Checking the truth value of political statements is difficult. Fact checking computationally has therefore not been very successful. An alternative to checking the truth value of a statement is to not consider the facts that are stated, but the way the statement is expressed. Using linguistic features from seven computational linguistic algorithms, we investigated whether truth-false statements...

Since the concept of linguistic variables was proposed, various kinds of linguistic terms have been used to express decision makers’ preference information in order to solve group decision making (GDM) problems. Probabilistic linguistic term set (PLTS) is a novel extension form of the existing linguistic variables. Based on it, the probabilistic linguistic preference relation (PLPR) has been pr...

The fuzzy logic theory proposed by Zadeh (1965) is based on intuitive reasoning and takes into account human subjectivity and imprecision. Unlike statistical data mining techniques such as cluster or regression analysis, fuzzy logic enables the use of nonnumerical values and introduces the notion of linguistic variables (Zadeh, 1975a, 1975b, 1975c). Using linguistic terms and variables hides Ab...

Linguistic variables are reviewed and some aspects of the original definition revisited, showing that they provide a first formal frame to do computing with words in a “narrow sense”. A two-levels hierarchy of languages is discussed in order to move to simple cases of computing with words in natural language, supported by linguistic variables.

The aim of this paper is to present the Temporal Fuzzy Chains (TFCs) [3] to model the dynamic systems in a linguistic manner. TFCs make use of two different concepts: the traditional method to represent the dynamic systems named state vectors [6], and the linguistic variables [8] used in fuzzy logic [7]. Thus, TFCs are qualitative and represents the ”temporal zones” using linguistic states and ...

The aim of this paper is to present an algorithm to induce the Temporal Fuzzy Chains (TFCs) (J. Moreno, 2002b). TFCs are used to model the dynamic systems in a linguistic manner. TFCs make use of two different concepts: the traditional method to represent the dynamic systems named state vectors (Ogata, 1998), and the linguistic variables (Zadeh, 1975) used in fuzzy logic (Tanaka, 1998). Thus, T...

The aim of this paper is to present the Temporal Fuzzy Chains (TFCs) [3] to model the dynamic systems in a linguistic manner. TFCs make use of two different concepts: the traditional method to represent the dynamic systems named state vectors [6], and the linguistic variables [8] used in fuzzy logic [7]. Thus, TFCs are qualitative and represents the ”temporal zones” using linguistic states and ...

Fuzzy logic control is a methodology bridging artificial intelligence and traditional control theory. This methodology is usually applied in the only cases when accuracy is not of high necessity or importance. On the other hand, as it is stated in (TI SPRA028, Jan.1993), “Fuzzy Logic can address complex control problems, such as robotic arm movement, chemical or manufacturing process control, a...

Generalizing our earlier results on optimization with linguistic variables [3, 6, 7] we introduce a novel statement of fuzzy multiobjective mathematical programming problems and provide a method for finding a fair solution to these problems. Suppose we are given a multiobjective mathematical programming problem in which the functional relationship between the decision variables and the objectiv...