Urban flood forecasting with multi-output neural networks: a physically-based and data-driven approach

Urban flood forecasting with multi-output neural networks: a physically-based and data-driven approach

ABSTRACT Physically based models for spatial flood prediction are time and computationally expensive. Data-driven models, while faster, require large amounts of data for adjustment. This study presents an original methodology combining these two approaches, using a physically-based model (HEC-RAS 2D...

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Bibliographic Details
Main Authors: Renata Bulling Magro, Olavo Correa Pedrollo, Silvio Luis Rafaeli Neto
Format: Article
Language:English
Published: Associação Brasileira de Recursos Hídricos 2025-05-01
Series:Revista Brasileira de Recursos Hídricos
Subjects:
Urban flooding
Hydrodynamic modeling
Computational intelligence
Forecasting model
Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S2318-03312025000100216&lng=en&tlng=en
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