Methods for ordering fuzzy numbers play an important role as decision criteria, with applications in areas such as optimization and data mining, among others. Although there are several proposals for ordering methods in the fuzzy literature, many of them are difficult to apply and present some problems with ranking computation. For that reason, this work proposes an ordering method for fuzzy nu...

In this work we address the data reduction problem for fuzzy data. In particular, following a possibilistic approach, several component models for handling twoand three-way fuzzy data sets are introduced. The two-way models are based on classical Principal Component Analysis (PCA), whereas the three-way ones on threeway generalizations of PCA, as Tucker3 and CANDECOMP/PARAFAC. The hereproposed ...

Many variants of fuzzy c-means (FCM) clustering method are applied to crisp numbers but only a few of them are extended to non-crisp numbers, mainly due to the fact that the latter needs complicated equations and exhausting calculations. Vector form of fuzzy c-means (VFCM), proposed in this paper, simplifies the FCM clustering method applying to non-crisp (symbolic interval and fuzzy) numbers. ...

in the mathematical analysis, there are some theorems and definitions that established for both real and fuzzy numbers. in this study, we try to prove  bernoulli's inequality in fuzzy real numbers with some of its applications. also, we prove two other theorems in fuzzy real numbers which are proved before, for real numbers.

fuzzy measures are suitable in analyzing human subjective evaluation processes. several different strategies have been proposed for distance of fuzzy numbers. the distances introduced for fuzzy numbers can be categorized in two groups:1. the crisp distances which explain crisp values for the distance between two fuzzy numbers.2. the fuzzy distance which introduce a fuzzy distance for normal fuz...

The conventional fuzzy c-spherical shells (FCSS) clustering model is extended to cluster involving non-crisp numbers, in this paper. This achieved by a vectorized representation of distance, between two numbers like the crisp case. Using proposed method, named vector (VFCSS), all and can be clustered FCSS algorithm unique structure. Therefore, we implement over various types structure with only...

BACKGROUND Low-Risk Human Papillomavirus (LR-HPV) genotypes 6 and 11 cause genital warts. This study investigated the association of LR-HPV infection with male circumcision (MC). METHODS We used data from the South African MC trial conducted among young men. Urethral swabs, collected among intervention (circumcised) and control (uncircumcised) groups, were analyzed using HPV linear array. Adj...

The problem of generating a superresolution (SR) image from a single low-resolution (LR) input image is addressed via granular computing clustering in the paper. Firstly, and the training images are regarded as SR image and partitioned into some SR patches, which are resized into LS patches, the training set is composed of the SR patches and the corresponding LR patches. Secondly, the granular ...

We consider a reduced model of four-dimensional Yang-Mills theory with a mass term. This matrix model has two classical solutions, two-dimensional fuzzy sphere and two-dimensional fuzzy torus. These classical solutions are constructed by embedding them into three or four dimensional flat space. They exist for finite size matrices, that is, the number of the quantum on these manifolds is finite....

Super-resolution (SR) is a technique that produces a high resolution (HR) image via employing a number of low resolution (LR) images from the same scene. One of the degradations that attenuates performance of the SR is the blurriness of the input LR images. In many previous works in the SR, the blurriness of the LR images is assumed to be due to the integral effect of the image sensor of the im...