计算机工程与应用2018，Vol.54Issue(10)：99-104,6.DOI:10.3778/j.issn.1002-8331.1704-0404
采用云量子PSO的属性约简方法
Attribute reduction method using cloud quantum-behaved PSO
摘要
Abstract
In the processing information system,the particle swarm optimization algorithm is applied for the minimum attribute reduction,which is slow and easy to fall into local optimum.Accordingly,this paper proposes a quantum-behaved particle swarm optimization algorithm combined with cloud model(CQPSO)to reduce the number of attributes in data set.First,the speed of convergence is accelerated by using a quantum behavior of QPSO algorithm;and the cloud model is introduced into QPSO to control different particle swarms in different states;then,the attribute reduction mathematical model is constructed according to property dependency and other properties; finally, the CQPSO algorithm is used to solve the problem and achieve the reduction results.In this experiment,the CQPSO algorithm is simulated and compared by the standard test function, which shows that the CQPSO algorithm performance is better than the quantum-behaved PSO algorithm.And the UCI standard database is used to perform attribute reduction tests.The results show that the pro-posed attribute reduction method is superior to the existing reduction method,and its calculation speed is fast and the rec-ognition precision is high.关键词
属性约简/粒子群优化算法/量子行为/云模型Key words
attribute reduction/particle swarm optimization algorithm/quantum behavior/cloud model分类
信息技术与安全科学引用本文复制引用
常红伟,夏克文,白建川,牛文佳,武盼盼..采用云量子PSO的属性约简方法[J].计算机工程与应用,2018,54(10):99-104,6.基金项目
河北省自然科学基金(No.E2016202341) （No.E2016202341）
河北省高等学校科学技术研究项目(No.BJ2014013). （No.BJ2014013）
