Estimating Particle Froude Number of Sewer Pipes by Boosting Machine-Learning Models-Reference-Cited by-同舟云学术

Estimating Particle Froude Number of Sewer Pipes by Boosting Machine-Learning Models

Published:2022-05 Issue:2 Volume:13 Page:
ISSN:1949-1190
Container-title:Journal of Pipeline Systems Engineering and Practice
language:en
Short-container-title:J. Pipeline Syst. Eng. Pract.

Author:

Shakya Deepti¹^ORCID,Agarwal Mayank²,Deshpande Vishal³^ORCID,Kumar Bimlesh⁴^ORCID

Affiliation:

1. Research Scholar, Dept. of Computer Science and Engineering, Indian Institute of Technology, Patna, Bihar 801103, India. ORCID: .

2. Assistant Professor, Dept. of Computer Science and Engineering, Indian Institute of Technology, Patna, Bihar 801103, India.

3. Assistant Professor, Dept. of Civil and Environmental Engineering, Indian Institute of Technology, Patna, Bihar 801103, India. ORCID: .

4. Professor, Dept. of Civil and Environmental Engineering, Indian Institute of Technology, Guwahati, Assam 781039, India (corresponding author). ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Mechanical Engineering,Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29PS.1949-1204.0000643

Reference29 articles.

1. Ab Ghani A. A. 1993. “Sediment transport in sewers.” Ph.D. thesis Dept. of Civil Engineering Newcastle Univ.

2. Ackers, J., D. Butler, and R. May. 1996. Design of sewers to control sediment problems. London: Construction Industry Research and Information Association.

3. Particle Densimetric Froude Number for Estimating Sediment Transport

4. Alvarez-Hernandez E. M. 1990. “The influence of cohesion on sediment movement in channels of circular cross-section.” Ph.D. thesis Dept. of Civil Engineering Newcastle Univ.

5. ANFIS-based approach for predicting sediment transport in clean sewer

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