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421
A Deep Reinforcement Learning-Driven Seagull Optimization Algorithm for Solving Multi-UAV Task Allocation Problem in Plateau Ecological Restoration
Published 2025-06-01“…The algorithm improves both global and local search capabilities by optimizing key phases of seagull migration, attack, and post-attack refinement. …”
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422
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423
Enhanced OCR Recognition for Madurese Text Documents: A Genetic Algorithm Approach with Tesseract 5.5
Published 2025-08-01“…Character Recognition (OCR) for the Madurese language using Genetic Algorithms (GA). The study addresses the challenges in processing Madurese text documents by implementing a nine-step image preprocessing workflow optimized through GA. …”
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424
A two stage differential evolution algorithm for parameter estimation of proton exchange membrane fuel cell
Published 2025-02-01“…Abstract Precise models predicting fuel cell performance under different operating conditions require accurate parameter identification in a proton exchange membrane fuel cell (PEMFC). Most traditional parameter estimation methodologies depend on optimization algorithms which are limited in their efficiency, convergence speed, and robustness. …”
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425
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426
A Robust Salp Swarm Algorithm for Photovoltaic Maximum Power Point Tracking Under Partial Shading Conditions
Published 2024-12-01“…Finally, the integration with P&O facilitates a meticulous search with a small step size, ensuring swift convergence and further mitigating post-convergence power oscillations. Both the simulations and the experimental results indicate that the proposed algorithm outperforms particle swarm optimization (PSO) and grey wolf optimization (GWO) in terms of convergence velocity, tracking precision, and the reduction in iteration power oscillation magnitude.…”
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427
Emission prediction and optimization of methanol/diesel dual-fuel engines based on ITransformer-BiGRU and NSGA-III
Published 2025-01-01“…Finally, based on the obtained mathematical model, the 3rd Non-dominated Sorting Genetic Algorithm (NGSA-III) is used to adjust and optimize the control parameters. …”
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428
Improved K-means clustering and adaptive distance threshold for energy reduction in WSN-IoTs
Published 2025-09-01“…However, due to the limited battery capacity of sensor nodes, energy efficiency remains a critical challenge, especially since data transmission consumes the most energy. This study introduces an enhanced energy aware clustering approach that combines an improved K-Means algorithm with an adaptive distance threshold to optimize relay node selection and cluster formation. …”
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429
Environmental risk assessment based on multiscale spatial recurrent neural network algorithm for IoT agriculture area
Published 2025-07-01“…The Exhaustive Traffic Information Rate (ETIR) method evaluates the marginal rate of each feature, and the AntLion Behavior Optimization (ALBO) algorithm selects the most significant features, reducing dimensionality. …”
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430
Enhanced Multi-Threshold Otsu Algorithm for Corn Seedling Band Centerline Extraction in Straw Row Grouping
Published 2025-06-01“…The method avoids premature convergence and improves population diversity by embedding the crossover mechanism of Differential Evolution (DE) into the Whale Optimization Algorithm (WOA) and introducing a vector disturbance strategy. …”
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431
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432
Aircraft range fuel prediction study based on WPD with IAPO optimized BiLSTM–KAN model
Published 2025-04-01“…Additionally, the SPM chaotic mapping strategy is utilized for population initialization, while the introduction of the golden sine operator variation strategy enhances the local search capabilities of the algorithm. The adaptive swoop switching strategy adjusts the search intensity, thereby improving the global search performance and convergence speed of the Arctic Puffin Optimization (APO). …”
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433
A Hybrid Three-Staged, Short-Term Wind-Power Prediction Method Based on SDAE-SVR Deep Learning and BA Optimization
Published 2022-01-01“…Wind power prediction (WPP) is necessary to the safe operation and economic dispatch of power systems. In order to improve the prediction accuracy of WPP, in this paper we propose a three-step model named SDAE-SVR-BA to be applied in short-term WPP based on stacked-denoising-autoencoder (SDAE) feature processing, bat algorithm (BA) optimization and support vector regression (SVR). …”
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434
Implementing an Industry 4.0 UWB-Based Real-Time Locating System for Optimized Tracking
Published 2025-03-01Get full text
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435
A non-dominated sorting based multi-objective neural network algorithm of ethylene glycol hydrogenation reactor in energy reduction
Published 2024-12-01“…Abstract Artificial intelligence has revolutionized various industries, including chemical process optimization. Artificial intelligence (AI) can be applied to various ethylene glycol (EG) production aspects to improve efficiency, quality, and overall process optimization. …”
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436
A Novel Back Propagation Neural Network Based on the Harris Hawks Optimization Algorithm for the Remaining Useful Life Prediction of Lithium-Ion Batteries
Published 2025-07-01“…In order to achieve accurate and reliable RUL prediction, a novel RUL prediction method which employs a back propagation (BP) neural network based on the Harris Hawks optimization (HHO) algorithm is proposed. This method optimizes the BP parameters using the improved HHO algorithm. …”
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437
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438
A genetic algorithm-based solution for multi-type maximal covering location problem (MMCLP): application to defense and deterrence
Published 2024-12-01“…Design/methodology/approach – In our case study, we use open source geographic and demographic data from Canadian sources as inputs to our optimization problem. Due to the complexity of the MIP formulation, we propose a hybrid metaheuristic solution approach, for which a genetic algorithm (GA) is proposed and integrated with local and large neighborhood search operators. …”
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439
Prediction of compressive strength of fiber-reinforced concrete containing silica (SiO2) based on metaheuristic optimization algorithms and machine learning techniques
Published 2025-06-01“…So, this study integrates the ANFIS (adaptive neuro-fuzzy inference system) and ELM (extreme learning machine) machine learning models with three optimization algorithms, i.e., WCA (water cycle algorithm), PSO (particle swarm optimization), and GWO (grey wolf optimizer) to precisely estimate the CS of fiber-reinforced concrete (FRC) containing SiO2. …”
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440