A Machine Learning Framework for Overflow Prediction in Combined Sewer Systems-Reference-Cited by-同舟云学术

A Machine Learning Framework for Overflow Prediction in Combined Sewer Systems

Published:2022-06-02 Issue: Volume: Page:
ISSN:
Container-title:World Environmental and Water Resources Congress 2022
language:
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Author:

Yin Zeda¹²¹²¹,Zahedi Leila¹²¹²¹,Leon Arturo S.¹²¹²¹,Amini M. Hadi¹²¹²¹,Bian Linlong¹²¹²¹

Affiliation:

1. Dept. of Civil and Environmental Engineering, Florida International Univ., Miami, FL.

2. Knight Foundation School of Computing and Information Sciences, Florida International Univ.

Publisher

American Society of Civil Engineers

Link

https://ascelibrary.org/doi/pdf/10.1061/9780784484258.019

Reference30 articles.

1. Evaluating different machine learning methods to simulate runoff from extensive green roofs;Abdalla E. M. H.;Hydrology and Earth System Sciences Discussions,2021

2. Short term rainfall-runoff modelling using several machine learning methods and a conceptual event-based model

3. Combined sewer overflows: A critical review on best practice and innovative solutions to mitigate impacts on environment and human health

4. A novel deep learning neural network approach for predicting flash flood susceptibility: A case study at a high frequency tropical storm area;Bui D. T.;Science of The Total Environment,2020

5. A Survival Analysis Model for Sewer Pipe Structural Deterioration

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