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基于蚁群算法求解Choquet模糊积分模型

1. 华南农业大学数学与信息学院, 广东 广州 510642
• 收稿日期:2017-05-09 出版日期:2018-06-20 发布日期:2017-05-09
• 通讯作者: 王金凤(1978— ),女,河北黄骅人,副教授,博士,主要研究方向为数据挖掘,机器学习. E-mail:wangphoenix@163.com E-mail:chen_jia_jie@sina.cn
• 作者简介:陈嘉杰(1993— ),男,广东东莞人,硕士研究生,主要研究方向为模糊积分. E-mail:chen_jia_jie@sina.cn
• 基金资助:
国家自然科学基金资助项目(61202295);广东省公益研究与能力建设基金资助项目(2017A040406023);广东省公益研究与能力建设基金资助项目(2015A030401081)

Method for solving Choquet integral model based on ant colony algorithm

CHEN Jiajie, WANG Jinfeng*

1. College of Mathematics and Information, South China Agricultural University, Guangzhou 510642, Guangdong, China
• Received:2017-05-09 Online:2018-06-20 Published:2017-05-09

Abstract: An improved ant colony algorithm for Choquet integral was investigated to enhance the search efficiency of fuzzy measure. Choquet integral model was built according to the characteristic quantity and solved by the process of searching globally or locally according to the state transition probability. It was classified by Fisher discriminates. The experiment used three sets of cancer gene datasets preprocessed by R language Bioconductor toolkit, and classification results was analyzed between new model and the mainstream algorithm. The results showed that in DLBCL dataset and colon dataset, ant colony algorithm had the better effect; in prostate dataset, although the classification results were about the same, ant colony algorithm still had faster convergence than genetic algorithm. The improved ant colony algorithm presented a feasible and effective way to solve fuzzy measures in Choquet integral model.

• TP399
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