Enhancing streamflow forecasting using the augmenting ensemble procedure coupled machine learning models: case study of Aswan High Dam-Reference-Cited by-同舟云学术

Enhancing streamflow forecasting using the augmenting ensemble procedure coupled machine learning models: case study of Aswan High Dam

Published:2019-09-23 Issue:13 Volume:64 Page:1629-1646
ISSN:0262-6667
Container-title:Hydrological Sciences Journal
language:en
Short-container-title:Hydrological Sciences Journal

Author:

Rezaie-Balf Mohammad¹,Naganna Sujay Raghavendra²^ORCID,Kisi Ozgur³,El-Shafie Ahmed⁴^ORCID

Affiliation:

1. Department of Civil Engineering, Graduate University of Advanced Technology-Kerman, Kerman, Iran

2. Department of Civil Engineering, Shri Madhwa Vadiraja Institute of Technology and Management, Bantakal, Udupi. Affiliated to: Visvesvaraya Technological University, Belagavi, India

3. School of Technology, Ilia State University, Tbilisi, Georgia

4. Civil Engineering Department, Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia

Publisher

Informa UK Limited

Subject

Water Science and Technology

Link

https://www.tandfonline.com/doi/pdf/10.1080/02626667.2019.1661417

Reference50 articles.

1. Neural networks and M5 model trees in modelling water level–discharge relationship

2. Monthly Streamflow Forecasting Using EEMD-Lasso-DBN Method Based on Multi-Scale Predictors Selection

3. Numerical Modeling of River Flow for Ecohydraulic Applications: Some Experiences with Velocity Characterization in Field and Simulated Data

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