[1]XIAO Qin,ZHANG Yongwei,WANG Lei.Intelligent optimized Bezier curves based on incremental polar coordinate coding[J].CAAI Transactions on Intelligent Systems,2017,12(6):841-847.[doi:10.11992/tis.201706076]
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Intelligent optimized Bezier curves based on incremental polar coordinate coding

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 12 Number of periods: 2017 6 Page number: 841-847 Column: 学术论文—机器学习 Public date: 2017-12-25
Title:
Intelligent optimized Bezier curves based on incremental polar coordinate coding
Author(s):
XIAO Qin1;  ZHANG Yongwei2;  WANG Lei3
1. Center of Information Construction and Management, Jiangsu University of Science and Technology, Zhenjiang 212003, China;
2. Department of Electronics and Information, Jiangsu University of Science and Technology, Zhenjiang 212003, China;
3. Coll
Keywords:
membership function; bezier curves; differential evolution; curve fitting; optimization algorithm; fuzzy classification; fuzzy statistics; evolutionary algorithms
CLC:
TP181
DOI:
10.11992/tis.201706076
Abstract:
This study improves the method of determining the statistic-based membership function for membership function selection in fuzzy classification. Bezier curves are used as the ascendant or descendant edge of the membership function, to ensure that the membership function goes through any arbitrary points stipulated in statistical results. The control points of the Bezier curves are expressed by incremental polar coordinate coding, which solves the control point constraint problem in optimization of traditional Bezier curves. In addition, the differential evolution algorithm is used to optimize the control points of Bezier curves, and this can intelligently fit the best Bezier curve that goes through any arbitrary point. Results show that the proposed algorithm can be extended to any order Bezier curve, and the obtained membership functions are more reasonable than those of the non-Bezier curve method.
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