A New Method for Reliability Optimizations of Complex Systems by Neural Networks and Chaotic Algorithm
The reliability optimization of complex systems is an important part of designing a system to match with performance parameters, it mostly involves combinatorial optimization and is hard to solve exactly. In this paper, a new reliability optimization method using neural networks is presented to identify the choice of components in series-parallel systems with multiple constraints. First of all, the neural networks corresponding to reliability optimizations are designed. Secondly, the optimal solutions of reliability optimization problems are obtained by making the neural networks converge to the stable states. The chaos is used in the method, which enhances the speed of convergence and improves the accuracy of solution. Simulation results show that the method proposed in this paper is a useful alternative for reliability optimizations of complex systems.
Zhongliang Pan Ling Chen Guangzhao Zhang
Department of Electronics, School of Physics and Telecommunication, South China Normal University, G Department of Electronics, School of Information Technology, Sun Yat-sen University, Guangzhou 51027
国际会议
南宁
英文
2007-07-20（万方平台首次上网日期，不代表论文的发表时间）