A fuzzy lagrange interpolation theorem
Fuzzy Sets and Systems
Fuzzy Sets and Systems
Aggregation of fuzzy opinions under group decision making
Fuzzy Sets and Systems
Fuzzy set theory: foundations and applications
Fuzzy set theory: foundations and applications
Modeling uncertain data with fuzzy B-splines
Fuzzy Sets and Systems
Fuzzy risk analysis based on similarity measures of generalized fuzzy numbers
IEEE Transactions on Fuzzy Systems
A fuzzy rule-based approach for screening international distribution centres
Computers & Mathematics with Applications
Fuzzy spline interpolation with optimal property in parametric form
Information Sciences: an International Journal
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In this article, new error and similarity indexes to determine the accuracy of interpolation of fuzzy data by cubic spline functions are presented. The measures introduced are based on the similarity measure of fuzzy numbers. Through experimental simulations with different examples, we verify the homogeneity of the error and similarity indexes, which provides a criterion for determining the accuracy of the interpolation method with fuzzy data. The development of a criterion or an error or similarity index represents an important advancement, because of the lack of qualitative measures to estimate the interpolation error using fuzzy numbers in order to compare the results from distinct fuzzy data sets.