Multilevel thresholding based on CDPSO

Versión 1.0.0 (12,8 KB) por Shilpa Suresh

Improved variant of Darwinian PSO algorithm based on chaotic functions.

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Actualizado 16 jul 2019

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Introduces an improved variant of Darwinian PSO algorithm based on chaotic functions.
It replaces random sequences by chaotic sequences mitigating the problem of premature convergence.Efficiency of 10 defined chaotic maps are investigated and the best one was chosen.

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Suresh, Shilpa, and Shyam Lal. “Multilevel Thresholding Based on Chaotic Darwinian Particle Swarm Optimization for Segmentation of Satellite Images.” Applied Soft Computing, vol. 55, Elsevier BV, June 2017, pp. 503–22, doi:10.1016/j.asoc.2017.02.005.

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Versión	Publicado	Notas de la versión
1.0.0	16 jul 2019		Descargar

MLA	Suresh, Shilpa, and Shyam Lal. “Multilevel Thresholding Based on Chaotic Darwinian Particle Swarm Optimization for Segmentation of Satellite Images.” Applied Soft Computing, vol. 55, Elsevier BV, June 2017, pp. 503–22, doi:10.1016/j.asoc.2017.02.005.
APA	Suresh, S., & Lal, S. (2017). Multilevel thresholding based on Chaotic Darwinian Particle Swarm Optimization for segmentation of satellite images. Applied Soft Computing, 55, 503–522. Elsevier BV. Retrieved from https://doi.org/10.1016%2Fj.asoc.2017.02.005
BibTeX	@article{Suresh_2017, doi = {10.1016/j.asoc.2017.02.005}, url = {https://doi.org/10.1016%2Fj.asoc.2017.02.005}, year = 2017, month = {jun}, publisher = {Elsevier {BV}}, volume = {55}, pages = {503--522}, author = {Shilpa Suresh and Shyam Lal}, title = {Multilevel thresholding based on Chaotic Darwinian Particle Swarm Optimization for segmentation of satellite images}, journal = {Applied Soft Computing} }