Prediction of Bed-Load Sediment Using Newly Developed Support-Vector Machine Techniques-Reference-Cited by-同舟云学术

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Prediction of Bed-Load Sediment Using Newly Developed Support-Vector Machine Techniques

Published:2022-10 Issue:10 Volume:148 Page:
ISSN:0733-9437
Container-title:Journal of Irrigation and Drainage Engineering
language:en
Short-container-title:J. Irrig. Drain Eng.

Author:

Samantaray Sandeep¹^ORCID,Sahoo Abinash¹^ORCID,Paul Siddhartha²^ORCID,Ghose Dillip K.³

Affiliation:

1. Ph.D. Research Scholar, Dept. of Civil Engineering, National Institute of Technology, Silchar, Assam 788010, India. ORCID:

2. Junior Research Fellow, Dept. of Civil Engineering, National Institute of Technology, Silchar, Assam 788010, India. ORCID:

3. Assistant Professor, Dept. of Civil Engineering, National Institute of Technology, Silchar, Assam 788010, India (corresponding author).

Publisher

American Society of Civil Engineers (ASCE)

Subject

Agricultural and Biological Sciences (miscellaneous),Water Science and Technology,Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29IR.1943-4774.0001689

Reference93 articles.

1. Rainfall simulator for field runoff studies

2. Prediction of Suspended Sediment Load Using Data-Driven Models

3. Multivariate Drought Forecasting in Short- and Long-Term Horizons Using MSPI and Data-Driven Approaches

4. Agnihotri A. A. Sahoo and M. K. Diwakar. 2022. “Flood prediction using hybrid ANFIS-ACO model: A case study.” In Proc. Inventive computation and information technologies: Proceedings of ICICIT 2021 169. Singapore: Springer.

5. A rainfall simulator for laboratory-scale assessment of rainfall-runoff-sediment transport processes over a two-dimensional flume

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