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Combining artificial and human intelligence to improve mountain flood prediction: Code


Authors: Purshottam Shivraj · Christina Bandaragoda
Owners: Christina Bandaragoda · Purshottam Shivraj
Resource type:Composite Resource
Created:Jan 09, 2018 at 8:46 p.m.
Last updated: May 14, 2018 at 12:04 a.m. by Purshottam Shivraj

Abstract

Testing ogh and pyDHSVM for the Sauk Watershed.

Subject Keywords

wrf,eScience winter incubator 2018,scikit,decision tree,dhsvm,spotpy,fast,ogh,dream

How to cite

Shivraj, P., C. Bandaragoda (2018). Combining artificial and human intelligence to improve mountain flood prediction: Code, HydroShare, http://www.hydroshare.org/resource/7c3416535ab24d4f93b0b94741bb9572

This resource is shared under the Creative Commons Attribution CC BY.

 http://creativecommons.org/licenses/by/4.0/
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    Content

    Download All Content as Zipped BagIt Archive
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    Authors

    The people or organizations that created the intellectual content of the resource.

    Name Organization Address Phone Author Identifiers
    Purshottam Shivraj University of Washington
    Christina Bandaragoda University of Washington

    Contributors

    People or organizations that contributed technically, materially, financially, or provided general support for the creation of the resource's content but are not considered authors.

    Name Organization Address Phone Author Identifiers
    Amanda Lehr University of Washington

    Credits

    This resource was created using funding from the following sources:
    Agency Name Award Title Award Number
    University of Washington eScience Institute Winter Incubator 2018
    National Science Foundation PREEVENTS TRACK 2: Integrated Modeling of Hydro-Geomorphic Hazards: Floods, Landslides and Sediment 1663859
    Sauk Suiattle Indian Tribe
    Bureau of Indian Affairs

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