Bayes_Opt-SWMM: A Gaussian process-based Bayesian optimization tool for real-time flood modeling with SWMM-Reference-Cited by-同舟云学术

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Bayes_Opt-SWMM: A Gaussian process-based Bayesian optimization tool for real-time flood modeling with SWMM

Published:2024-08 Issue: Volume:179 Page:106122
ISSN:1364-8152
Container-title:Environmental Modelling & Software
language:en
Short-container-title:Environmental Modelling & Software

Author:

Tanim Ahad Hasan,Smith-Lewis Corinne,Downey Austin R.J.,Imran Jasim,Goharian Erfan^ORCID

Funder

Office of the Vice President for Research and Partnerships

U.S. Department of Energy

UT-Battelle

Publisher

Elsevier BV

Reference47 articles.

1. Alamdari, N., 2016. Development of a robust automated tool for calibrating a SWMM watershed model. In: World Environmental and Water Resources Congress 2016. pp. 221–228.

2. Global sensitivity analysis in hydrodynamic modeling and flood inundation mapping;Alipour;Environ. Model. Softw.,2022

3. A review of parallel computing applications in calibrating watershed hydrologic models;Asgari;Environ. Model. Softw.,2022

4. Automatic calibration of the US EPA SWMM model for a large urban catchment;Barco;J. Hydraul. Eng.,2008

5. A comprehensive distributed hydrological modeling intercomparison to support process representation and data collection strategies;Baroni;Water Resour. Res.,2019

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Chaak: Urban Hydrological Impact modeling;SoftwareX;2024-09

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