Nowadays, kriging has been accepted as the most common method of grade estimation in mineral resource evaluation stage. Access to the crisp assay data and a variogram model are the necessary means for the utilization of this method. Since fitting a crisp variogram model is generally difficult, if not impossible, the fitted theoretical model is usually tainted with uncertainty due to various rea...

Fuzzy sets have been originally introduced as generalizations of crisp sets, and this is how they are usually considered. From the mathematical viewpoint, the problem with this approach is that most notions allow many different generalizations, so every time we try to generalize some notions to fuzzy sets, we have numerous alternatives. In this paper, we show that fuzzy sets can be alternativel...

A neural fuzzy system learning with linguistic teaching signals is proposed in this paper. This system is able to process and learn numerical information as well as linguistic information. It can be used either as an adaptive fuzzy expert system or as an adaptive fuzzy controller. At first, we propose a fivelayered neural network for the connectionist realization of a fuzzy inference system. Th...

Although crisp data are fundamentally indispensable in the conventional linear programming technique for multidimensional analysis of preference (LINMAP), the observed values in the real-world problems are often imprecise or vague. These imprecise or vague data can be suitably characterized by linguistic terms which are fuzzy in nature. LINMAP has been widely used to solve multi-attribute decis...

The decision data of human judgments with preferences are often vague in many real life cases. Human judgments with preferences are often unclear and hard to estimate by exact numerical values. So that the traditional ways of using crisp values are inadequate. The relationship among criteria and choosing and rating alternatives based on criterion are often expressed in terms of linguistic terms...

in this paper, a novel method for ranking of fuzzy numbers are proposed. in this method, decision maker is defined based on the center of mass at some cuts of a pair of fuzzy numbers in discreet version and center of mass on all of cuts of a pair of fuzzy numbers in continuous version. our method can rank more than two fuzzy numbers simultaneously. also, some properties of methods are described...

Linear programming (LP) is a widely used optimization method for solving real-life problems because of its efficiency. Although precise data are fundamentally indispensable in conventional LP problems, the observed values of the data in real-life problems are often imprecise. Fuzzy sets theory has been extensively used to represent imprecise data in LP by formalizing the inaccuracies inherent i...

Process capability indices (PCIs) can be used as an effective tool for measuring product quality and process performance. In classic quality control there are some limitations which prevent a deep and flexible analysis because of the crisp definition of PCA‟s parameters. Fuzzy set theory can be used to add more flexibility to process capability analyses. In this study, the fuzzy X ba and MRx ba...

When we deal with crisp data, it is very common to find the correlation between variables. Here, we propose a method to calculate the correlation coefficient for fuzzy data, but rather than defining the correlation on the intuitionistic fuzzy sets like most of the previous works, we adopt the method from central interval. This interval can be used as a crisp set approximation with respect to a ...