| 基于混沌遗传算法的SVM特征和参数优化 |
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| 引用本文： | 杜占龙,谭业双,甘彤. 基于混沌遗传算法的SVM特征和参数优化[J]. 计算机工程, 2012, 38(5): 163-166 |
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| 作者姓名： | 杜占龙 谭业双 甘彤 |
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| 作者单位： | 1. 军械工程学院,石家庄,050003
2. 中国科学院研究生院国家天文台,北京,100000 |
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| 摘 要： | 为解决支持向量机(SVM)分类器的样本特征选择和参数优化问题，提出一种将特征选择和参数选择进行联合优化的方法。基于变尺度的混沌遗传算法，联合优化染色体编、译码，利用混沌的遍历性产生初始种群，改进遗传算法中的交叉算子，动态缩减寻优区间。将该方法应用于短波通信控制器的诊断分类器中，以实现分类器特征子集选取和参数的联合优化，结果表明该方法具有较强的寻优能力。
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| 关 键 词： | 支持向量机 混沌遗传算法 特征选取 参数优化 故障诊断 变尺度 |
| 收稿时间： | 2011-08-11 |
SVM Feature and Parameter Optimization Based on Chaotic Genetic Algorithm |
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| DU Zhan-long , TAN Ye-shuang , GAN Tong. SVM Feature and Parameter Optimization Based on Chaotic Genetic Algorithm[J]. Computer Engineering, 2012, 38(5): 163-166 |
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| Authors: | DU Zhan-long TAN Ye-shuang GAN Tong |
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| Affiliation: | 1.Department of Optics and Electronic Engineering,Ordnance Engineering College,Shijiazhuang 050003,China;2.National Astronomical Observatory,Graduate University of Chinese Academy of Sciences,Beijing 100000,China) |
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| Abstract: | Aiming at feature selection and parameter optimization problem of classifier based on Support Vector Machine(SVM),one kind of combination optimization for feature selection and parameter is presented based on chaotic genetic algorithm of mutative scale.The method of chromosome coding and decoding is presented.Initialization population is produced by using chaos ergodicity.A modified crossover operator and dynamic reducing searching space is used for further optimization.This method is applied to fault classifier combination optimization of shortwave-control-equipment.Experimental results assess effectiveness on finding optimal solution of the proposed approach. |
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| Keywords: | Support Vector Machine(SVM) chaotic genetic algorithm feature selection parameter optimization fault diagnosis mutative scale |
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