small Polygroups are multi-valued systems that satisfy group-likeaxioms. Using the notion of “belonging ($epsilon$)” and “quasi-coincidence (q)” offuzzy points with fuzzy sets, the concept of ($epsilon$, $epsilon$ $vee$ q)-fuzzy subpolygroups isintroduced. The study of ($epsilon$, $epsilon$ $vee$ q)-fuzzy normal subpolygroups of a polygroupare dealt with. Characterization and some of the fundam...

It is firstly proved that the multi-input-single-output (MISO) fuzzy systems based on interval-valued $R$- and $S$-implications can approximate any continuous function defined on a compact set to arbitrary accuracy.  A formula to compute the lower upper bounds on the number  of interval-valued fuzzy sets needed to achieve a pre-specified approximation  accuracy for an arbitrary multivariate con...

Kim and Bishu (Fuzzy Sets and Systems 100 (1998) 343-352) proposeda modification of fuzzy linear regression analysis. Their modificationis based on a criterion of minimizing the difference of the fuzzy membershipvalues between the observed and estimated fuzzy numbers. We show that theirmethod often does not find acceptable fuzzy linear regression coefficients andto overcome this shortcoming, pr...

The paper presents a short review of some main properties of the most general fuzzy systems used in a large class of practical applications. The fuzzy systems, implemented using different rule bases, fuzzy values, membership functions, fuzzyfication and defuzzification methods, may be classified based on these fuzzy methods used in their development. This paper proposes a unitary theory for des...

Combining both kinds of fuzzy logic forms including fuzzy T-S model and adaptive fuzzy logic systems, this paper presents an adaptive control scheme for a class of nonlinear systems. Firstly, the fuzzy T-S model is used to approximate the nonlinear systems, and the fuzzy control law of the fuzzy model is derived by the linear matrix inequality. Secondly, the adaptive fuzzy logic systems are con...

Probabilistic fuzzy systems combine a linguistic description of the system behaviour with statistical properties of data. It was originally derived based on Zadeh’s concept of probability of a fuzzy event. Two possible and equivalent additive reasoning schemes were proposed, that lead to the estimation of the output’s conditional probability density. In this work we take a complementary approac...

in order to survive in today's competitive world, organizations are looking to increase their efficiency and effectiveness. therefore, they should focus on inputs that are more important than the rest of the inputs in their success. this paper aimed at ranking 7ms (management, man power, marketing, material, machinery, methods and money) and their sub-criteria of production in iran. by imp...

Rough fuzzy sets are an effective mathematical analysis tool to deal with vagueness and uncertainty in the area of machine learning and decision analysis. Fuzzy information systems and fuzzy objective information systems exit in many applications and knowledge reduction in them can’t be implemented by reduction methods in Pawlak information systems. Therefore, this paper provides a model for ru...