Detecor algorithm: derived from the exploration of iterative methods DOI Creative Commons
Jia Jia Li, Weimin Zheng

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 22, 2024

Abstract The paper summarizes the pattern framework of some optimization algorithms, and proposes four directions within this algorithmic pattern: search agent particles, direction perturbation, step size. Based on pattern, introduces an algorithm called "Detector", name is just for convenient.In algorithm, as well size, it performs simple processing only considers iterative particles. For current position a function designed to evaluate position. If value greater than threshold, particle will not explore around that position, but move another location.This without any natural inspirations, in order prove effectiveness proposed framework. It also analyzes limitations class algorithms.The tested CEC2013, CEC2014, CEC2015, CEC2017, CEC2022 test suites, compared with 9 other focus high-cost CEC2013 suite. most functions suites. uses very small number parameters steps, inspirations.

Language: Английский

An atom search optimization approach for IIR system identification DOI
Serdar Ekinci, Cafer Budak, Davut İzci

et al.

International Journal of Modelling and Simulation, Journal Year: 2023, Volume and Issue: unknown, P. 1 - 17

Published: Nov. 27, 2023

Filtering, or digital signal processing, is a significant and fundamental requirement in fields such as systems computers. The process of designing optimal filters difficult, which has led researchers to design using emerging evolutionary computations. Metaheuristics have emerged the most promising tool for solving optimization problems, with excellent development improvement. However, it not been clear how select best performing metaheuristic an filter. In this paper, infinite impulse response (IIR) filter constructed atom search (ASO) algorithm impressed by physical motion atoms nature based on molecular dynamics. simulation results obtained are extensively compared other algorithms moth flame optimization, gravitational artificial bee colony optimization. ASO was found highest percentage Furthermore, eight cases analyzed across four numerical instances same degree reduced degree, validated outperforming several different algorithm-based approaches literature. stability analysis basis pole zero diagrams further cements efficacy IIR system identification problem.

Language: Английский

Citations

7
A new mixed order reduction method using bonobo optimizer and stability equation DOI

Priyajit Dash,

M. L. Meena, Girish Parmar

et al.

Microsystem Technologies, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 11, 2024

Language: Английский

Citations

1
An Enhanced Symmetric Sand Cat Swarm Optimization with Multiple Strategies for Adaptive Infinite Impulse Response System Identification DOI Open Access

Chengtao Du,

Jinzhong Zhang, Jie Fang

et al.

Symmetry, Journal Year: 2024, Volume and Issue: 16(10), P. 1255 - 1255

Published: Sept. 24, 2024

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

Language: Английский

Citations

1
AI in gastrointestinal disease detection: overcoming segmentation challenges with Coati optimization strategy DOI

Manikandan Jagarajan,

Ramkumar Jayaraman

Evolving Systems, Journal Year: 2024, Volume and Issue: 16(1)

Published: Nov. 16, 2024

Language: Английский

Citations

0
Detecor algorithm: derived from the exploration of iterative methods DOI Creative Commons
Jia Jia Li, Weimin Zheng

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 22, 2024

Abstract The paper summarizes the pattern framework of some optimization algorithms, and proposes four directions within this algorithmic pattern: search agent particles, direction perturbation, step size. Based on pattern, introduces an algorithm called "Detector", name is just for convenient.In algorithm, as well size, it performs simple processing only considers iterative particles. For current position a function designed to evaluate position. If value greater than threshold, particle will not explore around that position, but move another location.This without any natural inspirations, in order prove effectiveness proposed framework. It also analyzes limitations class algorithms.The tested CEC2013, CEC2014, CEC2015, CEC2017, CEC2022 test suites, compared with 9 other focus high-cost CEC2013 suite. most functions suites. uses very small number parameters steps, inspirations.

Language: Английский

Citations

0