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

Applied Soft Computing, Journal Year: 2023, Volume and Issue: 151, P. 111135 - 111135

Published: Dec. 7, 2023

Language: 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, Journal Year: 2024, Volume and Issue: 106, P. 474 - 504

Published: Aug. 24, 2024

Language: Английский

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

Expert Systems with Applications, Journal Year: 2023, Volume and Issue: 235, P. 121218 - 121218

Published: Aug. 19, 2023

Language: Английский

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

Expert Systems with Applications, Journal Year: 2023, Volume and Issue: 227, P. 120278 - 120278

Published: April 26, 2023

Language: Английский

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

Applied Energy, Journal Year: 2024, Volume and Issue: 378, P. 124853 - 124853

Published: Nov. 12, 2024

Language: Английский

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

Soft Computing, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 7, 2025

Language: Английский

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

Metallurgical Research & Technology, Journal Year: 2025, Volume and Issue: 122(2), P. 209 - 209

Published: Jan. 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

Language: Английский

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

Ain Shams Engineering Journal, Journal Year: 2025, Volume and Issue: 16(4), P. 103342 - 103342

Published: March 1, 2025

Language: 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, Journal Year: 2025, Volume and Issue: 18(1)

Published: May 8, 2025

Language: 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, Journal Year: 2025, Volume and Issue: 96, P. 101985 - 101985

Published: May 14, 2025

Language: Английский

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