IIR model identification using a modified inclined planes system optimization algorithm

Mohammadi, Ali; Zahiri, Seyed Hamid

doi:10.1007/s10462-016-9500-z

Cited by 32 publications

(2 citation statements)

References 29 publications

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“…Simulated annealing [58] Teaching learning-based optimization [59] Thermodynamic laws [60] Harmony search [61] Gravitation [62,63] Taboo search [64] Big bang-big crunch [65] Group search optimizer [66] Charged system [67] Imperialist competitive algorithm [68] Central force [69] League championship algorithm [70] Chemical reaction [71] Colliding bodies optimization [72] Black hole [73] Interior search algorithm [74] Ray [75] Mine blast algorithm [76] Small-world [77] Soccer league competition algorithm [78] Galaxy-based [79] Seeker optimization algorithm [80] General relativity theory [81] Social-based algorithm [82] Sine cosine algorithm [83] Exchange market algorithm [84] Multi-verse optimizer [85] Nomadic people optimizer [86] Inclined planes system optimization [87] Group counseling optimization algorithm [88] Firework algorithm [89] Modified inclined planes system optimization [90] Simplified inclined planes system optimization [91] Spherical search [92] Solar system algorithm [15] evolve towards the global optimum [94]. In the second group, one individual moves in the search space and evolves towards the global optimum [95].…”

Section: Physical-based Metaheuristic Algorithms Human-based Metaheur...mentioning

confidence: 99%

The Archerfish Hunting Optimizer: a novel metaheuristic algorithm for global optimization

Zitouni¹,

Harous²,

Belkeram³

et al. 2021

Preprint

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Global optimization solves real-world problems numerically or analytically by minimizing their objective functions. Most of the analytical algorithms are greedy and computationally intractable. Metaheuristics are nature-inspired optimization algorithms. They numerically find a near-optimal solution for optimization problems in a reasonable amount of time. We propose a novel metaheuristic algorithm for global optimization. It is based on the shooting and

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Section: Physical-based Metaheuristic Algorithms Human-based Metaheur...mentioning

confidence: 99%

The Archerfish Hunting Optimizer: a novel metaheuristic algorithm for global optimization

Zitouni¹,

Harous²,

Belkeram³

et al. 2021

Preprint

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“…Several attempts have been made in recent years to investigate alternate architectures and methods for adaptive IIR filters. Mohammadi et al [34] have suggested an efficient optimization approach for digital IIR system identification based on inclined planes system optimization in 2017. Sarangi et al [35] produced Crazy cat swarm optimization (Crazy-CSO) algorithm to optimize the unknown plant.…”

Section: Introductionmentioning

confidence: 99%

A Whale Optimization Algorithm with Convergence and Exploitability Enhancement and Its Application

Liang

Zhang

2022

Mathematical Problems in Engineering

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The whale optimization algorithm (WOA) is inspired by humpback whale social behavior and WOA is a popular swarm intelligence algorithm. Yet, the WOA does have certain flaws, such as a restricted global search capability and an inconsistent convergence speed, and when dealing with complex optimization problems, WOA is easy to fall into local optimum. To address the WOA’s shortcomings, a modified whale optimization algorithm with convergence and exploitability enhancement called MWOA-CEE is proposed. Three operators, opposition-based learning, exponentially decreasing function, and elite-guided Cauchy mutation, are integrated into the WOA to enhance the exploration performance and avoid local optimum. First, the opposition-based learning used the opposition-based concept to generate the opposite position of the candidate solution, which can enhance the convergence ability and quality of the solution. Then, the exponentially decreasing function balances the exploitation and exploration phases and boosts the exploitation capability. In the end, the elite-guided Cauchy mutation generated a wide disturbance near the current candidate solution, which improves solutions diversity and increases the algorithm’s global search capability. MWOA-CEE is validated on 19 optimization benchmark functions and 14 CEC2014 benchmark functions and used to identify IIR systems. It is compared to seven of the commonly used algorithms. The results prove that MWOA-CEE outperforms the other algorithms in terms of final solution quality and convergence rate.

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Adaptive IIR Filtering for System Identification Applying the Method by Nelder and Mead

Guliashki

Marinova

2022

Communications in Computer and Information Science

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IIR model identification using a modified inclined planes system optimization algorithm

Cited by 32 publications

References 29 publications

The Archerfish Hunting Optimizer: a novel metaheuristic algorithm for global optimization

The Archerfish Hunting Optimizer: a novel metaheuristic algorithm for global optimization

A Whale Optimization Algorithm with Convergence and Exploitability Enhancement and Its Application

Adaptive IIR Filtering for System Identification Applying the Method by Nelder and Mead

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