基于严格二叉树编码和GA的模糊树结构学习

doi:10.16182/j.issn1004731x.joss.19-0019

系统仿真学报 ›› 2020, Vol. 32 ›› Issue (8): 1473-1480.doi: 10.16182/j.issn1004731x.joss.19-0019

基于严格二叉树编码和GA的模糊树结构学习

刘长良^1,2, 王梓齐²

1.华北电力大学新能源电力系统国家重点实验室,北京 102206;
2.华北电力大学控制与计算机工程学院,河北保定 071003

收稿日期:2019-01-11 修回日期:2019-03-27 出版日期:2020-08-18 发布日期:2020-08-13
作者简介:刘长良(1966-),男,河北,博士,教授,博导,研究方向为系统建模与仿真、风电机组故障预警;王梓齐(1995-),男,河南,博士生,研究方向为模糊T-S系统及应用。
基金资助:
北京市自然科学基金(4182061),中央高校基本科研业务费专项资金(2018ZD05)

Structure Learning of Fuzzy-tree Based on Rigorous Binary Tree Code and Genetic Algorithm

Liu Changliang^1,2, Wang Ziqi²

1. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China;
2. School of Control and Computer Engineering, North China Electric Power University, Baoding 071003, China

Received:2019-01-11 Revised:2019-03-27 Online:2020-08-18 Published:2020-08-13

摘要/Abstract

摘要： 为解决模糊树模型结构学习中存在的信息冗余、寻优效率低等问题,提出了一种基于严格二叉树编码和遗传算法的结构学习方法。通过严格二叉树编码对模型结构进行编码,改善了现有矩阵编码的信息冗余问题;考虑到编码特殊性和算法收敛性,提出了一种改进的遗传算法用来对模糊树模型的结构进行寻优。实验结果表明,不同数据集上该算法的稳定性和计算速度均较好,能够寻找到一个较优的二叉树结构,从而提高模糊树模型的建模精度。

关键词: 模糊树, 严格二叉树编码, 遗传算法, 结构学习

Abstract: To solve the problems of information redundancy and low optimization efficiency in the structure learning of fuzzy-tree model, a method based on rigorous binary tree code and genetic algorithm is proposed. The structure of fuzzy-tree model is coded by rigorous binary tree code, which improves the information redundancy of the existing matrix code. Considering the particularity of the code and the convergence of the algorithm, an improved genetic algorithm is proposed to optimize the structure of fuzzy-tree model. The experimental results show that the algorithm has good stability and computing speed on different data sets, and can find a better binary tree structure, and that improves the modeling accuracy of fuzzy-tree model.

Key words: fuzzy-tree, rigorous binary tree code, genetic algorithm, structure learning

中图分类号:

TP301.6

刘长良, 王梓齐. 基于严格二叉树编码和GA的模糊树结构学习[J]. 系统仿真学报, 2020, 32(8): 1473-1480.

Liu Changliang, Wang Ziqi. Structure Learning of Fuzzy-tree Based on Rigorous Binary Tree Code and Genetic Algorithm[J]. Journal of System Simulation, 2020, 32(8): 1473-1480.

