This book delivers an end-to-end, science-driven methodology for next-generation weather forecasting by integrating deep learning methods with physically based climate models. This book proposes a hybrid model incorporating multimodal data fusion, temporal sequence learning, and physics-constrained neural networks to improve forecast accuracy and credibility by a substantial margin.Using ground station, satellite, global reanalysis system, and IoT-based data, the framework resolves the spatial and temporal disconnects plaguing traditional prediction systems.
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book delivers an end-to-end, science-driven methodology for next-generation weather forecasting by integrating deep learning methods with physically based climate models. This book proposes a hybrid model incorporating multimodal data fusion, temporal sequence learning, and physics-constrained neural networks to improve forecast accuracy and credibility by a substantial margin.Using ground station, satellite, global reanalysis system, and IoT-based data, the framework resolves the spatial and temporal disconnects plaguing traditional prediction systems.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 52 pp. Englisch. Seller Inventory # 9786207998210
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Taschenbuch. Condition: Neu. Next-Gen Weather Forecasting: Deep Learning and Data Analysis | A hybrid LSTM and physics-guided framework using multimodal data for accurate weather prediction | Saptarshi Mondal (u. a.) | Taschenbuch | Englisch | 2025 | LAP LAMBERT Academic Publishing | EAN 9786207998210 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. Seller Inventory # 134022232
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