This paper provides a general overview about the use of fuzzy inference systems in the important field of river flow forecasting. It discusses the overall operation of the main two types of fuzzy inference systems, namely Mamdani and Takagi–Sugeno–Kang fuzzy inference systems, and the critical issues related to their application. A literature review of existing studies dealing with the use of fuzzy inference systems in river flow forecasting models is presented, followed by some recommendations for future research areas. This review shows that fuzzy inference systems can be used as effective tools for river flow forecasting, even though their application is rather limited in comparison to the popularity of neural networks models. In addition to this, it was found that there are several unresolved issues requiring further attention before more clear guidelines for the application of fuzzy inference systems can be given.
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Research Article|
July 01 2009
Review of the application of fuzzy inference systems in river flow forecasting
Alexandra P. Jacquin;
Alexandra P. Jacquin
1Facultdad de Ingeniería, Pontificia, Universidad Catoólica de Valparaíso, Av. Brasil 2147, Valparaíso, Chile and Departamento de Obras Civiles, Universidad Técnica Federico Santa María, Casilla 110-V, Valparaíso, Chile
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Asaad Y. Shamseldin
2Department of Civil and Environmental Engineering, University of Auckland, Private Bag 92019, Auckland, New Zealand
Tel.: +64 9 373 7599X88499 Fax: +64 9 373 7462; E-mail: [email protected]
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Journal of Hydroinformatics (2009) 11 (3-4): 202–210.
Article history
Received:
May 01 2008
Accepted:
March 23 2009
Citation
Alexandra P. Jacquin, Asaad Y. Shamseldin; Review of the application of fuzzy inference systems in river flow forecasting. Journal of Hydroinformatics 1 July 2009; 11 (3-4): 202–210. doi: https://doi.org/10.2166/hydro.2009.038
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