Parameters identification of photovoltaic models by using an enhanced adaptive butterfly optimization algorithm

Energy, Journal Year: 2021, Volume and Issue: 229, P. 120750 - 120750

Published: April 27, 2021

Language: Английский

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Parameters estimation of photovoltaic models using a novel hybrid seagull optimization algorithm

Energy, Journal Year: 2022, Volume and Issue: 249, P. 123760 - 123760

Published: March 15, 2022

Language: Английский

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Nature-inspired optimization algorithms and their significance in multi-thresholding image segmentation: an inclusive review

Evolving Systems, Journal Year: 2022, Volume and Issue: 13(6), P. 889 - 945

Published: Feb. 21, 2022

Language: Английский

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Improved Salp swarm algorithm for solving single-objective continuous optimization problems

Applied Intelligence, Journal Year: 2022, Volume and Issue: 52(15), P. 17217 - 17236

Published: March 31, 2022

Language: Английский

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A feature selection method based on the Golden Jackal-Grey Wolf Hybrid Optimization Algorithm

PLoS ONE, Journal Year: 2024, Volume and Issue: 19(1), P. e0295579 - e0295579

Published: Jan. 2, 2024

This paper proposes a feature selection method based on hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). The primary objective of this is to create an effective data dimensionality reduction technique for eliminating redundant, irrelevant, noisy features within high-dimensional datasets. Drawing inspiration from Chinese idiom “Chai Lang Hu Bao,” mechanisms, cooperative behaviors observed in natural animal populations, we amalgamate GWO algorithm, Lagrange interpolation method, GJO propose multi-strategy fusion GJO-GWO algorithm. In Case 1, addressed eight complex benchmark functions. 2, was utilized tackle ten problems. Experimental results consistently demonstrate under identical experimental conditions, whether solving functions or addressing problems, exhibits smaller means, lower standard deviations, higher classification accuracy, reduced execution times. These findings affirm superior performance, stability

Language: Английский

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Q-Learning-Driven Butterfly Optimization Algorithm for Green Vehicle Routing Problem Considering Customer Preference

Biomimetics, Journal Year: 2025, Volume and Issue: 10(1), P. 57 - 57

Published: Jan. 15, 2025

This paper proposes a Q-learning-driven butterfly optimization algorithm (QLBOA) by integrating the Q-learning mechanism of reinforcement learning into (BOA). In order to improve overall ability algorithm, enhance accuracy, and prevent from falling local optimum, Gaussian mutation with dynamic variance was introduced, migration also used population diversity algorithm. Eighteen benchmark functions were compare proposed method five classical metaheuristic algorithms three BOA variable methods. The QLBOA solve green vehicle routing problem time windows considering customer preferences. influence decision makers’ subjective preferences weight factors on fuel consumption, carbon emissions, penalty cost, total cost are analyzed. Compared algorithms, experimental results show that has generally superior performance.

Language: Английский

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Recursive elimination–election algorithms for wrapper feature selection

Applied Soft Computing, Journal Year: 2021, Volume and Issue: 113, P. 107956 - 107956

Published: Oct. 8, 2021

Language: Английский

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Lens-imaging learning Harris hawks optimizer for global optimization and its application to feature selection

Expert Systems with Applications, Journal Year: 2022, Volume and Issue: 202, P. 117255 - 117255

Published: April 26, 2022

Language: Английский

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A velocity-based butterfly optimization algorithm for high-dimensional optimization and feature selection

Expert Systems with Applications, Journal Year: 2022, Volume and Issue: 201, P. 117217 - 117217

Published: April 13, 2022

Language: Английский

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A mixed sine cosine butterfly optimization algorithm for global optimization and its application

Cluster Computing, Journal Year: 2022, Volume and Issue: 25(6), P. 4573 - 4600

Published: Aug. 11, 2022

Language: Английский

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