电子学报Issue(11)：2137-2144,8.DOI:10.3969/j.issn.0372-2112.2015.11.001
基于折射原理反向学习模型的改进粒子群算法
Improved Particle Swarm Optimization Algorithm Based on Opposite Learning of Refraction
摘要
Abstract
One of shortcomings found in the particle swarm optimization algorithm is that it is easy to fall into local opti-mum,and the opposite learning strategy has a good effect on the improvement of this shortcoming.However,to improve the global search ability by using the opposite learning strategy it is necessary that in the late algorithm other strategies are combined to oppo-site learning strategy.To overcome this shortcoming,this paper improves the opposite process of the opposite learning strategy ac-cording to the refraction principle of light,and proposes the unified model of opposite-based learning(UOBL)and the improved par-ticle swarm optimization algorithm based on the opposite learning model of the principle of refraction(refrPSO).Experiment results and analysis show that the model improves the global search ability of the refrPSO algorithm more effectively compared with other particle swarm algorithm based on opposite learning and the diversity of the population.Because of these improvements,the refrPSO enhances the convergence speed and the accuracy of optimization.关键词
智能优化算法/粒子群优化算法/反向学习/折射原理Key words
intelligent optimization/particle swarm optimization/opposite-based learning/refraction principle分类
信息技术与安全科学引用本文复制引用
邵鹏,吴志健,周炫余,邓长寿..基于折射原理反向学习模型的改进粒子群算法[J].电子学报,2015,(11):2137-2144,8.基金项目
国家自然科学基金（No．61070008，No．70971043）；武汉大学软件工程国家重点实验室开放基金项目（No．SKLSE2012-09-19）；中央高校基本科研业务专项项目（No．2012211020205）；江西省教育厅科学技术项目 （）
