[1]马胜蓝,叶东毅.一种带禁忌搜索的粒子并行子群最小约简算法[J].智能系统学报,2011,6(2):132-140.
MA Shenglan,YE Dongyi.A minimum reduction algorithm based on parallel particle subswarm optimization with tabu search capability[J].CAAI Transactions on Intelligent Systems,2011,6(2):132-140.
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MA Shenglan,YE Dongyi.A minimum reduction algorithm based on parallel particle subswarm optimization with tabu search capability[J].CAAI Transactions on Intelligent Systems,2011,6(2):132-140.
一种带禁忌搜索的粒子并行子群最小约简算法
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
6
期数:
2011年第2期
页码:
132-140
栏目:
学术论文—人工智能基础
出版日期:
2011-04-25
- Title:
- A minimum reduction algorithm based on parallel particle subswarm optimization with tabu search capability
- 文章编号:
- 1673-4785(2011)02-0132-09
- Keywords:
- attribute reduction; rough set; tabu search; particle swarm optimization; parallel particle subswarm
- 分类号:
- TP18
- 文献标志码:
- A
- 摘要:
- 为了提高基于群体智能的粗糙集最小属性约简算法的求解质量和计算效率，提出一个结合长期记忆禁忌搜索方法的粒子群并行子群优化算法.并行的各子群不仅具有禁忌约束，而且包含多样性和增强性策略.由于并行的子群共同陷入局部最优的概率小于一个粒子群陷入局部最优的概率，该算法可提高获得全局最优的可能性，并减少受初始粒子群体的影响.多个UCI数据集的实验计算表明，提出的算法相对于其他的属性约简算法具有更高的概率搜索到最小粗糙集约简.因此所提出的算法用于求解最小属性约简问题是可行和较为有效的.
- Abstract:
- In order to improve the solution quality and computing efficiency of rough set minimum attribute reduction algorithms based on swarm intelligence, a parallel particle subswarm optimization algorithm with longmemory Tabu search capability was proposed. In addition to the taboo restriction, some diversification and intensification schemes were employed. Since parallel subswarms have a lower probability of simultaneously getting trapped in a local optimum than a single particle swarm, the proposed algorithm enhances the probability of finding a global optimum and decreases the influence of initial particles. Experimental results on a number of UCI datasets show that the proposed algorithm has a higher probability of finding a minimum attribute reduction in rough sets compared with some existing swarm intelligence based attribute reduction algorithms. Therefore, the proposed algorithm is feasible and relatively effective for the minimum attribute reduction problem.
- 参考文献/References:
-
［1］SWINIARSKI R W, SKOWRON A. Rough set methods in feature selection and recognition［J］. Pattern Recognition Letters, 2003, 24: 833849.
［2］CHOUCHOULAS A, SHEN Q. Rough setaided keyword reduction for text categorization［J］. Applied Artificial Intelligence, 2001, 15(9): 843873.
［3］SKOWRON A, RAUSZER C. The discernibility matrices and functions in information systems［C］//Dordrech: Kluwer Academic Publishers, 1992: 311362.
［4］HU X. Knowledge discovery in databases: an attributeoriented rough set approach［D］. Regina, Saskatchewan： Canada, Computer Science Faculty of Graduate Studies, University of Regina, 1995: 1152.
［5］WROBLEWSKI, J. Finding minimal reducts using genetic algorithms［C］//Proc of the Second Annual Joint Conference on Information Sciences. Wrightsville Beach, USA, 1995: 186189.
［6］JENSEN R, SHEN Q. Finding rough set reducts with ant colony optimization［C］//Proceedings of the 2003 UK Workshop on Computational Intelligence. Bristol, UK, 2003: 1522.
［7］HEDAR A R, WANG J， FUKUSHIMA M. Tabu search for attribute reduction in rough set theory［J］. Soft Computing, 2008, 12(9): 909918.
［8］叶东毅, 廖建坤.基于二进制粒子群优化的最小属性约简算法［J］.模式识别与人工智能, 2007, 20(3): 295300. YE Dongyi, LIAO Jiankun. Minimum attribute reduction algorithm based on binary particle swarm optimization［J］. Pattern Recognition and Artificial Intelligence, 2007, 20(3): 295300.
［9］叶东毅, 廖建坤.最小约简问题的一个离散免疫粒子群算法［J］. 小型微型计算机系统， 2008， 29（6）: 550555.
YE Dongyi， LIAO Jiankun. Immune discrete particle swarm optimization algorithm for minimum attribute reduction problems［J］. Journal of Chinese Computer Systems, 2008, 29(6): 550555.
?［10］王国胤．Rough集理论与知识获取［M］．西安：西安交通大学出版社， 2001: 23145.
［11］张文修，梁怡，吴伟志．信息系统与知识发现［M］．北京： 科学出版社， 2003: 5668.
?［12］GLOVER F. Tabu searchpart I, ORSA［J］. Journal on Computing 1989, 1(3): 190206.
［13］KENNEDY J, EBERHART R C．Particle swarm optimization［C］//Proc of the IEEE International Conference on Neural Networks．Perth, Australia， 1995: 19421948.
［14］WANG Xiangyang, YANG Jie, PENG Ningsong, et al. Finding minimal rough set reducts with particle swarm optimization［J］. Lecture Notes in Artificial Intelligence, 2005, 3641: 451460.
［15］MENDES R, KENNEDY J, NEVES J. The fully informed particle swarm:simpler, maybe better［J］. IEEE Transactions on Evolutionary Computation, 2004, 7(8): 204210.
［16］DENG Tingquan, YANG Chengdong. An improved ant colony optimization applied to attributes reduction［J］. Fuzzy Information and Engineering, 2009, 54: 16.
［17］MONTGOMERY D C, RUNGER G C.Applied statistics and probability for engineers［M］. 3rd ed. New York，USA：John Wiley & Sons Inc, 2003: 278326.
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备注/Memo
收稿日期：2010-03-07.
基金项目： 国家自然科学基金资助项目（60805042）；福建省自然科学基金资助项目（2010J01329）.
通信作者：叶东毅.
E-mail:yiedy@fzu.edu.cn.
作者简介：
马胜蓝，男，1986年生，硕士研究生，主要研究方向为计算智能.
?叶东毅，男，1964年生，教授，博士生导师，主要研究方向为计算智能、数据挖掘.曾获得国家科技进步二等奖（主要成员1项）、福建省科学技术二等奖1项和福建省科学技术三等奖2项.出版著作和教材6部， 发表学术论文70余篇.
更新日期/Last Update:
2011-05-19