Subset Modeling Basis ANFIS for Prediction of the Reference Evapotranspiration-Reference-Cited by-同舟云学术

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Subset Modeling Basis ANFIS for Prediction of the Reference Evapotranspiration

Published:2017-11-11 Issue:3 Volume:32 Page:1101-1116
ISSN:0920-4741
Container-title:Water Resources Management
language:en
Short-container-title:Water Resour Manage

Author:

Keshtegar Behrooz,Kisi Ozgur,Ghohani Arab Hamed,Zounemat-Kermani Mohammad

Funder

University of Zabol under

Publisher

Springer Science and Business Media LLC

Subject

Water Science and Technology,Civil and Structural Engineering

Link

http://link.springer.com/article/10.1007/s11269-017-1857-5/fulltext.html

Reference38 articles.

1. Abdullah SS, Malek MA (2016) Empirical Penman-Monteith equation and artificial intelligence techniques in predicting reference evapotranspiration: a review. Int J Water 10(1):55–66. https://doi.org/10.1504/IJW.2016.073741

2. Abdulshahed AM, Longstaff AP, Fletcher S, Myers A (2015) Thermal error modelling of machine tools based on ANFIS with fuzzy c-means clustering using a thermal imaging camera. Appl Math Model 39(7):1837–1852. https://doi.org/10.1016/j.apm.2014.10.016

3. Aghajanloo M-B, Sabziparvar A-A, Talaee PH (2013) Artificial neural network–genetic algorithm for estimation of crop evapotranspiration in a semi-arid region of Iran. Neural Comput & Applic 23(5):1387–1393. https://doi.org/10.1007/s00521-012-1087-y

4. Akkemik Ü, Aras A (2005) Reconstruction (1689–1994 AD) of April–August precipitation in the southern part of central Turkey. Int J Climatol 25(4):537–548. https://doi.org/10.1002/joc.1145

5. Cigizoglu HK, Kisi Ö (2006) Methods to improve the neural network performance in suspended sediment estimation. J Hydrol 317(3-4):221–238. https://doi.org/10.1016/j.jhydrol.2005.05.019

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