Unraveling the complexities of urban fluvial flood hydraulics through AI.

ABSTRACT: As urbanization increases across the globe, urban flooding is an ever-pressing concern. Urban fluvial systems are highly complex, depending on a myriad of interacting variables. Numerous hydraulic models are available for analyzing urban flooding; however, meeting the demand of high spatial extension and finer discretization and solving the physics-based numerical equations are computationally expensive. Computational efforts increase drastically with an increase in model dimension and resolution, preventing current solutions from fully realizing the data revolution. In this research, we demonstrate the effectiveness of artificial intelligence (AI), in particular, machine learning (ML) methods including the emerging deep learning (DL) to quantify urban flooding considering the lower part o

SUBMITTER: Mehedi MAA 

PROVIDER: S-EPMC9636396 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature