[1]肖琴,张永韡,汪镭.增量极坐标编码的贝赛尔曲线智能优化算法[J].智能系统学报,2017,(06):841-847.[doi:10.11992/tis.201706076]
 XIAO Qin,ZHANG Yongwei,WANG Lei.Intelligent optimized Bezier curves based on incremental polar coordinate coding[J].CAAI Transactions on Intelligent Systems,2017,(06):841-847.[doi:10.11992/tis.201706076]
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增量极坐标编码的贝赛尔曲线智能优化算法(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
期数:
2017年06期
页码:
841-847
栏目:
出版日期:
2017-12-25

文章信息/Info

Title:
Intelligent optimized Bezier curves based on incremental polar coordinate coding
作者:
肖琴1 张永韡2 汪镭3
1. 江苏科技大学 信息化建设与管理中心, 江苏 镇江 212003;
2. 江苏科技大学 电子信息学院, 江苏 镇江 212003;
3. 同济大学 电子与信息工程学院, 上海 200092
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
关键词:
隶属度函数贝塞尔曲线差分进化算法曲线拟合优化算法模糊分类模糊统计进化计算
Keywords:
membership functionbezier curvesdifferential evolutioncurve fittingoptimization algorithmfuzzy classificationfuzzy statisticsevolutionary algorithms
分类号:
TP181
DOI:
10.11992/tis.201706076
摘要:
针对基于统计的隶属度函数确定方法进行了改进,使用贝塞尔曲线作为隶属度函数的上升或下降沿,使隶属度函数可以经过统计结果规定的任意中间点。使用新的增量极坐标编码对贝塞尔曲线控制点进行表达,解决了传统贝塞尔曲线优化中的控制点约束问题。采用差分进化算法对贝塞尔曲线控制点进行优化,可智能拟合经过任意点的最佳贝塞尔曲线。算法可扩展到任意阶贝塞尔曲线,所得隶属度函数较非贝塞尔曲线方法更为合理。
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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备注/Memo

备注/Memo:
收稿日期:2017-06-23;改回日期:。
基金项目:国家自然科学基金项目(71371142, 61503287);镇江市软科学基金项目(2225031701).
作者简介:肖琴,女,1983年生,助理实验师,主要研究方向为机器学习、数据挖掘;张永韡,男,1983年生,讲师,博士,主要研究方向为智能计算、智能控制;汪镭,男,1970年生,教授,博导,主要研究方向为具有群体智能特征的各类智能理论和算法及其融合、并行实现技术。发表学术论文90余篇,出版专著4部。
通讯作者:张永韡.E-mail:ywzhang@just.edu.cn.
更新日期/Last Update: 2018-01-03