Please wait a minute...
浙江大学学报(理学版)  2016, Vol. 43 Issue (2): 149-155    DOI: 10.3785/j.issn.1008-9497.2016.02.005
数学与计算机科学     
折线Mamdnai模糊系统及其权值参数的萤火虫优化算法
索春凤, 王贵君
天津师范大学数学科学学院, 天津 300387
Polygonal Mamdnai fuzzy system and the firefly optimization algorithm of its weight parameters
SUO Chunfeng, WANG Guijun
School of Mathematics Sciences, Tianjin Normal University, Tianjin 300387, China
 全文: PDF(1260 KB)  
摘要: 折线Mamdnai模糊系统是基于折线模糊数的线性运算构造的系统模型,其主要特点是前件模糊集及后件中心连接权均取值于由有限个有序点决定的折线模糊数.依据折线模糊规则建立了折线Mamdnai模糊系统模型,进而基于适应度函数、荧光素和决策半径设计了该系统权值参数的萤火虫优化算法,以优化该系统的后件中心连接权参数.最后,通过一个双输入单输出仿真实例,验证了该萤火虫优化算法的有效性.
关键词: 折线模糊数折线Mamdnai模糊系统后件中心连接权萤火虫优化算法    
Abstract: The polygonal Mamadnai fuzzy system is a model based on the linear operation of polygonal fuzzy numbers, and its main characteristic is that the antecedent fuzzy sets and consequent centre connection weights are decided by finite points of a polygonal fuzzy number. In this paper, a polygonal Mamdnai fuzzy system is constructed by some polygonal fuzzy rules, and a firefly optimization algorithm for the weigh parameters is designed based on the fitness function, fluorescein and decision radius. Therefore, the consequent centre connection weights of this system are optimized. Finally, through a double input and single output simulation instance, we verify the effectiveness of the firefly optimization algorithm.
Key words: polygonal fuzzy numbers    polygonal Mamadnai fuzzy system    consequent centre connection weights    firefly optimization algorithm
收稿日期: 2015-06-08 出版日期: 2016-03-12
CLC:  TP183  
基金资助: 国家自然科学基金资助项目(61374009).
通讯作者: 王贵君,E-mail:tjwgj@126.com.     E-mail: tjwgj@126.com
作者简介: 索春凤(1990-),ORCID:http://orcid.org/000-0001-7082-8151,女,硕士研究生,主要从事模糊神经网络与模糊系统研究,E-mail:1242362420@qq.com.
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  
索春凤
王贵君

引用本文:

索春凤, 王贵君. 折线Mamdnai模糊系统及其权值参数的萤火虫优化算法[J]. 浙江大学学报(理学版), 2016, 43(2): 149-155.

SUO Chunfeng, WANG Guijun. Polygonal Mamdnai fuzzy system and the firefly optimization algorithm of its weight parameters. Journal of ZheJIang University(Science Edition), 2016, 43(2): 149-155.

链接本文:

https://www.zjujournals.com/sci/CN/10.3785/j.issn.1008-9497.2016.02.005        https://www.zjujournals.com/sci/CN/Y2016/V43/I2/149

[1] 周永权,黄正新,刘洪霞.求解TSP问题的离散型萤火虫群优化算法[J].电子学报,2012,40(6):1164-1170. ZHOU Yongquan, HUANG Zhengxin, LIU Hongxia. Discrete glowworm swarm optimization algorithm for TSP problem[J]. Acta Electronica Sinica,2012, 40(6):1164-1170.
[2] 李永梅,周永权,韦军.用于函数优化的层次结构萤火虫群算法[J].应用科学学报,2012,30(4):391-396. LI Yongmei, ZHOU Yongquan, WEI Jun. Using hierarchical structure glowworm swarm algorithm for function optimization[J]. Journal of Applied Sciences,2012,30(4):391-396.
[3] 候越,赵贺,路小娟.基于萤火虫优化的BP神经网络算法研究[J].兰州交通大学学报,2013,32(6):24-27. HOU Yue, ZHAO He, LU Xiaojuan. Study on glowworm swarm optimized BP neural network algorithm[J]. Journal of Lanzhou Jiaotong University,2013,32(6):24-27.
[4] 刘长平,叶春明.一种新颖的仿生群智能优化算法:萤火虫算法[J].计算机应用研究,2011,28(9):3295-3297. LIU Changping, YE Chunming. Novel bioinspired swarm intelligence optimization algorithm:Firefly algorithm[J]. Application Research of Computers,2011,28(9):3295-3297.
[5] 吴斌,崔志勇,倪卫红.具有混合群智能行为的萤火虫群优化算法研究[J].计算机科学,2012,39(5):198-200. WU Bing, CUI Zhiyong, NI Weihong. Research on glowworm swarm optimization with hybrid swarm intelligence behavior[J]. Computer Science,2012,39(5):198-200.
[6] 喻金平,郑洁,梅洪标.基于改进人工蜂群算法的K均值聚类算法[J].计算机与应用,2014,34(4):1065-1069. YU Jinping, ZHENG Jie, MEI Hongbiao. K-means clustering algorithm based on improved artificial bee colony algorithm[J]. Journal of Computer Applicati-ons,2014,34(4):1065-1069.
[7] 刘普寅.一种新的模糊神经网络及其逼近性[J].中国科学:E辑,2002,32(1):76-86. LIU Puyin. A new fuzzy neural network and its approximation capability[J]. Science in China:Ser E, 2002,32(1):76-86.
[8] 王贵君,李晓萍.K-积分模意义下折线模糊神经网络的泛逼近性[J].中国科学:信息科学,2012,42(3):362-378. WANG Guijun, LI Xiaoping. Universal approxima-tion of polygonal fuzzy neural networks in sense of K-integral norms[J]. Scientia Sinica Informationis,2012,42(3):362-378.
[9] 何英,王贵君.折线模糊神经网络的共轭梯度法[J].电子学报,2012,40(10):2079-2084. HE Ying, WANG Guijun. Conjugate gradient algori-thm of the polygonal fuzzy neural networks[J]. Acta Electronica Sinica,2012,40(10):2079-2084.
[10] YANG Yongqiang, WANG Guijun, YANG Yang. Parameters optimization of polygonal fuzzy neural networks based on GA-BP hybrid algorithm[J].International Journal of Machine Learning and Cybernetics,2014,5(5):815-822.
[11] 隋晓琳,王贵君.训练模式对摄动对折线模糊神经网络稳定性的影响[J].模式识别与人工智能,2012,26(6):928-936 SUI Xiaolin, WANG Guijun. Influence of perturba-tion of training pattern pairs on stability of polygonal fuzzy neural networks[J]. Pattern Recognition and Artificial Intelligence,2012,26(6):928-936.
[12] 王贵君,何英,李晓萍.基于MISO折线模糊神经网络的优化算法[J].中国科学:信息科学,2015,45(5):650-667. WANG Guijun,HE Ying,LI Xiaoping. Optimization algorithm for MISO polygonal fuzzy neural network[J].Scientia Sinica Informationis,2015,45(5):650-667.
No related articles found!