青岛大学学报（自然科学版）2017，Vol.30Issue(3)：51-54,4.DOI:10.3969/j.issn.1006-1037.2017.08.11
基于粒子群优化和邻域粗糙集的快速约简算法
Quick Attribute Reduct Algorithm Based on Particle Swarm Optimization and Neighborhood Rough Set
王蓉 1刘遵仁 1高阳1
作者信息
- 1. 青岛大学数据科学与软件工程学院,青岛266071
- 折叠
摘要
Abstract
A simplified particle swarm optimization (PSO) algorithm is proposed to solve the neighborhood decision table (SPSO),which is based on the standard particle swarm optimization (PSO),which is prone to premature convergence,slow search speed and long search time.In the algorithm,the particle swarm simplification structure is adopted to eliminate the velocity terrn,and the current optimal value of the origi nal individual is replaced by the average value of the current optimal value of all the particles,so as to improve the global searching ability of the particle.The experimental results show that the algorithm proposed in this paper is effective and feasible for improving the performance of UCI standard data sets.关键词
粗糙集/邻域/粒子群优化算法Key words
rough set/neighborhood sets/particle swarm optimization分类
信息技术与安全科学引用本文复制引用
王蓉,刘遵仁,高阳..基于粒子群优化和邻域粗糙集的快速约简算法[J].青岛大学学报（自然科学版）,2017,30(3):51-54,4.
