Research Article
Studying Genetic Algorithm and Particle Swarm Optimization In Machine Learning
@INPROCEEDINGS{10.4108/eai.27-2-2020.2303168, author={Shameen Basharat and Sapna Jain}, title={Studying Genetic Algorithm and Particle Swarm Optimization In Machine Learning}, proceedings={Proceedings of the 2nd International Conference on ICT for Digital, Smart, and Sustainable Development, ICIDSSD 2020, 27-28 February 2020, Jamia Hamdard, New Delhi, India}, publisher={EAI}, proceedings_a={ICIDSSD}, year={2021}, month={3}, keywords={genetic algorithm swarm intelligence machine learning fitness function}, doi={10.4108/eai.27-2-2020.2303168} }- Shameen Basharat
Sapna Jain
Year: 2021
Studying Genetic Algorithm and Particle Swarm Optimization In Machine Learning
ICIDSSD
EAI
DOI: 10.4108/eai.27-2-2020.2303168
Abstract
Each streamlining issue can be disentangled into the basic minimum-seeking dilemma. Which way is the most limited in separation? Which choice is the least expensive? Such inquiries are surely key to the investigation of optimisation. The accomplishment of genetic algorithm and swarm intelligence in managing enhancement issues is their common capacity to progressively find minima through straightforward, nearby associations of potential arrangements. This paper learns about streamlining methods like Genetic Algorithm utilizing Swarm Intelligence.
Copyright © 2020–2025 EAI
