期刊文献+

基于α截集的改进二型模糊集合降阶算法研究

Research on Improved Type 2 Fuzzy Sets Reduction Algorithm Based on a-cut
分享 导出
摘要 针对普通二型模糊集合降阶计算量很大的问题,提出了一种基于α截集的改进降阶算法。利用α截集表示二型普通模糊集合,将普通二型模糊集合的降阶过程简化为α-区间二型模糊集合的降阶过程。对快速二型模糊集合降阶算法进行改进,利用插半法求取左、右切换点。2种不同形式的首隶属度函数和次隶属度函数的仿真实验表明,本文算法能够有效减少求取切换点的比较次数,提高运算效率,具有较强的实用性和适应性。 In according with large computing of type reduction for general type 2 fuzzy sets, an improved type reduction algorithm is proposed in this paper. The general type 2 fuzzy is expressed with a-cut, and the type reduction of general type 2 fuzzy sets is simplified interval type 2 fuzzy sets. The proposed algorithm improves fast type reduction for general type 2 fuzzy sets, where left and right switch point is obtained by half insert method. The simulation results of two kinds of first or secondary membership function shows the practical and adaptable of this method, which reduce the compare numbers for evaluation of switch point and improve operation efficiency.
作者 施建中 李荣 杨勇 SHI Jian-zhong, LI Rong,YANG Yong (School of Energy and Power Engineering, Nanjing Institute of Technology, Nanjing 211167,China)
出处 《模糊系统与数学》 CSCD 北大核心 2016年第4期50-60,共11页 Fuzzy Systems and Mathematics
基金 南京工程学院校级科研基金资助项目(YKJ201523)
关键词 降阶 α截集 二型模糊集合 KM/EKM算法 Type Reduction a-cut Type 2 Fuzzy Sets KM/EKM Algorithm
作者简介 施建中(1984-),男,江苏淮安人,南京工程学院能源与动力工程学院讲师,博士,研究方向:二型模糊逻辑系统辨识与控制; 李荣(1987-),男,山西忻州人,南京工程学院能源与动力工程学院讲师,博士研究生,研究方向:分数阶系统控制; 杨勇(1986-),女,陕西咸阳人,南京工程学院能源与动力工程学院讲师,博士研究生,研究方向:槽式太阳能发电系统建模与控制。
  • 相关文献

参考文献1

二级参考文献18

  • 1Molina-Lozano H. A new fast fuzzy Cocke-Younger- Kasami algorithm for DNA strings analysis[J]. Int J of Machine Learning and Cybernetics, 2011, 2(3): 209-218. 被引量:1
  • 2Wang X Z, He Y L, Dong L C, et al. Particle swarm optimization for determining fuzzy measures from data[J]. Information Science, 2011, 181(19): 4230-4252. 被引量:1
  • 3Wu J, Wang S T, Chung F L. Positive and negative fuzzy rule system, extreme learning machine and image classification[J]. Int J of Machine Learning and Cybernetics, 2011, 2(4): 261-271. 被引量:1
  • 4Zadeh L A. The concept of a linguistic variable and its application to approximate reasoning- Ⅰ[J]. Information Science, 1975, 8(3): 199-249. 被引量:1
  • 5Hagras H. A hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots[J]. IEEE Trans on Fuzzy Systems, 2004, 12(4): 524-539. 被引量:1
  • 6Lin F J, Chou P H. Adaptive control of two-axis motion control system using interval type-2 fuzzy neural network[J]. IEEE Trans on Industrial Electronics, 2009, 56(1): 178-193. 被引量:1
  • 7Melin P, Mendoza O, Castillo O. An improved method for edge detection based on interval type-2 fuzzy logic[J]. Expert Systems with Applications, 2010, 37(12): 8527- 8535. 被引量:1
  • 8Choi Byung-In, Frank Chung-H0on Rhee. Interval type-2 fuzzy membership function generation methods for pattern recognition[J]. Information Science, 2009, 179(13): 2102- 2122. 被引量:1
  • 9Lucas L A, Centeno T M, Delgado M R. Land cover classification based on general type-2 fuzzy classifiers[J]. Int J of Fuzzy Systems, 2008, 10(3): 207-216. 被引量:1
  • 10Zeng J, Liu Z Q. Type-2 fuzzy Markov random fields and their application to handwritten Chinese character recognition[J]. IEEE Trans on Fuzzy Systems, 2008, 16(3): 747-760. 被引量:1

共引文献4

投稿分析

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部 意见反馈