This is stars and forks stats for /SRKabir/Rapid_FloodModelling_CNN repository. As of 28 Mar, 2024 this repository has 21 stars and 14 forks.
This is an implementation of Convolutional Neural Network-based rapid fluvial flood modelling system. This implemention trains on the outputs of a 2D hydraulic model (LISFLOOD-FP). LSIFLOOD-FP is a Bristol University software for inundaiton modelling and can be used freely for research purposes. To acquire this software please consult http://www.bristol.ac.uk/geography/research/hydrology/models/lisflood/ Once you have the software, you would need to execute it for different boundary conditions. The...
This is an implementation of Convolutional Neural Network-based rapid fluvial flood modelling system. This implemention trains on the outputs of a 2D hydraulic model (LISFLOOD-FP). LSIFLOOD-FP is a Bristol University software for inundaiton modelling and can be used freely for research purposes. To acquire this software please consult http://www.bristol.ac.uk/geography/research/hydrology/models/lisflood/ Once you have the software, you would need to execute it for different boundary conditions. The...
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