MONTHLY LOW-FLOW FORECASTING USING A STOCHASTIC MODEL AND ADAPTIVE NETWORK BASED FUZZY INFERENCE SYSTEM

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KHOLGHI M.; ASHRAFZADEH A.; MAALMIR M.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: IRAN-WATER RESOURCES RESEARCH Year:2009 | Volume:5 | Issue:2 (14) Page(s): 18-19

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Information Journal Paper

Title

MONTHLY LOW-FLOW FORECASTING USING A STOCHASTIC MODEL AND ADAPTIVE NETWORK BASED FUZZY INFERENCE SYSTEM

Author(s)

KHOLGHI M. | ASHRAFZADEH A. | MAALMIR M. | Issue Writer Certificate

Keywords

MONTHLY LOW-FLOW

TIME SERIES MODELING

ARIMA

ANFIS

NAVROOD RIVER BASIN

IRAN

Abstract

Introduction: Water resources systems management is directly influenced by stream flow forecasting. It is therefore necessary to develop appropriate and applicable models for stream flow forecasting, especially in the low-flow context. Both stochastic models and artificial intelligence based models are widely used for simulation and forecasting of hydrologic time series. The literature shows that both models have performed well in different cases (Mishra et al., 2007) and thus it is difficult to know a priori which particular model would be better suited for a given problem.

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APA: Copy

KHOLGHI, M., ASHRAFZADEH, A., & MAALMIR, M.. (2009). MONTHLY LOW-FLOW FORECASTING USING A STOCHASTIC MODEL AND ADAPTIVE NETWORK BASED FUZZY INFERENCE SYSTEM. IRAN-WATER RESOURCES RESEARCH, 5(2 (14)), 18-19. SID. https://sid.ir/paper/582609/en

Vancouver: Copy

KHOLGHI M., ASHRAFZADEH A., MAALMIR M.. MONTHLY LOW-FLOW FORECASTING USING A STOCHASTIC MODEL AND ADAPTIVE NETWORK BASED FUZZY INFERENCE SYSTEM. IRAN-WATER RESOURCES RESEARCH[Internet]. 2009;5(2 (14)):18-19. Available from: https://sid.ir/paper/582609/en

IEEE: Copy

M. KHOLGHI, A. ASHRAFZADEH, and M. MAALMIR, “MONTHLY LOW-FLOW FORECASTING USING A STOCHASTIC MODEL AND ADAPTIVE NETWORK BASED FUZZY INFERENCE SYSTEM,” IRAN-WATER RESOURCES RESEARCH, vol. 5, no. 2 (14), pp. 18–19, 2009, [Online]. Available: https://sid.ir/paper/582609/en

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