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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Saptarshi Mondal, B.Tech CSE (AIML) 3rd year student at Adamas University, has published a Springer paper on AI for disabled assistance. Rupsha Roy, B.Sc (Hons) Agriculture 3rd year student at Adamas University, focuses on climate-resilient farming. Both collaborate on AI-driven weather forecasting research.
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Taschenbuch. Zustand: 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: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. Bestandsnummer des Verkäufers 134022232
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