Add to ORKGAbstract — 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. I
Abstract: Multi-modal optimisation problems are characterised by the presence of either local sub-op...
A multiscale method is described in the context of binary Hopfield--type neural networks. The approp...
Abstract This article presents a simulation study for validation of an adaptation methodology for le...
Solving combinatorial optimization problem is one of the im-portant applications of neural network (...
Combinatorial optimization problems can be solved with the Hopfield Neural Network. If we choose con...
Abstract—Solving combinatorial optimization problems is one of the important applications of neural ...
Abstract In our past study, the solving ability of the Hopeld Neural Network with noise for quadrat...
In this paper, performance of chaos and burst noises injected to the Hopfield Neural Network for qua...
Although it would be possible to solve combinatorial op-timization problems with a huge number of el...
In this paper, we investigate the solving ability of Hop-field neural network with iterative simulat...
The Quadratic Assignment Problem (QAP) was introduced by Koopmans and Beckmann in 1957 as a mathemat...
Neural networks can be successfully applied to solving certain types of combinatorial optimization p...
Optimization plays a significant role in almost every field of applied sciences (e.g., signal proces...
Abstract. In the use of Hopfield networks to solve optimization problems, a critical problem is the ...
After more than a decade of research, there now exist several neural-network techniques for solving ...
Abstract: Multi-modal optimisation problems are characterised by the presence of either local sub-op...
A multiscale method is described in the context of binary Hopfield--type neural networks. The approp...
Abstract This article presents a simulation study for validation of an adaptation methodology for le...
Solving combinatorial optimization problem is one of the im-portant applications of neural network (...
Combinatorial optimization problems can be solved with the Hopfield Neural Network. If we choose con...
Abstract—Solving combinatorial optimization problems is one of the important applications of neural ...
Abstract In our past study, the solving ability of the Hopeld Neural Network with noise for quadrat...
In this paper, performance of chaos and burst noises injected to the Hopfield Neural Network for qua...
Although it would be possible to solve combinatorial op-timization problems with a huge number of el...
In this paper, we investigate the solving ability of Hop-field neural network with iterative simulat...
The Quadratic Assignment Problem (QAP) was introduced by Koopmans and Beckmann in 1957 as a mathemat...
Neural networks can be successfully applied to solving certain types of combinatorial optimization p...
Optimization plays a significant role in almost every field of applied sciences (e.g., signal proces...
Abstract. In the use of Hopfield networks to solve optimization problems, a critical problem is the ...
After more than a decade of research, there now exist several neural-network techniques for solving ...
Abstract: Multi-modal optimisation problems are characterised by the presence of either local sub-op...
A multiscale method is described in the context of binary Hopfield--type neural networks. The approp...
Abstract This article presents a simulation study for validation of an adaptation methodology for le...