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Fuzzy Approach to Rank Global Climate Models

Raju, Srinivasa K and Kumar, Nagesh D (2015) Fuzzy Approach to Rank Global Climate Models. In: 5th International Conference on Fuzzy and Neuro Computing (FANCCO), DEC 17-19, 2015, Inst Dev & Res Banking Technol, Hyderabad, INDIA, pp. 53-61.

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Official URL: http://dx.doi.org/10.1007/978-3-319-27212-2_5


Eleven coupled model intercomparison project 3 based global climate models are evaluated for the case study of Upper Malaprabha catchment, India for precipitation rate. Correlation coefficient, normalised root mean square deviation, and skill score are considered as performance indicators for evaluation in fuzzy environment and assumed to have equal impact on the global climate models. Fuzzy technique for order preference by similarity to an ideal solution is used to rank global climate models. Top three positions are occupied by MIROC3, GFDL2.1 and GISS with relative closeness of 0.7867, 0.7070, and 0.7068. IPSL-CM4, NCAR-PCMI occupied the tenth and eleventh positions with relative closeness of 0.4959 and 0.4562.

Item Type: Conference Proceedings
Series.: Advances in Intelligent Systems and Computing
Additional Information: Copy right for this article belongs to the SPRINGER-VERLAG BERLIN, HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY
Keywords: Global climate models; India; Rank; Performance indicators; Fuzzy; TOPSIS
Department/Centre: Division of Mechanical Sciences > Civil Engineering
Date Deposited: 29 Feb 2016 06:50
Last Modified: 29 Feb 2016 06:50
URI: http://eprints.iisc.ac.in/id/eprint/53383

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