An atom search optimization approach for IIR system identification

Ekinci, Serdar; Budak, Cafer; Izci, Davut; Gider, Veysel

doi:10.1080/02286203.2023.2287968

International Journal of Modelling and Simulation

2023

DOI: 10.1080/02286203.2023.2287968

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An atom search optimization approach for IIR system identification

Serdar Ekinci,

Cafer Budak,

Davut Izci

et al.

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2024

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Cited by 2 publications

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A Modified Bonobo Optimizer With Its Application in Solving Engineering Design Problems

Alabdulhafith,

Batra,

Abdel Samee

et al. 2024

IEEE Access

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A Modified Bonobo Optimizer With Its Application in Solving Engineering Design Problems

Alabdulhafith,

Batra,

Abdel Samee

et al. 2024

IEEE Access

View full text Add to dashboard Cite

An Enhanced Symmetric Sand Cat Swarm Optimization with Multiple Strategies for Adaptive Infinite Impulse Response System Identification

Du,

Zhang,

Fang

2024

Symmetry

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An infinite impulse response (IIR) system might comprise a multimodal error surface and accurately discovering the appropriate filter parameters for system modeling remains complicated. The swarm intelligence algorithms facilitate the IIR filter’s parameters by exploring parameter domains and exploiting acceptable filter sets. This paper presents an enhanced symmetric sand cat swarm optimization with multiple strategies (MSSCSO) to achieve adaptive IIR system identification. The principal objective is to recognize the most appropriate regulating coefficients and to minimize the mean square error (MSE) between an unidentified system’s input and the IIR filter’s output. The MSSCSO with symmetric cooperative swarms integrates the ranking-based mutation operator, elite opposition-based learning strategy, and simplex method to capture supplementary advantages, disrupt regional extreme solutions, and identify the finest potential solutions. The MSSCSO not only receives extensive exploration and exploitation to refrain from precocious convergence and foster computational efficiency; it also endures robustness and reliability to facilitate demographic variability and elevate estimation precision. The experimental results manifest that the practicality and feasibility of the MSSCSO are superior to those of other methods in terms of convergence speed, calculation precision, detection efficiency, regulating coefficients, and MSE fitness value.

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An atom search optimization approach for IIR system identification

Cited by 2 publications

References 47 publications

A Modified Bonobo Optimizer With Its Application in Solving Engineering Design Problems

A Modified Bonobo Optimizer With Its Application in Solving Engineering Design Problems

An Enhanced Symmetric Sand Cat Swarm Optimization with Multiple Strategies for Adaptive Infinite Impulse Response System Identification

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