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Issue title: Special Section: Intelligent tools and techniques for signals, machines and automation
Guest editors: Smriti Srivastava, Hasmat Malik and Rajneesh Sharma
Article type: Research Article
Authors: Gupta, Sangeeta; * | Upadhyaya, Varun | Singh, Ayush | Varshney, Pragya | Srivastava, Smriti
Affiliations: Department of Instrumentation and Control Engineering, NSIT, New Delhi, India
Correspondence: [*] Corresponding author. Sangeeta Gupta, Instrumentation and Control Engineering Department, NSIT, New Delhi, India. E-mail: [email protected].
Abstract: In this paper, a modified Artificial Bee Colony algorithm is proposed. Then estimation of the parameters of fractional order chaotic systems is performed using the proposed Artificial Bee Colony algorithm and Ant Colony algorithm. For the purpose of modeling, four fractional order chaotic systems viz. Financial System, Chen System, Lorenz’s system and 3 Cell Net system have been considered. Each chaotic system is defined by a set of fractional-order differential equations. These equations comprise of several variables – model parameters, derivative orders, and initial conditions. For the system’s entire state and future values to be known, the values of all the parameters have to be estimated to a reasonable degree of accuracy. It is a general practice to use modern evolutionary algorithms to solve such problems. Simulations on both nature inspired optimization algorithms are performed and estimated values of parameters determined. Comparisons with existing scheme of Artificial Bee Colony based parameter estimation are also performed. Observations reveal that the results of the modified ABC algorithm outperform those of other techniques for all the four cases.
Keywords: Artificial bee colony optimization (ABC), ant colony optimization (ACO), fractional order chaotic systems
DOI: 10.3233/JIFS-169816
Journal: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 5, pp. 5337-5344, 2018
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