Hybrid nonlinear probabilistic model using Monte Carlo simulation and hybrid support vector regression for evaporation predictions-Reference-Cited by-同舟云学术

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Hybrid nonlinear probabilistic model using Monte Carlo simulation and hybrid support vector regression for evaporation predictions

Published:2024-09-11 Issue: Volume: Page:
ISSN:0262-6667
Container-title:Hydrological Sciences Journal
language:en
Short-container-title:Hydrological Sciences Journal

Author:

Piri Jamshid¹,Kisi Ozgur²³

Affiliation:

1. Department of Water Engineering, Faculty of Soil & Water, University of Zabol, P.O. Box: 98615-538, Zabol, Iran

2. Department of Civil Engineering, Lubeck University of Applied Sciences, 23562, Lübeck, Germany

3. Department of Civil Engineering, Ilia State University, 0162, Tbilisi, Georgia

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/02626667.2024.2403718

Reference35 articles.

1. Ali S. Ghosh N. C. and Singh R. (2008) Evaluating best evaporation estimate model for water surface evaporation in semi‐arid region India. Hydrological Processes: An International Journal 22 (8) 1093-1106.

2. Amasyali K. and El-Gohary N. M. (2018) A review of data-driven building energy consumption prediction studies. Renewable and Sustainable Energy Reviews 81 1192-1205.

3. Atangana A. and Araz S. I. (2021) Deterministic-Stochastic modeling: A new direction in modeling real world problems with crossover effect.

4. Baig F. Ali L. Abrar M. Chen H. and Sherif M. (2024) How accurate are the machine learning models in improving monthly rainfall prediction in hyper arid environment? Journal of Hydrology 131040.

5. Bokil V. A. and Allen L. (2012) Stochastic models for competing species with a shared pathogen. Mathematical Biosciences and Engineering 9 (3) 461.

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