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Improved particle swarm optimization by fast annealing algorithm

Bashath, Samar and Ismail, Amelia Ritahani (2019) Improved particle swarm optimization by fast annealing algorithm. In: 2019 International Conference of Artificial Intelligence and Information Technology (ICAIIT), 13th-15th March 2019, Yogyakarta, Indonesia,.

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Abstract

This paper proposes a hybrid particle swarm optimization with the fast-simulated annealing (PSO-FSA). The proposed algorithm is meant to solve high dimensional optimization problems based on two strategies, which are utilizing the particle swarm optimization to define the global search area and utilizing the fast-simulated annealing to refine the visited search area. To evaluate its performance, we examined the algorithm on 14 benchmark functions. Based on the results, PSO-FSA has higher accuracy result compared with particle swarm, simulated annealing. We also apply the algorithm in clustering problem, and the results shows that the proposed method has better accuracy than the optimization methods.

Item Type: Conference or Workshop Item (Plenary Papers)
Additional Information: 4296/77179
Uncontrolled Keywords: Particle swarm optimization, High dimension problems, Fast simulated annealing, clustering
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Information and Communication Technology
Kulliyyah of Information and Communication Technology

Kulliyyah of Information and Communication Technology > Department of Computer Science
Kulliyyah of Information and Communication Technology > Department of Computer Science
Depositing User: Amelia Ritahani Ismail
Date Deposited: 03 Feb 2020 10:01
Last Modified: 03 Feb 2020 10:01
URI: http://irep.iium.edu.my/id/eprint/77179

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