The Fuzzy transform is applied mainly to 1-D signals and 2-D data organized as a regular grid (e.g., images), thus, limiting its potential application arbitrary in terms of dimensionality structure. This article defines analyzes the properties data-driven F-transform, with focus on construction class membership functions, which are multiscale, local, linearly independent, intrinsic, robust disc...

In this paper, a new set of spline functions called ``Flat End Fuzzy Spline" is defined to interpolate given fuzzy data. Some important theorems on these splines together with their existence and uniqueness properties are discussed. Then numerical examples are presented to illustrate the differences between of using our spline and other interpolations that have been studied before.

abstract— in this paper, a new extended method of multi criteria decision making based on fuzzy-topsis theory is introduced. fuzzy mcdm algorithm for determining the best choice among all possible choices when the data are fuzzy is also presented. using a new index leads to procedure for choosing fuzzy ideal and negative ideal solutions directly from the fuzzy data observed alternatives.in this...

this study is an investigation of fuzzy linear regression model for crisp/fuzzy input and fuzzy output data. a least absolutes deviations approach to construct such a model is developed by introducing and applying a new metric on the space of fuzzy numbers. the proposed approach, which can deal with both symmetric and non-symmetric fuzzy observations, is compared with several existing models by...

The fuzzy c-means clustering algorithm is a useful tool for clustering; but it is convenient only for crisp complete data. In this article, an enhancement of the algorithm is proposed which is suitable for clustering trapezoidal fuzzy data. A linear ranking function is used to define a distance for trapezoidal fuzzy data. Then, as an application, a method based on the proposed algorithm is pres...

The classification of fuzzy uncertain data is considered one of the most challenging issues in data analysis. In spite of the significance of fuzzy data in mathematical programming, the development of the analytical methods of fuzzy data is slow. Therefore, the current study proposes a new fuzzy data classification method based on fuzzy data envelopment analysis (DEA) which can handle strea...

background and objectives: evaluating the performance of clinical units is critical for effective managementof health settings. certain assessment of clinical variables for performance analysis is not always possible,calling for use of uncertainty theory. this study aimed to develop and evaluate an integrated independentcomponent analysis-fuzzy-data envelopment analysis approach to accurate the...