The paper deals with an idea of a linguistic knowledge representation and a linguistic inference. Relational linguistic fuzzy model with weights of rules is utilising. The probability of linguistic values of antecedent and consequent variables, calculated according to Zadeh’s definition, is proposed to formulate a linguistic fuzzy model of a stochastic system. The linguistic inference procedure...

Complex fuzzy sets (CFSs) are a suitable tool to manage spatial directional information which includes distance and direction. However, is given by linguistic values. It very awkward for the CFS describe this type of information. To overcome limitation, we first propose novel concept called complex set (LCFS) serve as an extension CFS. Then put forward some basic operational laws LCFSs. After t...

In [13], an algebraic approach to the natural structure of domains of linguistic variables was introduced. In this approach, every linguistic domain can be interpreted as an algebraic structure called a hedge algebra. In this paper, a refinement structure of hedge algebras based on free distributive lattices generated by linguistic hedge operations will be examined in order to model structure o...

Lawrence O. Hall Dept. of Computer Science and Engineering, ENB 118 University of South Florida Tampa, Fl. 33620 [email protected] Abstract A fuzzy expert system must do rule chaining differently than a non-fuzzy expert system. In particular, any rule that can fire with a particular linguistic variable in its consequent must fire before any rule whose antecedent conditions depend upon the resul...

Purpose – The purpose of this paper is to define an evaluation model for cloud services to deal with the fuzzy information and propose a novel fuzzy evaluation method based on consistency intensity to analyze the quantitative value from the fuzzy information. Design/methodology/approach – The cloud service evaluation framework is constructed, and different trusted indicators for the infrastruct...

A new systematic algorithm to build adaptive linguistic fuzzy models directly from input-output data is presented in this paper. Based on clustering and projection in the input and output spaces, significant inputs are selected, the number of clusters is determined, rules are generated automatically, and a linguistic fuzzy model is constructed. Then, using a simplified fuzzy reasoning mechanism...

The intuitionistic uncertain fuzzy linguistic variable can easily express the fuzzy information, and the power average (PA) operator is a useful tool which provides more versatility in the information aggregation procedure. At the same time, Einstein operations are a kind of various t-norms and t-conorms families which can be used to perform the corresponding intersections and unions of intuiti...

A fuzzy-set-based approach is presented to describe linguistic information in multi-criteria decision making. After having introduced concepts of determinacy and consistency of linguistic terms, the understandable degree and consistence degree of linguistic terms are illustrated by these two concepts. A case study is demonstrated for the proposed decision-making model with an analytical conclus...

This paper proposes a Fuzzy Group Decision Making approach for ranking work stations based on physical pressure. Fuzzy group decision making approach allows experts to evaluate different ergonomic factors using linguistic terms such as very high, high, medium, low, very low, rather than precise numerical values. In this way, there is no need to measure parameters and evaluation can be easily ma...

The fuzzy sets defining the linguistic variable values can be seen as a fuzzy partition of the linguistic variable. The membership functions obtained using fuzzy clustering algorithms are defined with respect to the group prototypes, and they cannot be used to define the linguistic variable values. We introduce several criteria to pass from the clustering membership functions to the linguistic ...