
fYear
2008
fDate
18-21 May 2008
Firstpage
105
Lastpage
108
Abstract
One of the applications of neural network is solving combinatorial optimization problems. In our past study, the solving ability of the Hopfleld Neural Network with noise for quadratic assignment problem is investigated. However, even if we injected the noise to the network, the optimal solution cannot occasionally be found. In this study, we propose the method adding scale-rule noise to the Hopfleld Neural Network to achieve better performance. By computer simulations solving quadratic assignment problem, we evaluate the performance of the method.
Keywords
Hopfield neural nets; mathematics computing; optimisation; Hopfield neural network; QAP; quadratic assignment problem; scale-rule noise; Chaos; Computer simulation; Hopfield neural networks; Logistics; Neural networks; Neurons; Noise level; Performance gain; Production facilities; Stochastic resonance;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 2008. ISCAS 2008. IEEE International Symposium on
Conference_Location
Seattle, WA
Print_ISBN
978-1-4244-1683-7
Electronic_ISBN
978-1-4244-1684-4
Type
conf
DOI
10.1109/ISCAS.2008.4541365
Filename
4541365
Link To Document