AI-Driven Hydroinformatics for Physical Hydraulic Modeling and Climate Change Impact Assessment
DOI:
https://doi.org/10.48047/ye6bcs57Keywords:
Artificial Intelligence, Hydroinformatics, Physical Hydraulic Modeling, Real-Time Hydrologic Operations, Climate Change Impact, Process-Based Models, Machine Learning,Abstract
This study provides an original investigation into artificial intelligence (AI)-driven hydroinformatics for physical hydraulic modeling in real-time and conventional hydrologic operations and climate change impact assessments. The blurred line between process-based models and machine learning (ML) models is exemplified by advanced hydraulic simulations for barotrauma.
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References
Ravi Kumar Vankayalapati, Dilip Valiki, Venkata Krishna Azith Teja Ganti (2025) Zero-Trust Security Models for Cloud Data Analytics: Enhancing Privacy in Distributed Systems . Journal of Artificial Intelligence & Cloud Computing. SRC/JAICC-436. DOI: doi.org/10.47363/JAICC/2025(4)415
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