Calculation of surface leakage currents on high voltage insulators by ant colony algorithm-supported FEM

Öztürk, Dursun; CEBECİ, Mehmet

doi:10.3906/elk-1305-6

Cited by 5 publications

(3 citation statements)

References 18 publications

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“…ACO was developed in 1991 by Dorigo et al, inspired by the behaviors of real ant colonies. Ant Colony Optimization (ACO) is a population-based approach that is often used in optimization problems [38,39].…”

Section: Ant Colony Optimization Algorithmmentioning

confidence: 99%

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Load-Frequency Optimization With Heuristic Techniques in a Autonomous Hybrid Ac Microgrid

Öztürk¹,

Çelik²,

Özdemir³

2017

IJESG

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Section: Ant Colony Optimization Algorithmmentioning

confidence: 99%

“…Ant Colony Optimization (ACO) is a population-based approach that is often used in optimization problems [38,39].…”

Section: Ant Colony Optimization Algorithmmentioning

confidence: 99%

Load-Frequency Optimization With Heuristic Techniques in a Autonomous Hybrid Ac Microgrid

Öztürk¹,

Çelik²,

Özdemir³

2017

IJESG

Self Cite

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show abstract

“…Although various optimization algorithms are available in the literature, there is no such thing as a main algorithm to be accepted as the best for any situation [1][2][3][4][5] and algorithm developers keep developing stronger and more efficient algorithms every day [6]. Metaheuristic based algorithms have generally been classified as bioinspired [7][8][9][10][11], swarm intelligence [12][13][14][15], evolutionary and nature-inspired algorithms [16][17][18][19] and physicsbased [20][21][22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

Chaos in metaheuristic based artificial intelligence algorithms: a short review

Atali¹,

Pehlivan²,

Gürevin³

et al. 2021

Turkish Journal of Electrical Engineering and Computer Sciences

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Metaheuristic based artificial intelligence algorithms are commonly used in the solution of optimization problems. Another area -besides engineering systems-where chaos theory is widely employed is optimization problems.Being applied easily and not trapping in local optima, chaos-based search algorithms have attracted great attention. For example, it has been reported that when random number sequences generated from different chaotic systems are replaced with parameter values in bioinspired and swarm intelligence algorithms, an increase in the performance of metaheuristic algorithms is observed. Many scientific studies on developing hybrid algorithms in which metaheuristic algorithms and chaos theory are used together are already in process.In this article, scientific studies that cover the most popular metaheuristic algorithms in the literature in recent years and chaos theory subtopics together are examined. Great number of studies on metaheuristic algorithms and chaos issues exist in scientific literature. This article, hitherto, had to be limited to the most common meta-heuristic algorithms. In chaos-based metaheuristic algorithms, some advantages such as easy implementation, short application time and search acceleration have been addressed.This article is believed to contribute to two groups of researchers: The first group includes researchers already using meta-heuristic algorithms and who will come to understand that they can even improve their current techniques with chaos theory subarguments. The second group includes those who currently utilize chaotic analysis and methods in areas like nonlinear prediction modeling design and who will realize that they can make their existing methods even smarter with metaheuristic methods. Some metaheuristic algorithms use chaotic maps to solve problems such as trapping in local optimal solutions and premature convergence. In this study, such algorithms are examined through the benchmark functions they use. In addition, PSO, FA, ABC, WO algorithms are compared in terms of their common features, and algorithms with the best success rate are presented.

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Influence of humidity and contamination on the leakage current of 230-kV composite insulator

Mohammadnabi

Rahmani

2021

Electric Power Systems Research

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Calculation of surface leakage currents on high voltage insulators by ant colony algorithm-supported FEM

Cited by 5 publications

References 18 publications

Load-Frequency Optimization With Heuristic Techniques in a Autonomous Hybrid Ac Microgrid

Load-Frequency Optimization With Heuristic Techniques in a Autonomous Hybrid Ac Microgrid

Chaos in metaheuristic based artificial intelligence algorithms: a short review

Influence of humidity and contamination on the leakage current of 230-kV composite insulator

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