A genetic programming technique for lake level modeling | Hydrology Research | IWA Publishing

Skip to Main Content

A genetic programming technique for lake level modeling

Hydrology Research (2014) 45 (4-5): 529–539.

This article has been cited by the following articles in journals that are participating in CrossRef Cited-by Linking.

Generating Monthly Stream Flow Using Nearest River Data: Assessing Different Trees Models

Anas Mahmood Al-Juboori

Water Resources Management (2019) 33 (9): 3257.

Lake Water-Level fluctuations forecasting using Minimax Probability Machine Regression, Relevance Vector Machine, Gaussian Process Regression, and Extreme Learning Machine

Hossein Bonakdari
Isa Ebtehaj
Pijush Samui
Bahram Gharabaghi

Water Resources Management (2019) 33 (11): 3965.

Wavelet-genetic programming conjunction model for flood forecasting in rivers

Mani Kumar
Rajeev Ranjan Sahay

Hydrology Research (2018) 49 (6): 1880.

Explicit prediction of expanding channels hydraulic jump characteristics using gene expression programming approach

Kiyoumars Roushangar
Roghayeh Ghasempour

Hydrology Research (2018) 49 (3): 815.

Improved predictive model to the cross-sectional resistance of CFT

Iman Mansouri
Rolando Chacón
Jong Wan Hu

Journal of Mechanical Science and Technology (2017) 31 (8): 3887.

Hydropower Plant Site Assessment by Integrated Hydrological Modeling, Gene Expression Programming and Visual Basic Programming

Anas Mahmood Al-Juboori
Aytac Guven

Water Resources Management (2016) 30 (7): 2517.

A stepwise model to predict monthly streamflow

Anas Mahmood Al-Juboori
Aytac Guven

Journal of Hydrology (2016) 543: 283.

Lake Level Forecasting Using Wavelet-SVR, Wavelet-ANFIS and Wavelet-ARMA Conjunction Models

Maryam Shafaei
Ozgur Kisi

Water Resources Management (2016) 30 (1): 79.