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 :
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