Research Article
Enhancing ABC with Dynamic Techniques to Optimize the Execution Time
@INPROCEEDINGS{10.4108/eai.16-4-2022.2318074, author={Samiulla Beg Mirza and Akhilesh A. Waoo}, title={Enhancing ABC with Dynamic Techniques to Optimize the Execution Time}, proceedings={Proceedings of The International Conference on Emerging Trends in Artificial Intelligence and Smart Systems, THEETAS 2022, 16-17 April 2022, Jabalpur, India}, publisher={EAI}, proceedings_a={THEETAS}, year={2022}, month={6}, keywords={artificial bee colony (abc) particle swarm optimization (pso) genetic algorithm (ga) wireless sensor network (wsn) glowworm swarm optimization (gso) improved artificial bee colony optimization-based clustering (iabcoct)}, doi={10.4108/eai.16-4-2022.2318074} }- Samiulla Beg Mirza
Akhilesh A. Waoo
Year: 2022
Enhancing ABC with Dynamic Techniques to Optimize the Execution Time
THEETAS
EAI
DOI: 10.4108/eai.16-4-2022.2318074
Abstract
This paper deals with the dynamic technique which is used in Artificial Bee Colony Algorithm to give better results. This technique is used in data optimization, so far whatever artificial Bee colony has been used in the field technology, takes more time in data optimization. Whereas when dynamic techniques are used in Artificial Bee Colony Algorithm, it takes less time for data optimization. Here using this technique to reduce the time and give a better result for optimization. This is the comparison done in this paper. In this paper, the technique is a comparison with a PSO and GA algorithm. This algorithm is best for all of them.
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