Binary Artificial Electric Field Algorithm

Versione 1.0.0.1 (5,15 KB) da Dr Anupam Yadav

Artificial Electric Field Algorithm (AEFA) is a population-based optimization techniques, it is inspired by the electrostatic force theory.

https://github.com/anupuam/BAEFA

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Aggiornato 24 giu 2023

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Artificial Electric Field Algorithm (AEFA) is a population-based optimization techniques, it is inspired by the electrostatic force theory. This is a binary version of the AEFA scheme to improve the performance of the original AEFA scheme in discrete space. The popular S-shaped and V-shaped functions are used to design the binary versions of the AEFA.

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Dr Anupam Yadav (2026). Binary Artificial Electric Field Algorithm (https://it.mathworks.com/matlabcentral/fileexchange/131568-binary-artificial-electric-field-algorithm), MATLAB Central File Exchange. Recuperato febbraio 5, 2026.

Chauhan, Dikshit, and Anupam Yadav. “Binary Artificial Electric Field Algorithm.” Evolutionary Intelligence, Springer Science and Business Media LLC, Apr. 2022, doi:10.1007/s12065-022-00726-x.

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

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Versione	Pubblicato	Note della release
1.0.0.1	24 giu 2023	No Change	Scarica
1.0.0	24 giu 2023		Scarica

MLA	Chauhan, Dikshit, and Anupam Yadav. “Binary Artificial Electric Field Algorithm.” Evolutionary Intelligence, Springer Science and Business Media LLC, Apr. 2022, doi:10.1007/s12065-022-00726-x.
APA	Chauhan, D., & Yadav, A. (2022). Binary Artificial Electric Field Algorithm. Evolutionary Intelligence. Springer Science and Business Media LLC. Retrieved from https://doi.org/10.1007%2Fs12065-022-00726-x
BibTeX	@article{Chauhan_2022, doi = {10.1007/s12065-022-00726-x}, url = {https://doi.org/10.1007%2Fs12065-022-00726-x}, year = 2022, month = {apr}, publisher = {Springer Science and Business Media {LLC}}, author = {Dikshit Chauhan and Anupam Yadav}, title = {Binary Artificial Electric Field Algorithm}, journal = {Evolutionary Intelligence} }