This repository contains the source code and datasets for "FIDLAR: Forecast-Informed Deep Learning Architecture for Flood Mitigation".
data
folder includes data sets usedbaseline
folder includes baseline models usedmodel
folder includes our proposed modelsloss
folder includes loss functions usedpreprocess
folder includes data pre-processingpostprocess
folder includes the programs for experiment results, visualization, and ablation studytraining_WaLeF_models
folder includes training programs for Flood Evaluator
with all modelstraining_optimization_models
folder includes training programs for Flood Manager
with frozen Flood Evaluator
conda create -n env_name python=3.8
conda activate env_name
pip3 install -r requirements.txt
Flood Evaluator
, go to the training_WaLeF_models
folder and run cells in the ipynb
filesFlood Manager
, go to the training_optimization_models
folder and run cells in the ipynb
filespostprocess
folder and run cells in the ipynb
files.