Fuzzy sets, uncertainty, and information
Fuzzy sets, uncertainty, and information
Weighted fuzzy averages in fuzzy environment: part I. Insufficient expert data and fuzzy averages
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Generalized weighted fuzzy expected values in uncertainty environment
AIKED'10 Proceedings of the 9th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases
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In this paper authors propose a method of evaluation of performance of some climate model simulation based on input linguistic variables defined on different statistical metrics, fuzzy terms of which measure how well this simulations performed in past. The output of compositional method (constructed in the paper) is the evaluation of simulation by the linguistic variable, showing how "applicable" this simulation is to predict future climate. Constructed method presents a special composition of concatenated input terms and the terms of output one by the possibilistic transition fuzzy relation. This fuzzy relation was created on the basis of expert knowledge reflections. The proposed approach is illustrated for evaluation of performances of two different simulations performed by PRECIS Regional Climate Model (RCM) for two different Global Climate Models (GCM) - ECHAM4 form Max-Planck Institute, Germany and HadCM3 from Hadley Centre, UK over Dedoplistskaro region in Georgia.