基于反馈策略的引力搜索算法及其在支持向量机中应用

doi:10.3724/SP.J.1087.2013.00806

计算机应用 ›› 2013, Vol. 33 ›› Issue (03): 806-809.DOI: 10.3724/SP.J.1087.2013.00806

基于反馈策略的引力搜索算法及其在支持向量机中应用

顾斌杰^*,潘丰

轻工过程先进控制教育部重点实验室(江南大学),江苏无锡 214122

收稿日期:2012-09-26 修回日期:2012-11-01 出版日期:2013-03-01 发布日期:2013-03-01
通讯作者: 顾斌杰
作者简介:顾斌杰(1980-),男,江苏宜兴人,讲师,博士研究生,主要研究方向:工业过程建模及优化控制、信号处理; 潘丰(1963-),男,江苏苏州人,教授,博士生导师,主要研究方向:工业过程建模及优化控制。
基金资助:
国家自然科学基金资助项目(61273131); 江苏高校优势学科建设工程资助项目。

Gravitational search algorithm based on feedback mechanism and its application in SVM

GU Binjie^*, PAN Feng

Key Laboratory of Advanced Process Control for Light Industry of Ministry of Education (Jiangnan University), Wuxi Jiangsu 214122, China

Received:2012-09-26 Revised:2012-11-01 Online:2013-03-01 Published:2013-03-01
Contact: Bin-Jie GU
Supported by:
Bioprocess Modeling and Optimization Based on On-line Support Vector Machines

摘要/Abstract

摘要： 针对标准引力搜索算法(SGSA)在高维多峰函数寻优过程中容易出现早熟的问题,提出一种基于反馈策略的引力搜索算法(FGSA)。由于粒子在进化过程中群体多样性损失过快,采用粒子与最佳位置的距离和最邻近粒子的距离两个参数来均衡优化算法的勘探和开发能力,并将变异操作引入到FGSA中。通过对选取的四个基准函数测试,验证了FGSA和SGSA相比,在高维多峰函数寻优时,精确度和稳定性都有显著提高。同时,针对支持向量机(SVM)分类问题时,可有效地找出合适的特征子集及SVM参数,并取得较好的分类结果。

关键词: 引力搜索算法, 反馈策略, 变异操作, 多峰函数优化, 支持向量机

Abstract: To overcome premature problem of high-dimensional multimodal function in the optimization process by Standard Gravitational Search Algorithm (SGSA), a new Gravitational Search Algorithm based on Feedback mechanism (FGSA) was proposed. Considering the large loss in population diversity during the evolution process, the distance to the optimum position and the distance to its nearest neighbor were introduced into the proposed algorithm to balance the trade-off between exploration and exploitation ability. Mutation operation was also embedded into FGSA. The test results of four benchmark functions demonstrate that FGSA has much better stability and accuracy than SGSA in finding global optimum. Furthermore, when FGSA is applied to Support Vector Machine (SVM) classification, suitable feature subsets and SVM parameters can be effectively found out, and better classification results will be obtained.

Key words: Gravitational Search Algorithm (GSA), feedback mechanism, mutation operation, multimodal function optimization, Support Vector Machine (SVM)

中图分类号:

TP301.6

顾斌杰潘丰. 基于反馈策略的引力搜索算法及其在支持向量机中应用[J]. 计算机应用, 2013, 33(03): 806-809.

GU Binjie PAN Feng. Gravitational search algorithm based on feedback mechanism and its application in SVM[J]. Journal of Computer Applications, 2013, 33(03): 806-809.

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基于反馈策略的引力搜索算法及其在支持向量机中应用

Gravitational search algorithm based on feedback mechanism and its application in SVM

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