Identification of the parameters of fuzzy approximators and classifiers based on the cuckoo search algorithm

被引：8
作者：
Hodashinsky I.A. [1 ]
Minina D.Y. [1 ]
Sarin K.S. [1 ]
机构：
[1] Tomsk State University of Control Systems and Radio Electronics, pr. Lenina 40, Tomsk
来源：
Optoelectronics, Instrumentation and Data Processing | 2015年 / 51卷 / 03期
关键词：
cuckoo search algorithm; fuzzy approximator; fuzzy classifier; parameter identification;
D O I：
10.3103/S8756699015030048
中图分类号：
学科分类号：
摘要：
A cuckoo search algorithm for identifying the parameters of fuzzy approximators and classifiers is presented. The results of experiments on eight sets of data from the KEEL repository are described. Comparison with analogs are given. © 2015, Allerton Press, Inc.
引用
收藏
页码：234 / 240
页数：6
相关论文
共 22 条
[1]  
Takagi T., Sugeno M., Fuzzy Identification of Systems and Its Application to Modeling and Control, IEEE Trans. Syst., Man, and Cybern., 15, 1, pp. 116-132, (1985)
[2]  
Sugeno M., Yasukawa T., A Fuzzy-Logic-Based Approach to Qualitative Modeling, IEEE Trans. Fuzzy Syst., 1, 1, pp. 7-31, (1993)
[3]  
Herrera F., Genetic Fuzzy Systems: Taxonomy, Current Research Trends and Prospects, Evolutionary Intelligence, 1, 1, pp. 27-46, (2008)
[4]  
Hodashinsky I.A., Gorbunov I.V., Algorithms of the Tradeoff between Accuracy and Complexity in the Design of Fuzzy Approximators, Avtometriya, 49, 6, pp. 51-61, (2013)
[5]  
Hodashinsky I.A., Sin'kov D.S., The Use of the Hybrid Quantum Algorithm of Swarming Particles to Identify the Parameters of Fuzzy Approximators, Informatika i Sistemy Upravleniya, 36, 2, pp. 56-63, (2013)
[6]  
Juang C.-F., Chang P.-H., Designing Fuzzy-Rule-Based Systems Using Continuous Ant-Colony Optimization, IEEE Trans. Fuzzy Syst., 18, 1, pp. 138-149, (2010)
[7]  
Hodashinsky I.A., Dudin P.A., Lavygina A.V., Bioinspired Methods of Parametric Identification of Fuzzy Models, Dokl.TUSUR, 16, 2, pp. 81-92, (2007)
[8]  
Yang X.-S., Deb S., Engineering Optimisation by Cuckoo Search, Intern. J. Math. Modelling Numerical Optimisation, 1, 4, pp. 330-343, (2010)
[9]  
Yang X.-S., Deb S., Cuckoo Search: Recent Advances and Applications, Neural Comput. Appl., 24, 1, pp. 169-174, (2014)
[10]  
Civicioglu P., Besdok E., A Conceptual Comparison of the Cuckoo-Search, Particle Swarm Optimization, Differential Evolution and Artificial Bee Colony Algorithms, Artificial Intell. Rev., 39, 4, pp. 315-346, (2013)
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