| 文本特征抽取中基于基因集编码的遗传退火算法 |
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| 引用本文： | 符保龙.文本特征抽取中基于基因集编码的遗传退火算法[J].广西科学院学报,2012,28(1):1-3. |
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| 作者姓名： | 符保龙 |
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| 作者单位： | 柳州职业技术学院 |
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| 基金项目： | 广西教育厅科研项目(NO:200911LX486;201106LX745)资助 |
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| 摘 要： | 采用基因集的形式对传统遗传算法的编码方式进行改进,再引入模拟退火的思想,提出一种基于基因集编码的遗传退火算法的文本特征抽取方法（GSGAA）,并与遗传算法（GA）和模拟退火GA算法（SA-GA）进行比较实验。结果表明,GSGAA算法用于文本分类的特征抽取所得出结果的正确率和执行时间都比采用单基因进行编码的GA算法和GA-SA算法好,具有一定的应用价值。
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| 关 键 词： | 文本分类 特征抽取 基因集 遗传算法 退火算法 |
| 收稿时间： | 2011/4/2 0:00:00 |
| 修稿时间： | 2011/5/13 0:00:00 |
The Application of Genetic Annealing Algorithm Based on Gene-Set in the Feature Selection of Text Classification |
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| FU Bao-long.The Application of Genetic Annealing Algorithm Based on Gene-Set in the Feature Selection of Text Classification[J].Journal of Guangxi Academy of Sciences,2012,28(1):1-3. |
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| Authors: | FU Bao-long |
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| Institution: | FU Bao-long(Liuzhou Vocational Technological College,Liuzhou,Guangxi,545006,China) |
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| Abstract: | By usage of gene-set,the encoding of traditional genetic algorithm is improved.The improved encoding with the introduction of simulated annealing,a feature selection of text classification through the genetic annealing algorithm based on genetic-set(GSGAA) is illustrated.Compared with genetic algorithm(GA) and simulated annealing genetic algorithm(SAGA),the results show that GSGAA can significantly improve the accuracy and shorten the execution time,which indicate the application value of GSGAA. |
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| Keywords: | text classification feature selection gene-set genetic algorithm annealing algorithm |
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