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1. 1. An evaluation of deep learning models for urban floods forecasting

   University essay from KTH/Geoinformatik

   Author : Yang Mu; [2022]
   Keywords : Urban flooding forecasting; Convolutional neural networks; Deep learning; Physically-based simulation; Recurrent neural network; Stadsöversvämningsprognoser; konvolutionella neurala nätverk; djupinlärning; fysiskt baserad simulering; återkommande neurala nätverk;

   Abstract : Flood forecasting maps are essential for rapid disaster response and risk management, yet the computational complexity of physically-based simulations hinders their application for efficient high-resolution spatial flood forecasting. To address the problems of high computational cost and long prediction time, this thesis proposes to develop deep learning neural networks based on a flood simulation dataset, and explore their potential use for flood prediction without learning hydrological modelling knowledge from scratch. READ MORE