Improvement of Best First Decision Trees Using Bagging and Dagging Ensembles for Flood Probability Mapping

Development of zoning and flood-forecasting models is essential for making optimal management decisions before and after floods. The Komijan watershed of Markazi Province, Iran is often affected by floods that have caused great material damage and loss of life. The main objective of this study is to...

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Veröffentlicht in:	Water resources management 2020-07, Vol.34 (9), p.3037-3053
Hauptverfasser:	Yariyan, Peyman, Janizadeh, Saeid, Van Phong, Tran, Nguyen, Huu Duy, Costache, Romulus, Van Le, Hiep, Pham, Binh Thai, Pradhan, Biswajeet, Tiefenbacher, John P.
Format:	Artikel
Sprache:	eng
Schlagworte:	Atmospheric Sciences Bagging Civil Engineering Decision making Decision trees Earth and Environmental Science Earth Sciences Environment Flood damage Flood forecasting Flood management Flood mapping Flood predictions Flooding Floods Geotechnical Engineering & Applied Earth Sciences Hydrogeology Hydrology/Water Resources Information management Learning algorithms Machine learning Management decisions Mapping Probability theory Risk management Root-mean-square errors Sea surface Soil Specificity Surface temperature Watersheds
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