Fast Prediction of Urban Flooding Water Depth Based on CNN−LSTM
Fast Prediction of Urban Flooding Water Depth Based on CNN−LSTM
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Publisher
Basel: MDPI AG
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Language
English
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Publisher
Basel: MDPI AG
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Contents
Rapid prediction of urban flooding is an important measure to reduce the risk of flooding and to protect people’s property. In order to meet the needs of emergency flood control, this paper constructs a rapid urban flood prediction model based on a machine learning approach. Using the simulation results of the hydrodynamic model as the data driver,...
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Full title
Fast Prediction of Urban Flooding Water Depth Based on CNN−LSTM
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TN_cdi_proquest_miscellaneous_3153191483
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_3153191483
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ISSN
2073-4441
E-ISSN
2073-4441
DOI
10.3390/w15071397
