Recently, the concept of intuitionistic fuzzy parameterized soft matrices (ifpifs-matrices) has allowed to mathematically model some problems in which parameters and alternatives exhibit uncertainties. To this end, present study aims generalise 24 decision-making (SDM) methods operating space with a single fpfs-matrix ifpifs-matrices spaces. Afterwards, we propose five test scenarios analyse wh...

We propose a new MCDM method based on fuzzy pair-wise comparisons and a feedback between the criteria. The evaluation of the weights of criteria, the variants as well as the feedback between the criteria is based on the data given in pair-wise comparison matrices. Extended arithmetic operations with fuzzy numbers are used as well as ordering fuzzy relations to compare fuzzy outcomes. An illustr...

Cost-sensitive classification is based on a set of weights defining the expected cost of misclassifying an object. In this paper, a Genetic Fuzzy Classifier, which is able to extract fuzzy rules from interval or fuzzy valued data, is extended to this type of classification. This extension consists in enclosing the estimation of the expected misclassification risk of a classifier, when assessed ...

In practice, some of information systems are based on dominance relations, and values of decision attribute are fuzzy. So, it is meaningful to study attribute reductions in ordered decision tables with fuzzy decision. In this paper, upper and lower approximation reductions are proposed in this kind of complicated decision table, respectively. Some important properties are discussed. The judgeme...

Starting from a unified treatment of uncertainty by combining probability and fuzzy set theory [1], Goodman [2] put forward the equivalence between a fuzzy set and a class of random sets. Falling shadow representation theory was established based on the collection of Wang and Sanchez [3], which is directly related to the concept of probabilistic fuzzy set membership function. The theory shows t...

In this paper, we proposed the principal component analysis (PCA) fuzzy mixture model for speaker identification. A PCA fuzzy mixture model is derived from the combination of the PCA and the fuzzy version of mixture model with diagonal covariance matrices. In this method, the feature vectors are first transformed by each speaker’s PCA transformation matrix to reduce the correlation among the el...

The non-abelian Dirac-Born-Infeld action is used to construct the D2-brane from multiple D0-branes in the curved spacetimes. After choosing the matrix elements as the coordinates of the D0-branes we obtain a simple formula of the Lagrangian for the system in a class of the curved background. Using the formula we first re-examine the system in the flat spacetime and show that, in addition to the...

This paper presents the stability analysis of the sampled-data fuzzy-model-based control systems. To investigate the system stability, a T-S fuzzy model is employed to represent the nonlinear system. A sampled-data fuzzy controller is employed to close the feedback loop. Due to the sampling activity of the sampled-data fuzzy controller, discontinuity is introduced which complicates the stabilit...

The traditional statistical models assume the covariance matrices for two populations are identical and both populations need to be described by multivariate normal distribution. Clearly, these assumptions do not always reflect the real world. Rough set is a new technique for data mining domain application. In this study, establish a financial distress Classification model using Fuzzy Nearest–N...

An approach to the diagnostic type expert systems design based on the special matrix representation of fuzzy predicates in the attribute model of the problem domain is presented. Intensive representation of predicates by means of sectional matrices is an analogue of the conjunctive normal form. Rules, positive examples and negative examples (in general, all fuzzy) can be used to form knowledge ...