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441
Electric vehicle battery state of charge estimation using metaheuristic-optimized CatBoost algorithms
Published 2025-06-01“…Three distinct metaheuristic algorithms were investigated: Barnacles Mating Optimizer (BMO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Whale Optimization Algorithm (WOA), each integrated with CatBoost to optimize critical parameters including learning rate, tree depth, regularization, and bagging temperature. …”
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442
GWO and WOA variable step MPPT algorithms-based PV system output power optimization
Published 2025-03-01“…This study proposes two innovative Maximum Power Point Tracking (MPPT) algorithms based on the Whale Optimization Algorithm (WOA) and Grey Wolf Optimization (GWO). …”
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443
Enhanced skill optimization algorithm: Solution to the stochastic reactive power dispatch framework with optimal inclusion of renewable resources using large‐scale network
Published 2024-12-01“…The normal, lognormal, and Weibull distributions are utilized to model system uncertainties, while Monte‐Carlo simulation and reduction‐based approaches are utilized to generate the novel set of optimal scenarios. …”
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444
A Markov decision optimization of medical service resources for two-class patient queues in emergency departments via particle swarm optimization algorithm
Published 2025-01-01“…The particle swarm optimization algorithm was applied to determine the optimal number of servers, service rate, and number of beds. …”
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445
Explainable Artificial Intelligence in Malignant Lymphoma Classification: Optimized DenseNet121 Deep Learning Approach With Particle Swarm Optimization and Genetic Algorithm
Published 2025-01-01“…It is recommended that the combined application of PSO for feature reduction and GA for model optimization can be successfully used for improving accuracy rate of such algorithms while reducing computation time. …”
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446
Multi-strategy enterprise development optimizer for numerical optimization and constrained problems
Published 2025-03-01“…However, the analysis of the EDO algorithm shows that it suffers from the defects of rapidly decreasing population diversity and weak exploitation ability when dealing with complex optimization problems, while its algorithmic structure has room for further enhancement in the optimization process. …”
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447
A multi-objective optimization-based ensemble neural network wind speed prediction model
Published 2025-09-01“…Built upon the NSGA-II framework, NS-ADPOA enhances offspring generation by leveraging a probabilistic error-driven fusion of Particle Swarm Optimization (PSO) and Whale Optimization Algorithm (WOA), combining their strengths in local and global search, respectively. …”
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448
A Chemistry-Based Optimization Algorithm for Quality of Service-Aware Multi-Cloud Service Compositions
Published 2025-04-01“…These results validate the proposed approach’s effectiveness in optimizing service composition while minimizing computational overhead in multi-cloud environments.…”
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449
Real-Time Drilling Performance Optimization Using Automated Penetration Rate Algorithms with Vibration Control
Published 2025-05-01“…Automation has transformed process optimization across industries by enhancing efficiency, safety, and reliability while minimizing human intervention. …”
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450
DGA-ACO: Enhanced Dynamic Genetic Algorithm—Ant Colony Optimization Path Planning for Agribots
Published 2025-06-01“…A multi-objective fitness function simultaneously optimizes path length, energy efficiency, and safety metrics, while genetic operators prevent algorithmic stagnation. …”
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451
Optimizing stochastic multi-project scheduling with a simulation integrated multi-objective genetic algorithm
Published 2025-01-01“…The effectiveness of the proposed SIHMO-GA is evaluated through a real-world case study by comparing it with simulation-optimization approaches, namely the multi-objective genetic algorithm (MOGA) and goal attainment programming. …”
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452
Spatiotemporally Combined Dimensionality Reduction Algorithm for Optimizing Long-term Operation of Multi-reservoir Systems
Published 2023-01-01“…To alleviate the “curse of dimensionality” and improve the solution efficiency while ensuring the quality of solutions in optimizing the operation of multi-reservoir systems,this paper proposes a spatiotemporally combined dimensionality reduction algorithm which integrates and improves the dynamic programming with successive approximation (DPSA) and the progressive optimality algorithm (POA).First,a chain-based successive approximation strategy is proposed to expand the DPSA's optimization mode from “single reservoir alternation” to “cascade reservoir chain alternation”,which makes up for the DPSA's shortcomings in dealing with the hydraulic coupling relationships among cascade reservoirs.Then,a dynamic variable decoupling strategy and perturbation mechanism are proposed to deal with the POA's blind search problem and dimensionality problem.Finally,the two improved algorithms are combined,in which the improved POA is applied to solving the optimization problems of cascade reservoir chains under the framework of the improved DPSA.The power generation operation problem of the cascade reservoirs in the Yuan River Basin of Hunan Province and the classical ten-reservoir problem are utilized to test the performance of the proposed algorithm.The proposed algorithm outperforms seven existing alternatives in terms of solution quality and efficiency.The results indicate that the proposed algorithm can effectively alleviate the “curse of dimensionality” in optimizing the operation of multi-reservoir systems,improve the efficiency while ensuring the quality of solutions and has potential to be applied to optimizing the operation of complex large-scale multi-reservoir systems.…”
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453
An analysis of unconventional grid sizes for wind farm layout optimization using a genetic algorithm
Published 2025-01-01“…Due to the sheer complexity of the problem, evolutionary and swarm intelligence algorithms have been employed for wind farm layout optimization. …”
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454
Optimizing protein-ligand docking through machine learning: algorithm selection with AutoDock Vina
Published 2025-07-01“…While numerous algorithms exist for protein-ligand docking, achieving an optimal balance between accuracy and computational speed remains challenging. …”
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455
QELPS Algorithm: A Novel Dynamic Optimization Technology for Quantum Circuits Scheduling Engineering Problems
Published 2025-06-01“…We propose a collaborative optimization framework that integrates the Quantum Exchange Lock Parallel Scheduler (QELPS) with the Full-level Joint Optimization SWAP Algorithm (FJOSA). …”
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456
Learning-Driven Algorithm With Dual Evolution Patterns for Solving Large-Scale Multiobjective Optimization Problems
Published 2025-01-01“…Recently, a series of evolutionary algorithms have been proposed to enhance the search efficiency when handling large-scale multiobjective optimization problems (LSMOPs). …”
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457
Overlapping community-based fair influence maximization under a multi-transformation optimization algorithm
Published 2025-05-01“…Specifically, the proposed algorithm demonstrates a 9.2% improvement in average influence spread over the best existing method, while effectively addressing the trade-offs between influence, fairness, and complexity.…”
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458
Optimizing Feature Selection and Machine Learning Algorithms for Early Detection of Prediabetes Risk: Comparative Study
Published 2025-07-01“…PCA kept 12 components while maintaining 95% of the variance in the dataset. …”
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459
AI-driven genetic algorithm-optimized lung segmentation for precision in early lung cancer diagnosis
Published 2025-07-01“…This study presents an advanced AI-driven framework, optimized through genetic algorithms, for precise lung segmentation in early cancer diagnosis. …”
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460
Multiphase Transport Network Optimization: Mathematical Framework Integrating Resilience Quantification and Dynamic Algorithm Coupling
Published 2025-06-01“…Next, we create a dynamic adaptive public transit optimization model using an entropy weight-TOPSIS decision framework coupled with an improved simulated annealing algorithm (ISA-TS), achieving coordinated suburban–urban network optimization while maintaining 92.3% solution stability under simulated node failure conditions. …”
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