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|Created:||Dec 21, 2017 at 5:12 p.m.|
|Last updated:|| Mar 01, 2018 at 10:09 p.m.
|Citation:||See how to cite this resource|
|Content types:||Single File Content|
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This is tabular output data from two data-driven models used to predict flood severity, Poisson regression and Random Forest regression. Both outputs from the training and testing phases of the modeling are included in the resource. Additionally, results indicating the relative importance of each predictor variable in the Random Forest model are provided in the "rf_impo_out.csv" file. This work is described in the following paper published in the Journal of Hydrology: https://doi.org/10.1016/j.jhydrol.2018.01.044.
|The content of this resource was created by a related App or software program||https://www.hydroshare.org/resource/712cd2ce8f604c8f824d6836ee3fcb53/|
|The content of this resource references||https://doi.org/10.1016/j.jhydrol.2018.01.044|
|The content of this resource is derived from||https://www.hydroshare.org/resource/ff8be5aea3224c15b262bfddd5fb6033/|
|Title||Owners||Sharing Status||My Permission|
|Data-driven street flood severity modeling in Norfolk, Virginia USA 2010-2016||Jeff Sadler · Jonathan Goodall||Public & Shareable||Open Access|
This resource was created using funding from the following sources:
|Agency Name||Award Title||Award Number|
|Mid-Atlantic Transportation Sustainability Center|
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.http://creativecommons.org/licenses/by/4.0/