Published on 27 January 2024

Interpretable Deep Convolutional Neural Network-based Surrogates for Complex Urban Hydrodynamic Modeling using Random Chaotic Rainfall

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Bo Pang - Hydrology Research Group

Description

This data is part of the article "Interpretable Deep Convolutional Neural Network-based Surrogates for Complex Urban Hydrodynamic Modeling using. Random Chaotic Rainfall "data for model training and validation, as well as a dynamic runoff range generated by DHMUrban

Citations (0)

Mentions (0)

Metrics

Dataset Index

1.5

FAIR Score

69%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

Zenodo

Assigned Domain

Subfield

Global and Planetary Change

Field

Environmental Science

Domain

Physical Sciences

Confidence Score

99%

Source

Open Alex

Normalization Factors

FT

15.38

CTw

1.00

MTw

1.00