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Water Resources Management

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01-04-2012

River Flow Estimation and Forecasting by Using Two Different Adaptive Neuro-Fuzzy Approaches

Authors: Hadi Sanikhani, Ozgur Kisi

Published in: Water Resources Management | Issue 6/2012

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Abstract

This paper demonstrates the application of two different adaptive neuro-fuzzy (ANFIS) techniques for the estimation of monthly streamflows. In the first part of the study, two different ANFIS models, namely ANFIS with grid partition (ANFIS-GP) and ANFIS with sub clustering (ANFIS-SC), were used in one-month ahead streamflow forecasting and the results were evaluated. Monthly flow data from two stations, the Besiri Station on the Garzan Stream and the Baykan Station on the Bitlis Stream in the Firat-Dicle Basin of Turkey were used in the study. The effect of periodicity on the model’s forecasting performance was also investigated. In the second part of the study, the performance of the ANFIS techniques was tested for streamflow estimation using data from the nearby river. The results indicated that the performance of the ANFIS-SC model was slightly better than the ANFIS-GP model in streamflow forecasting.

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Title: River Flow Estimation and Forecasting by Using Two Different Adaptive Neuro-Fuzzy Approaches
Authors: Hadi Sanikhani
Ozgur Kisi
Publication date: 01-04-2012
Publisher: Springer Netherlands
Published in: Water Resources Management / Issue 6/2012
Print ISSN: 0920-4741
Electronic ISSN: 1573-1650
DOI: https://doi.org/10.1007/s11269-012-9982-7

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