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