Prediction of daily reference evapotranspiration with M5P, Gaussian process regression and Support vector regression methods

Articles in Press, Accepted Manuscript, Available Online from 22 September 2024

10.22034/ws.2024.58879.2541

Saeed Samadianfard; Zahra Rousta; Milad Sharafi

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Estimation of Daily Evaporation from Class A Pan using Five Data Mining Methods (Case Study: Tabriz Synoptic Station)

Volume 33, Issue 4, December 2023, Pages 167-184

10.22034/ws.2021.48668.2447

Khadigeh Seifzadeh; davoud ZAREHAGHI; Saeed Samadianfard; Mohammad Reza Neyshabouri; Fatemeh Mikaeili

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Modeling and Determination of Effective Parameters in Flow Roughness Coefficient in Alluvial Channels with Dun Bedforms Using Support Vector Regression

Volume 28, Issue 2, May 2018, Pages 235-248

K Roushangar; MT Alami; S.M Saghebian

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Modeling Crump Weir Discharge Coefficient Using Machine Learning Methods

Volume 26, Issue 4.2, March 2017, Pages 1-12

MT Sattari; F Salmasi2; A Hajimohammadi

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Estimating Free and Submerged Hydraulic Jump’s Length in Horizontal and Slopping Channels Using Support Vector Regression

Volume 26, 3-2, December 2016, Pages 51-62

K Roshanghar; F Homayounfar

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Baranduz-Chay River Flow Modeling Using the K-Nearest Neighbor and Intelligent Methods

Volume 25, Issue 1, May 2015, Pages 219-233

H Sanikhani; y Dinpashoh; MA Ghorbani

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