Title: The compound iterative algorithm for rational models based on the Coyote optimisation algorithm

Authors: Fei Xu; Jing Chen; Xia Yin

Addresses: School of Science, Jiangnan University, Jiangsu, Wuxi, China ' School of Science, Jiangnan University, Jiangsu, Wuxi, China ' School of Science, Jiangnan University, Jiangsu, Wuxi, China

Abstract: This article proposes a Coyote Optimisation Compound Iterative Algorithm (CO-CIA) for rational models. Particularly, the parameters in the numerator and denominator of rational models make the derivative equation hard to solve. To deal with this problem, the Coyote Optimisation Algorithm (COA) is applied to estimate the parameters in the denominator. Compared with the Bias Compensation-based Least Squares (BCLS) algorithm and the Particle Swarm Optimisation Compound Iterative Algorithm (PSO-CIA), the proposed method has higher accuracy and faster convergence rates. Finally, a simulation example is utilised to verify the effectiveness of the proposed algorithm.

Keywords: Coyote optimisation algorithm; recursive least squares; rational model; parameter estimation; compound iterative algorithm.

DOI: 10.1504/IJCAT.2023.133881

International Journal of Computer Applications in Technology, 2023 Vol.72 No.4, pp.241 - 248

Received: 07 Jan 2023
Accepted: 23 Feb 2023
Published online: 04 Oct 2023 *

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