We present an approach to learn fuzzy binary decision rules from ordinal temporal data where the task is to classify every instance at each point in time. We assume that one class is preferred to the other, e.g. the undesirable class must not be misclassified. Hence it is appealing to use the Variable Consistency Dominance-based Rough Set Approach (VC-DRSA) to exploit preference information abo...

We investigated analytical structure of the Takagi–Sugeno (TS) type of fuzzy controllers, which was unavailable in the literature. The TS fuzzy controllers we studied employ a new and simplified TS control rule scheme in which all the rule consequent use a common function and are proportional to one another, greatly reducing the number of parameters needed in the rules. Other components of the ...

Enhanced fuzzy modeling by multivariable fuzzy membership functions is described. From the interpretability issues viewpoint conventionally fuzzy modeling is carried out by means of decomposition of multivariable membership functions via projections on each variable component. However, due to decomposition there involves an error while reconstructing the model output from the contributions of e...

In 1982, Dubois and Prade [4, 5] first introduced the concept of integration of fuzzy functions. Kaleva [7] studied the measurability and integrability for the fuzzy set-valued mappings of a real variable whose values are normal, convex, upper semicontinuous, and compactly supported by fuzzy sets in Rn. Existence of solutions of fuzzy integral equations has been studied by several authors [1, 2...

Temperature is a universe and significant data in production and scientific experiment, effective measurement and control of the temperature are widely applied in every part of national economy. Therefore, temperature control has great significance; relevant requirements regarding temperature control are also higher and higher. Temperature command system for animal house is a complex system wit...

This research proposes an automatic dental radiograph image recognition using fuzzy approach for disaster victim identification. Moreover, a new method using fuzzy inference system to determine an optimal degree of Zernike moment in the system is also proposed. Correlation coefficient and Euclidean distance are used as input variables for fuzzy set. The difference between the correlation coeffi...

A fuzzy variable is a function from a possibility space to the set of real numbers, while a bifuzzy variable is a function from a possibility space to the set of fuzzy variables. In this paper, a concept of chance distribution is originally presented for bifuzzy variable, and the linearity of expected value operator of bifuzzy variable is proved. Furthermore, bifuzzy simulations are suggested a...

Group technology (GT) is a useful way to increase productivity with high quality in flexible manufacturing systems. Cell formation (CF) is a key step in GT. It is used to design a good cellular manufacturing system that uses the similarity measure between parts and machines so that it can identify part families and machine groups. Recently, fuzzy clustering has been applied in GT because the fu...

The concept of Fuzzy-random-variable was introduced as an analogous notion to randomvariable in order to extend statistical analysis to situations when the outcomes of some random experiment are fuzzy sets. But in contrary to the classical statistical methods no unique definition has been established yet. In this paper a set-theoretical concept of fuzzy-random-variable will be presented. This n...