应用改进型微粒群算法优化语言模型

被引:1
作者
刘建成
蒋新华
吴今培
机构
[1] 中南大学信息科学与工程学院
基金
湖南省自然科学基金;
关键词
语言模型; 语言值; 改进型微粒群算法;
D O I
暂无
中图分类号
TP301.6 [算法理论];
学科分类号
081202 ;
摘要
语言模型具有很好的可理解性特征,但在多数情况下,其精确性是难满足要求的.本文利用改进型微粒群算法(MPSO)优化输入变量的语言值及对应的正交模糊集参数,再应用Wang方法以形成语言模型,在保持可理解性情况下,获得较精确的语言模型.改进型微粒群算法采用惯性权重自适应动态调整策略,结果显示该改进算法在语言模型过程中更容易获得全局最优解,学习效率和优化性能明显提高.
引用
收藏
页码:2306 / 2309
页数:4
相关论文
共 8 条
[1]  
Generating fuzzy rules by learning from examples. Wang L X,Mendel J. IEEE Transactions on Systems,Man and Cyber-netics . 1992
[2]  
Particle swarm optimization:Develop-ments,applications and resources. Eberhart R C,Shi Y. Proc.2001Congress on Evolutionary Computation . 2001
[3]  
Linguistic decision analysis:steps for solving decision problems under linguistic information. Herrera F,Herrera-Viedma E. Fuzzy Sets and Systems . 2000
[4]  
Particle swarm optimization. Kennedy J,Eberhart R. Proc IEEE Int Conf on Neural Networks.Perth . 1995
[5]  
Learning fuzzy rules using ant colony optimization algorithms. Casillas J,Cordón O,Herrera F. Technical Report#DEC-SAI-01-01-03,Department of Computer and Artificial Intelli-gence,University of Granada . 2001
[6]  
A proposal for improving the accuracy of linguistic modeling. Cordón O,Herrera F. IEEE Transactions on Fuzzy Systems . 2000
[7]  
Coevolutionary fuzzy modeling. Pen~a-Reyes C A. . 2002
[8]  
Designing fuzzy inference systems from data:An interpretability oriented review. Guillaume S. IEEE Transactions on Fuzzy Systems . 2001