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Titlebook: Computational Science – ICCS 2024; 24th International C Leonardo Franco,Clélia de Mulatier,Peter M. A. Slo Conference proceedings 2024 The

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31#
發(fā)表于 2025-3-26 21:14:26 | 只看該作者
32#
發(fā)表于 2025-3-27 03:40:43 | 只看該作者
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發(fā)表于 2025-3-27 06:10:23 | 只看該作者
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35#
發(fā)表于 2025-3-27 16:08:57 | 只看該作者
36#
發(fā)表于 2025-3-27 19:29:28 | 只看該作者
XLTU: A Cross-Lingual Model in?Temporal Expression Extraction for?Uyghure XLTU with different models on our dataset, and the results demonstrate that our model XLTU achieves the SOTA results on various evaluation metrics. We make our code and dataset publicly available (.).
37#
發(fā)表于 2025-3-27 23:53:00 | 只看該作者
Modeling Tsunami Waves at?the?Coastline of?Valparaiso Area of?Chile with?Physics Informed Neural Neted by graph transformation rules to generate a sequence of triangular computational meshes approximating the seabed and seashore of the Valparaiso area based on the Global Multi-Resolution Topography Data available. For the training of the PINN, we employ points from the vertices of the generated triangular mesh.
38#
發(fā)表于 2025-3-28 04:26:53 | 只看該作者
Stacking for?Probabilistic Short-Term Load Forecastingeta-model is trained using patterns most similar to the query pattern. Through extensive experimental studies across 35 forecasting scenarios and employing 16 base forecasting models, our findings underscored the superiority of quantile regression forest over its competitors.
39#
發(fā)表于 2025-3-28 09:42:27 | 只看該作者
Cascade Training as?a?Tree Search with?Dijkstra’s Algorithmut information, respectively. We experiment with different tree sizes and different branching factors. Results confirm that training times of obtained cascades, especially for large heavily branched trees, were reduced. For small trees, the previous technique can sometimes achieve better results but the difference is negligible in most cases.
40#
發(fā)表于 2025-3-28 12:25:56 | 只看該作者
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