Takagi-Sugeno fuzzy modelling of some nonlinear problems using ant colony programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{Kamali:2017:AMM,

• author = "M. Z. M. Kamali and N. Kumaresan and Kuru Ratnavelu",
• title = "Takagi-Sugeno fuzzy modelling of some nonlinear problems using ant colony programming",
• journal = "Applied Mathematical Modelling",
• volume = "48",
• pages = "635--654",
• year = "2017",
• ISSN = "0307-904X",
• DOI = "doi:10.1016/j.apm.2017.04.019",
• URL = "http://www.sciencedirect.com/science/article/pii/S0307904X17302913",
• abstract = "In this paper, the Takagi-Sugeno fuzzy model is derived from the given nonlinear systems. The objective is to linearize these nonlinear systems into several fuzzy differential equations according to the Takagi-Sugeno fuzzy rules. The present work implemented the nontraditional ant colony programming (ACP) method to solve these fuzzy differential equations. The proposed ACP algorithm manages to give either similar or almost close solutions to the analytical form. Accuracy of the solution computed by this ACP method is qualitatively better when it is compared with other nontraditional approaches such as the genetic programming (GP) method. Illustrative numerical examples and tables are presented for comparative purpose.",
• keywords = "genetic algorithms, genetic programming, Ant colony programming, Differential equation, Fuzzy modelling",

}

Genetic Programming entries for Mohd Zahurin Bin Mohamed Kamali Nallasamy Kumaresan Kuru Ratnavelu

Citations