Self-adaptive hybrid mutation slime mould algorithm: Case studies on UAV path planning, engineering problems, photovoltaic models and infinite impulse response-Reference-Cited by-同舟云学术

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Self-adaptive hybrid mutation slime mould algorithm: Case studies on UAV path planning, engineering problems, photovoltaic models and infinite impulse response

Published:2024-07 Issue: Volume:98 Page:364-389
ISSN:1110-0168
Container-title:Alexandria Engineering Journal
language:en
Short-container-title:Alexandria Engineering Journal

Author:

Zhang Yu-Jun,Wang Yu-Fei,Yan Yu-Xin,Zhao Juan^ORCID,Gao Zheng-Ming

Publisher

Elsevier BV

Reference105 articles.

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2. Tree growth algorithm (tga): a novel approach for solving optimization problems;Cheraghalipour;Eng. Appl. Artif. Intell.,2018

3. Biogeography-based optimization;Simon;IEEE Trans. Evolut. Comput.,2008

4. Genetic algorithms;Frenzel;IEEE Potentials,1993

5. Differential evolution with dynamic parameters selection for optimization problems;S.R. A;IEEE Trans. Evolut. Comput.,2014

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1. Parameters estimation of complex solar photovoltaic models using bi-parameter coordinated updating L-SHADE with parameter decomposition method;Case Studies in Thermal Engineering;2024-09

2. Gene-targeting multiplayer battle game optimizer for large-scale global optimization via cooperative coevolution;Cluster Computing;2024-06-14

3. A novel evolutionary status guided hyper-heuristic algorithm for continuous optimization;Cluster Computing;2024-06-08

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