A teaching-learning-based optimization algorithm with reinforcement learning to address wind farm layout optimization problem

Applied Soft Computing, Год журнала: 2023, Номер 151, С. 111135 - 111135

Опубликована: Дек. 7, 2023

Язык: Английский

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PSAO: An enhanced Aquila Optimizer with particle swarm mechanism for engineering design and UAV path planning problems

Alexandria Engineering Journal, Год журнала: 2024, Номер 106, С. 474 - 504

Опубликована: Авг. 24, 2024

Язык: Английский

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Quadruple parameter adaptation growth optimizer with integrated distribution, confrontation, and balance features for optimization

Expert Systems with Applications, Год журнала: 2023, Номер 235, С. 121218 - 121218

Опубликована: Авг. 19, 2023

Язык: Английский

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An effective ensemble framework for Many-Objective optimization based on AdaBoost and K-means clustering

Expert Systems with Applications, Год журнала: 2023, Номер 227, С. 120278 - 120278

Опубликована: Апрель 26, 2023

Язык: Английский

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Microgrid energy management system with degradation cost and carbon trading mechanism: A multi-objective artificial hummingbird algorithm

Applied Energy, Год журнала: 2024, Номер 378, С. 124853 - 124853

Опубликована: Ноя. 12, 2024

Язык: Английский

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Improved snake optimizer based on forced switching mechanism and variable spiral search for practical applications problems

Soft Computing, Год журнала: 2025, Номер unknown

Опубликована: Фев. 7, 2025

Язык: Английский

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Prediction of the end-point carbon content and temperature of AOD furnace based on LAOA-DeepSCNs

Metallurgical Research & Technology, Год журнала: 2025, Номер 122(2), С. 209 - 209

Опубликована: Янв. 1, 2025

The end-point carbon content and temperature in the steelmaking process of AOD furnace are important factors affecting product quality, traditional algorithms have problems slow convergence, being easy to fall into local optimal solution lack a unified parameter selection criterion, which leads convergence low prediction accuracy. To solve above problems, research group adopts improved arithmetic optimization algorithm deep stochastic configuration networks (LAOA-DeepSCNs) predict furnace. First, correlation analysis was performed with SPSS identify seven as model inputs. Second, verify effect model, is compared three typical algorithms: BP, RBF SCN. results show that LAOA-DeepSCNs fastest speed, highest accuracy, strongest generalization ability. Finally, applied actual production steel mill, showed hit rate 90.8%, 86.4%; 92.6%, 88.1% for refining error within ±0.015%, ±0.01%; ±10 °C, ±5 respectively. Which can well meet practical needs mill. It also provides theoretical guidance control at

Язык: Английский

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A novel hybrid biological optimisation algorithm for tackling reservoir optimal operation problem

Ain Shams Engineering Journal, Год журнала: 2025, Номер 16(4), С. 103342 - 103342

Опубликована: Март 1, 2025

Язык: Английский

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Enhanced Global Optimization Using a Novel Hybrid Sine Cosine-Gazelle Algorithm with Brownian Motion and Lévy Flight Mechanisms

International Journal of Computational Intelligence Systems, Год журнала: 2025, Номер 18(1)

Опубликована: Май 8, 2025

Язык: Английский

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An improved arithmetic optimization algorithm based on reinforcement learning for global optimization and engineering design problems

Swarm and Evolutionary Computation, Год журнала: 2025, Номер 96, С. 101985 - 101985

Опубликована: Май 14, 2025

Язык: Английский

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