A Data-Driven Surrogate Modelling Approach for Acceleration of Short-Term Simulations of a Dynamic Urban Drainage Simulator

A Data-Driven Surrogate Modelling Approach for Acceleration of Short-Term Simulations of a Dynamic Urban Drainage Simulator

In this study, applicability of a data-driven Gaussian Process Emulator (GPE) technique to develop a dynamic surrogate model for a computationally expensive urban drainage simulator is investigated. Considering rainfall time series as the main driving force is a challenge in this regard due to the h...

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Bibliographic Details
Main Authors: Mahmood Mahmoodian, Jairo Arturo Torres-Matallana, Ulrich Leopold, Georges Schutz, Francois H. L. R. Clemens
Format: Article
Language:English
Published: MDPI AG 2018-12-01
Series:Water
Subjects:
surrogate model
data-driven
Gaussian process
emulator
urban drainage
Online Access:https://www.mdpi.com/2073-4441/10/12/1849

Internet

https://www.mdpi.com/2073-4441/10/12/1849

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