参考文献 19

[1]	Takagi T, Sugeno M.Fuzzy identification of systems and its applications to modeling and control[J]. IEEE Transactions on Systems, Man, and Cybernetics (S0018-9472), 1985, 15(1): 116-132.
[2]	Jang R.ANFIS: Adaptive-network-based fuzzy inference systems[J]. IEEE Transactions on Systems, Man, and Cybernetics (S0018-9472), 1993, 23(3): 665-685.
[3]	Chiu S L.Fuzzy model identification based on cluster estimation[J]. Journal of Intelligent & Fuzzy Systems (S1064-1246), 1994, 2(3): 267-278.
[4]	Mao J Q, Zhang J G, Yue Y F, et al.Adaptive-tree- structure-based fuzzy inference system[J]. IEEE Transactions on Fuzzy Systems (S1063-6706), 2005, 13(1): 1-12.
[5]	张伟, 柳萍, 刘青松, 等. 基于模糊树的Hammerstein-like模型对超磁致伸缩作动器的建模与控制[J]. 振动与冲击, 2013, 32(15): 184-189.Zhang Wei, Liu Ping, Liu Qingsong, et al.Modeling and control of giant magnetostrictive actuator based on a Hammerstein-like model by using fuzzy tree method[J]. Journal of Vibration and Shock, 2013, 32(15): 184-189.
[6]	张伟, 毛剑琴. 基于模糊树模型的非线性系统内模控制[J]. 控制理论与应用, 2013, 30(4): 463-468.Zhang Wei, Mao Jianqin.Internal model control for nonlinear system based on fuzzy-tree method[J]. Control Theory & Applications, 2013, 30(4): 463-468.
[7]	Zhang W G, Zhang Y, Sun Y Z, et al.Condition monitoring of limestone and soft sensing model of SO2 emissions in a circulating fluidized bed boiler[J]. Energy & Fuels (S0887-0624), 2016, 30(4): 3519-3528.
[8]	岳玉芳, 毛剑琴. 基于遗传算法优化模糊树模型参数的算法设计及仿真[J]. 系统仿真学报, 2002, 14(7): 870-873.Yue Yufang, Mao Jianqin.Parameter optimization and simulation for fuzzy tree model based on genetic algorithm[J]. Journal of System Simulation, 2002, 14(7): 870-873.
[9]	张伟, 毛剑琴. 基于最小Wilcoxon学习方法的模糊树模型[J]. 北京航空航天大学学报, 2013, 39(7): 973-977.Zhang Wei, Mao Jianqin.Least Wilcoxon learning method based fuzzy tree model[J]. Journal of Beijing University of Aeronautics and Astronautics, 2013, 39(7): 973-977.
[10]	张文广, 张越. 模糊树鲁棒回归算法的研究及其应用[J]. 动力工程学报, 2017, 37(5): 401-407.Zhang Wenguang, Zhang Yue.Research and application of the robust fuzzy tree method[J]. Journal of Chinese Society of Power Engineering, 2017, 37(5): 401-407.
[11]	刘建伟, 黎海恩, 罗雄麟. 概率图模型学习技术研究进展[J]. 自动化学报, 2014, 40(6): 1025-1044.Liu Jianwei, Li Haien, Luo Xionglin.Learning technique of probabilistic graphical model: a review[J]. Acta Automatica Sinica, 2014, 40(6): 1025-1044.
[12]	李硕豪, 张军. 贝叶斯网络结构学习综述[J]. 计算机应用研究, 2015, 32(3): 641-646.Li Shuohao, Zhang Jun.Review of Bayesian networks structure learning[J]. Application Research of Computers, 2015, 32(3): 641-646.
[13]	代冀阳, 张建刚. 基于遗传算法的模糊树建模方法[J]. 自动化学报, 2000, 26(5): 707-710.Dai Jiyang, Zhang Jiangang.Fuzzy-tree modeling based on genetic algorithm[J]. Acta Automatica Sinica, 2000, 26(5): 707-710.
[14]	代冀阳, 毛剑琴, 张建刚. GA矩阵编码方法及其在模糊建模中的应用[J]. 北京航空航天大学学报, 2000, 26(5): 612-615.Dai Jiyang, Mao Jianqin, Zhang Jiangang.Matrix coding in GA and its application to fuzzy modeling[J]. Journal of Beijing University of Aeronautics and Astronautics, 2000, 26(5): 612-615.
[15]	University of California Irvine. University of California Irvine Machine Learning Repository[EB/OL]. (2018-11-30) [2019-01-10]. http://archive.ics.uci.edu/ml.
[16]	Liu H J, Luo P, Zeng Z F.A structured hierarchical P2P model based on a rigorous binary tree code algorithm[J]. Future Generation Computer Systems (S0167-739X), 2007, 23(2): 201-208.
[17]	Liu H J, Luo P, Wang D S.A distributed expansible authentication model based on Kerberos[J]. Journal of Network & Computer Applications (S1084-8045), 2008, 31(4): 472-486.
[18]	徐蕾, 孙尚波. 基于严格二叉树的证书路径构造方法[J]. 计算机应用, 2010, 30(增2): 107-109.Xu Lei, Sun Shangbo.Certificate path construction in rigorous binary tree trust model[J]. Journal of Computer Applications, 2010, 30(S2): 107-109.
[19]	葛志远, 王永县, 南兰, 等. 基于二叉树结构编码的遗传算法[J]. 清华大学学报(自然科学版), 2000, 40(10): 125-128.Ge Zhiyuan, Wang Yongxian, Nan Lan, et al.Genetic algorithms based on binary tree structure encoding[J]. Journal of Tsinghua University (Science and Technology), 2000, 40(10): 125-128.

