AEFA: Artificial Electric Field Algorithm

Versione 1.0.0 (27,7 KB) da Dr Anupam Yadav

This simulates the charge movement of AEFA

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Aggiornato 15 apr 2019

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Electrostatic Force is one of the fundamental force of physical world. The concept of electric field and charged particles provide us a strong theory for the working force of attraction or repulsion between two charged particles. In the recent years many heuristic optimization algorithms are proposed based on natural phenomenon. The current article proposes a novel artificial electric field algorithm (AEFA) which inspired by the Coulomb's law of electrostatic force. The AEFA has been designed to work as a population based optimization algorithm, the concept of charge is extended to fitness value of the population in an innovative way.

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Dr Anupam Yadav (2024). AEFA: Artificial Electric Field Algorithm (https://www.mathworks.com/matlabcentral/fileexchange/71218-aefa-artificial-electric-field-algorithm), MATLAB Central File Exchange. Recuperato novembre 25, 2024.

Anita, and Anupam Yadav. “AEFA: Artificial Electric Field Algorithm for Global Optimization.” Swarm and Evolutionary Computation, vol. 48, Elsevier BV, Aug. 2019, pp. 93–108, doi:10.1016/j.swevo.2019.03.013.

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Sciences > Material Sciences > Thermal Analysis >

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Ispirato da: Gravitational Search Algorithm (GSA)

Ispirato: iAEFA, AEFA for Training Neural Network (GAEFA-HK)

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Versione	Pubblicato	Note della release
1.0.0	15 apr 2019		Zip Toolbox

MLA	Anita, and Anupam Yadav. “AEFA: Artificial Electric Field Algorithm for Global Optimization.” Swarm and Evolutionary Computation, vol. 48, Elsevier BV, Aug. 2019, pp. 93–108, doi:10.1016/j.swevo.2019.03.013.
APA	Anita, & Yadav, A. (2019). AEFA: Artificial electric field algorithm for global optimization. Swarm and Evolutionary Computation, 48, 93–108. Elsevier BV. Retrieved from https://doi.org/10.1016%2Fj.swevo.2019.03.013
BibTeX	@article{Anita_2019, doi = {10.1016/j.swevo.2019.03.013}, url = {https://doi.org/10.1016%2Fj.swevo.2019.03.013}, year = 2019, month = {aug}, publisher = {Elsevier {BV}}, volume = {48}, pages = {93--108}, author = {Anita and Anupam Yadav}, title = {{AEFA}: Artificial electric field algorithm for global optimization}, journal = {Swarm and Evolutionary Computation} }