JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2018, Vol. 48 ›› Issue (3): 81-87.doi: 10.6040/j.issn.1672-3961.0.2017.412

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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

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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.

Key words: Choquet fuzzy integral, ant colony algorithm, cancer classification, fuzzy measures, genetic algorithm

CLC Number: 

  • TP399
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