Evaluation of stochastic and artificial intelligence models in modeling and predicting of river daily flow time series

Author:

Aghelpour PouyaORCID,Varshavian VahidORCID

Publisher

Springer Science and Business Media LLC

Subject

General Environmental Science,Safety, Risk, Reliability and Quality,Water Science and Technology,Environmental Chemistry,Environmental Engineering

Reference46 articles.

1. Abudu S, Cui C, King JP, Abudukadeer K (2010) Comparison of performance of statistical models in forecasting monthly streamflow of Kizil River, China. Water Sci Eng 3(3):269–281

2. Achouri I, Hani I, Bougherira N, Djabri L, Chaffai H, Lallahem S (2015) River flow model using artificial neural networks. Energy Proc 74:1007–1014

3. Aghelpour P, Mohammadi B, Biazar SM (2019) Long-term monthly average temperature forecasting in some climate types of Iran, using the models SARIMA, SVR, and SVR-FA. Theor Appl Climatol 138:1471–1480

4. Alipour Y, Mardoukhpour A, Amiri E, Jamasbi H (2016) Investigation of estimating river suspended sediment using artificial neural network and neuro-fuzzy inference system. In: 1st national conference on civil engineering, new releases, economic development, cultural and tenacious management, Islamic Azad University of Bandar-Anzali, Bandar-Anzali, Iran

5. Araghinejad S (2013) Data-driven modeling: using MATLAB® in water resources and environmental engineering, vol 67. Springer, Berlin

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