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Optimal Detection of Lung cancer using Bees Algorithm

Publication Type : Journal Article

Source : International Journal of Pure and Applied Mathematics, Volume 118, No. 18, 2018, 1775-1781

Url : https://acadpubl.eu/jsi/2018-118-18/articles/18b/65.pdf

Campus : Chennai

School : School of Engineering

Department : Computer Science and Engineering

Year : 2018

Abstract : In the world history of cancer decease, lung cancer plays a important role. It is significant to diagnose lung cancer at premature stage itself. To enhance detection radiologist use scans and X-ray images out of which CT scans seems to provide better result. So the proposed work deals with classifying data of CT scan images. Once classification is done the classified data is then optimized to improve the results with high accuracy. Several optimization algorithms like Ant Colony Optimization ,Genetic Algorithm, Bees Algorithm, Particle Swarm Optimization, Multi Swarm Optimization are compared and bees algorithm proves to give better accuracy result.

Cite this Research Publication : R. Abirami,L. Andrea, M. Diviya, Optimal Detection of Lung cancer using Bees Algorithm, International Journal of Pure and Applied Mathematics, Volume 118, No. 18, 2018, 1775-1781

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