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made optimization » model optimization (Expand Search), whale optimization (Expand Search), based optimization (Expand Search)
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binary layer » boundary layer (Expand Search), final layer (Expand Search), linear layer (Expand Search)
layer made » layer model (Expand Search), layer map (Expand Search)
based art » based care (Expand Search)
made optimization » model optimization (Expand Search), whale optimization (Expand Search), based optimization (Expand Search)
art optimization » swarm optimization (Expand Search), after optimization (Expand Search), path optimization (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
binary layer » boundary layer (Expand Search), final layer (Expand Search), linear layer (Expand Search)
layer made » layer model (Expand Search), layer map (Expand Search)
based art » based care (Expand Search)
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Hyperparameters of the LSTM Model.
Published 2025“…The capacity to confront and overcome this obstacle is where machine learning and metaheuristic algorithms shine. This study introduces the Adaptive Dynamic Particle Swarm Optimization enhanced with the Guided Whale Optimization Algorithm (AD-PSO-Guided WOA) for rainfall prediction. …”
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The AD-PSO-Guided WOA LSTM framework.
Published 2025“…The capacity to confront and overcome this obstacle is where machine learning and metaheuristic algorithms shine. This study introduces the Adaptive Dynamic Particle Swarm Optimization enhanced with the Guided Whale Optimization Algorithm (AD-PSO-Guided WOA) for rainfall prediction. …”
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Prediction results of individual models.
Published 2025“…The capacity to confront and overcome this obstacle is where machine learning and metaheuristic algorithms shine. This study introduces the Adaptive Dynamic Particle Swarm Optimization enhanced with the Guided Whale Optimization Algorithm (AD-PSO-Guided WOA) for rainfall prediction. …”
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Analysis and design of algorithms for the manufacturing process of integrated circuits
Published 2023“…The (approximate) solution proposals of state-of-the-art methods include rule-based approaches, genetic algorithms, and reinforcement learning. …”
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datasheet1_Graph Neural Networks for Maximum Constraint Satisfaction.pdf
Published 2021“…Despite being generic, we show that our approach matches or surpasses most greedy and semi-definite programming based algorithms and sometimes even outperforms state-of-the-art heuristics for the specific problems.…”
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