A hybrid SVR-PSO model to predict concentration of sediment in typical and debris floods-Reference-Cited by-同舟云学术

A hybrid SVR-PSO model to predict concentration of sediment in typical and debris floods

Published:2021-01-21 Issue:1 Volume:14 Page:365-376
ISSN:1865-0473
Container-title:Earth Science Informatics
language:en
Short-container-title:Earth Sci Inform

Author:

Kazemi Mahsa Sheikh,Banihabib Mohammad Ebrarim^ORCID,Soltani Jaber

Publisher

Springer Science and Business Media LLC

Subject

General Earth and Planetary Sciences

Link

http://link.springer.com/content/pdf/10.1007/s12145-021-00570-0.pdf

Reference48 articles.

1. Adamowski J (2013) Using support vector regression to predict direct runoff, base flow and total flow in a mountainous watershed with limited data in Uttaranchal, India. Annals of Warsaw University of Life Sciences-SGGW. Land Reclamation 45(1):71–83

2. Banihabib ME, Bahram E (2009) Experimental analyses of sedimentation in the slit dam Reservoir. World Environmental and Water Resources Congress, ASCE, Great Rivers 5845–5856

3. Banihabib ME, Forghani A (2017) An assessment framework for the mitigation effects of check dams on debris flow. Catena 152:277–284

4. Banihabib ME et al (2020) Bayesian networks model for identification of the effective variables in the forecasting of debris flows occurrence. Environ Earth Sci 79:1–15

5. Byun H, Lee S-W (2002) Applications of support vector machines for pattern recognition: a survey. International Workshop on Support Vector Machines, Springer 2388:213–236

Cited by 11 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. H-ADCP-based real-time sediment load monitoring system using support vector regression calibrated by global optimization technique and its applications;Advances in Water Resources;2024-03

2. Study on formation mechanism of mud-inclusion-type underground debris flows using natural caving method;Scientific Reports;2024-02-21

3. Data-driven approaches for estimation of sediment discharge in rivers;Earth Science Informatics;2023-12-22

4. Study on the Effect of Ore-Drawing Shear Factor on Underground Debris Flow in the Block Caving Method;Water;2023-10-12

5. A Novel Efficient Method of Estimating Suspended‐To‐Total Sediment Load Fraction in Natural Rivers;Water Resources Research;2023-10