A Novel Fruit Fly Optimization Algorithm with Evolution Strategy for Magnetotelluric Data Inversion

As a novel metaheuristic algorithm, fruit fly optimization algorithm (FOA) can effectively deal with the inversion problem of one-dimensional magnetotelluric data. However, FOA still has the disadvantage of premature convergence and falling into local extreme value. Therefore, based on standard FOA,...

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Main Authors: Bin Yin, Jie Yang, Yue Li
Format: Article
Language:English
Published: Wiley 2023-01-01
Series:Journal of Mathematics
Online Access:http://dx.doi.org/10.1155/2023/8810401
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author Bin Yin
Jie Yang
Yue Li
author_facet Bin Yin
Jie Yang
Yue Li
author_sort Bin Yin
collection DOAJ
description As a novel metaheuristic algorithm, fruit fly optimization algorithm (FOA) can effectively deal with the inversion problem of one-dimensional magnetotelluric data. However, FOA still has the disadvantage of premature convergence and falling into local extreme value. Therefore, based on standard FOA, we improve the FOA algorithm by introducing evolutionary strategies. Firstly, crossover and mutation strategies are introduced to improve the updating process of FOA population individuals. Secondly, by improving the variation scale factor, the global search and local search capabilities of the algorithm are balanced, and these improvements can accelerate the algorithm convergence. The improved algorithm is compared with other algorithms. After the benchmark function test, the improved algorithm has better optimization ability. Finally, the MT theoretical model and field data are used to test that the evolutionary strategy can effectively improve the convergence speed of the algorithm, and the inversion accuracy of the new algorithm is greatly improved.
format Article
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institution OA Journals
issn 2314-4785
language English
publishDate 2023-01-01
publisher Wiley
record_format Article
series Journal of Mathematics
spelling doaj-art-729fbe738dcf42da8e45c9f43da928cf2025-08-20T02:06:24ZengWileyJournal of Mathematics2314-47852023-01-01202310.1155/2023/8810401A Novel Fruit Fly Optimization Algorithm with Evolution Strategy for Magnetotelluric Data InversionBin Yin0Jie Yang1Yue Li2Jiangxi University of Science and TechnologyHubei Communications Planning and Design Institute Co., Ltd.Hubei Communications Planning and Design Institute Co., Ltd.As a novel metaheuristic algorithm, fruit fly optimization algorithm (FOA) can effectively deal with the inversion problem of one-dimensional magnetotelluric data. However, FOA still has the disadvantage of premature convergence and falling into local extreme value. Therefore, based on standard FOA, we improve the FOA algorithm by introducing evolutionary strategies. Firstly, crossover and mutation strategies are introduced to improve the updating process of FOA population individuals. Secondly, by improving the variation scale factor, the global search and local search capabilities of the algorithm are balanced, and these improvements can accelerate the algorithm convergence. The improved algorithm is compared with other algorithms. After the benchmark function test, the improved algorithm has better optimization ability. Finally, the MT theoretical model and field data are used to test that the evolutionary strategy can effectively improve the convergence speed of the algorithm, and the inversion accuracy of the new algorithm is greatly improved.http://dx.doi.org/10.1155/2023/8810401
spellingShingle Bin Yin
Jie Yang
Yue Li
A Novel Fruit Fly Optimization Algorithm with Evolution Strategy for Magnetotelluric Data Inversion
Journal of Mathematics
title A Novel Fruit Fly Optimization Algorithm with Evolution Strategy for Magnetotelluric Data Inversion
title_full A Novel Fruit Fly Optimization Algorithm with Evolution Strategy for Magnetotelluric Data Inversion
title_fullStr A Novel Fruit Fly Optimization Algorithm with Evolution Strategy for Magnetotelluric Data Inversion
title_full_unstemmed A Novel Fruit Fly Optimization Algorithm with Evolution Strategy for Magnetotelluric Data Inversion
title_short A Novel Fruit Fly Optimization Algorithm with Evolution Strategy for Magnetotelluric Data Inversion
title_sort novel fruit fly optimization algorithm with evolution strategy for magnetotelluric data inversion
url http://dx.doi.org/10.1155/2023/8810401
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