بدائل البحث:
simulation algorithm » segmentation algorithm (توسيع البحث), maximization algorithm (توسيع البحث), selection algorithm (توسيع البحث)
process simulation » process optimization (توسيع البحث)
whale optimization » swarm optimization (توسيع البحث)
image process » damage process (توسيع البحث), image processing (توسيع البحث), simple process (توسيع البحث)
binary 2 » binary _ (توسيع البحث), binary b (توسيع البحث)
2 whale » _ whale (توسيع البحث), a whale (توسيع البحث)
simulation algorithm » segmentation algorithm (توسيع البحث), maximization algorithm (توسيع البحث), selection algorithm (توسيع البحث)
process simulation » process optimization (توسيع البحث)
whale optimization » swarm optimization (توسيع البحث)
image process » damage process (توسيع البحث), image processing (توسيع البحث), simple process (توسيع البحث)
binary 2 » binary _ (توسيع البحث), binary b (توسيع البحث)
2 whale » _ whale (توسيع البحث), a whale (توسيع البحث)
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Hyperparameters of the LSTM Model.
منشور في 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.
منشور في 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.
منشور في 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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Thesis-RAMIS-Figs_Slides
منشور في 2024"…Importantly, this strategy locates samples adaptively on the transition between facies which improves the performance of conventional \emph{<i>MPS</i>} algorithms. In conclusion, this work shows that preferential sampling can contribute in \emph{<i>MPS</i>} even at very small sampling regimes and, as a corollary, demonstrates that prior models (obtained form a training image) can be used effectively not only to simulate non-sensed variables of the field, but to decide where to measure next.…"