A Data-Driven Surrogate Approach for the Temporal Stability Forecasting of Vegetation Covered Dikes

A Data-Driven Surrogate Approach for the Temporal Stability Forecasting of Vegetation Covered Dikes

Climatic conditions and vegetation cover influence water flux in a dike, and potentially the dike stability. A comprehensive numerical simulation is computationally too expensive to be used for the near real-time analysis of a dike network. Therefore, this study investigates a random forest (RF) reg...

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Bibliographic Details
Main Authors: Elahe Jamalinia, Faraz S. Tehrani, Susan C. Steele-Dunne, Philip J. Vardon
Format: Article
Language:English
Published: MDPI AG 2021-01-01
Series:Water
Subjects:
machine learning
random forest
slope stability
numerical simulation
climate
vegetation
Online Access:https://www.mdpi.com/2073-4441/13/1/107

Internet

https://www.mdpi.com/2073-4441/13/1/107

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