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An experience oriented-convergence improved gravitational search algorithm for minimum variance distortionless response beamforming optimum

algorithm; Article; computer heuristics; controlled study; data processing; experience oriented convergence improved gravitational search algorithm; gravitational search algorithm; minimum variance distortionless response beamforming technique; statistical analysis; statistical parameters; computer...

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Main Authors: Darzi S., Tiong S.K., Tariqul Islam M., Rezai Soleymanpour H., Kibria S.
Other Authors: 55651612500
Format: Article
Published: Public Library of Science 2023
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id my.uniten.dspace-22695
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spelling my.uniten.dspace-226952023-05-29T14:11:42Z An experience oriented-convergence improved gravitational search algorithm for minimum variance distortionless response beamforming optimum Darzi S. Tiong S.K. Tariqul Islam M. Rezai Soleymanpour H. Kibria S. 55651612500 15128307800 55328836300 57189004509 55637259500 algorithm; Article; computer heuristics; controlled study; data processing; experience oriented convergence improved gravitational search algorithm; gravitational search algorithm; minimum variance distortionless response beamforming technique; statistical analysis; statistical parameters; computer simulation; gravity; Algorithms; Computer Simulation; Gravitation An experience oriented-convergence improved gravitational search algorithm (ECGSA) based on two new modifications, searching through the best experiments and using of a dynamic gravitational damping coefficient (?), is introduced in this paper. ECGSA saves its best fitness function evaluations and uses those as the agents' positions in searching process. In this way, the optimal found trajectories are retained and the search starts from these trajectories, which allow the algorithm to avoid the local optimums. Also, the agents can move faster in search space to obtain better exploration during the first stage of the searching process and they can converge rapidly to the optimal solution at the final stage of the search process by means of the proposed dynamic gravitational damping coefficient. The performance of ECGSA has been evaluated by applying it to eight standard benchmark functions along with six complicated composite test functions. It is also applied to adaptive beamforming problem as a practical issue to improve the weight vectors computed by minimum variance distortionless response (MVDR) beamforming technique. The results of implementation of the proposed algorithm are compared with some well-known heuristic methods and verified the proposed method in both reaching to optimal solutions and robustness. � 2016 Darzi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Final 2023-05-29T06:11:42Z 2023-05-29T06:11:42Z 2016 Article 10.1371/journal.pone.0156749 2-s2.0-84978779871 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84978779871&doi=10.1371%2fjournal.pone.0156749&partnerID=40&md5=529f72686650a1af7732d15b6658cdbd https://irepository.uniten.edu.my/handle/123456789/22695 11 7 e0156749 All Open Access, Gold, Green Public Library of Science Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description algorithm; Article; computer heuristics; controlled study; data processing; experience oriented convergence improved gravitational search algorithm; gravitational search algorithm; minimum variance distortionless response beamforming technique; statistical analysis; statistical parameters; computer simulation; gravity; Algorithms; Computer Simulation; Gravitation
author2 55651612500
author_facet 55651612500
Darzi S.
Tiong S.K.
Tariqul Islam M.
Rezai Soleymanpour H.
Kibria S.
format Article
author Darzi S.
Tiong S.K.
Tariqul Islam M.
Rezai Soleymanpour H.
Kibria S.
spellingShingle Darzi S.
Tiong S.K.
Tariqul Islam M.
Rezai Soleymanpour H.
Kibria S.
An experience oriented-convergence improved gravitational search algorithm for minimum variance distortionless response beamforming optimum
author_sort Darzi S.
title An experience oriented-convergence improved gravitational search algorithm for minimum variance distortionless response beamforming optimum
title_short An experience oriented-convergence improved gravitational search algorithm for minimum variance distortionless response beamforming optimum
title_full An experience oriented-convergence improved gravitational search algorithm for minimum variance distortionless response beamforming optimum
title_fullStr An experience oriented-convergence improved gravitational search algorithm for minimum variance distortionless response beamforming optimum
title_full_unstemmed An experience oriented-convergence improved gravitational search algorithm for minimum variance distortionless response beamforming optimum
title_sort experience oriented-convergence improved gravitational search algorithm for minimum variance distortionless response beamforming optimum
publisher Public Library of Science
publishDate 2023
_version_ 1806427652472438784
score 13.222552

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