Solving ability of Hopfield Neural Network with scale-rule noise for QAP
One of the applications of neural network is solving combinatorial optimization problems. In our past study, the solving ability of the Hopfield Neural Network with noise for quadratic assignment problem is investigated. However, even if we injected the noise to the network, the optimal solution can...
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| creator | Tada, Y Uwate, Y Nishio, Y |
| description | One of the applications of neural network is solving combinatorial optimization problems. In our past study, the solving ability of the Hopfield 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 Hopfield Neural Network to achieve better performance. By computer simulations solving quadratic assignment problem, we evaluate the performance of the method. |
| doi_str_mv | 10.1109/ISCAS.2008.4541365 |
| format | Conference Proceeding |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Chaos Computer simulation Hopfield neural networks Logistics Neural networks Neurons Noise level Performance gain Production facilities Stochastic resonance |
| title | Solving ability of Hopfield Neural Network with scale-rule noise for QAP |
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