基于严格二叉树编码和GA的模糊树结构学习

Structure Learning of Fuzzy-tree Based on Rigorous Binary Tree Code and Genetic Algorithm

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献 19

相关文章 15

编辑推荐

Metrics

本文评价

[1]	李智杰, 石昊琦, 李昌华, 张颉. 基于改进遗传算法的影像中心布局优化方法[J]. 系统仿真学报, 2022, 34(6): 1173-1184.
[2]	付建林, 丁国富, 张剑, 江海凡, 郭沛佩. 基于响应面和NSGA-II的AGV系统多目标优化配置[J]. 系统仿真学报, 2022, 34(5): 994-1002.
[3]	王语童, 马世伟, 杨元睿, 陈超宇. 多机器人组合最大覆盖面积寻优及预测方法[J]. 系统仿真学报, 2022, 34(1): 86-92.
[4]	何昕杰, 周少武, 张红强, 吴亮红, 周游. 基于改进遗传算法的四向穿梭车系统订单排序优化[J]. 系统仿真学报, 2021, 33(9): 2166-2179.
[5]	唐婕, 曹瑾鑫. 共享汽车联合调度优化研究[J]. 系统仿真学报, 2021, 33(8): 1959-1968.
[6]	陈芮莹, 王承涛, 刘振元. 考虑服务水平的IT运维人员调度的智能遗传算法[J]. 系统仿真学报, 2021, 33(3): 732-744.
[7]	陆嘉波, 程培星, 黄羿, 姚进强, 杨雪梦, 马新强, 刘勇. 用于时敏目标打击链快速构建的智能方法[J]. 系统仿真学报, 2021, 33(2): 346-357.
[8]	孙国栋, 何其昌. 螺钉机工艺智能化设计与仿真方法研究[J]. 系统仿真学报, 2021, 33(1): 62-73.
[9]	毛李恒, 邓清, 刘柔妮, 孔祥龙. 针对多星多任务仿真调度的关键路径遗传算法[J]. 系统仿真学报, 2021, 33(1): 205-214.
[10]	樊海霞, 陈小惠. 一种连续无创血压预测的改进向量机学习方法[J]. 系统仿真学报, 2020, 32(9): 1686-1692.
[11]	王宁, 魏利胜. 一种基于GA的新型生物地理学优化算法研究[J]. 系统仿真学报, 2020, 32(9): 1717-1723.
[12]	魏乐, 李希金. 基于多目标的含风电场动态环境经济调度[J]. 系统仿真学报, 2020, 32(9): 1825-1830.
[13]	肖运启, 王乙. 基于混合建模仿真的大型风电场降损控制[J]. 系统仿真学报, 2020, 32(9): 1831-1838.
[14]	刘佳佳, 左兴权. 交叉口交通信号灯的模糊控制及优化研究[J]. 系统仿真学报, 2020, 32(12): 2401-2408.
[15]	张祥, 王艳, 纪志成. 基于动态交互层的柔性作业车间动态调度问题研究[J]. 系统仿真学报, 2020, 32(11): 2129-2137.