The hybridization of rough sets and fuzzy sets has focused on creating an end product that extends both contributing computing paradigms in a conservative way. As a result, the hybrid theory inherits their respective strengths, but also exhibits some weaknesses. In particular, although they allow for gradual membership, fuzzy rough sets are still abrupt in a sense that adding or omitting a sing...

One of the toughest challenges in medical diagnosis is the handling of uncertainty. Since medical diagnosis with respect to the symptoms uncertain, they will be assumed to have an intuitive nature. Thus, to obtain the uncertain optimism degree of the doctor, fuzzy linguistic quantifiers will be used. The aim of this article is to provide an improved nonprobabilistic entropy approach to support ...

In this paper, a new approximate syllogistic reasoning schema is described that expands some of the approaches expounded in the literature into two ways: (i) a number of different types of quantifiers (logical, absolute, proportional, comparative and exception) taken from Theory of Generalized Quantifiers and similarity quantifiers, taken from statistics, are considered and (ii) any number of p...

Linguistic rules in natural language are useful and consistent with human way of thinking. They are very important in multi-criteria decision making due to their interpretability. In this paper, our discussions concentrate on extracting linguistic rules from data sets. In the end, we firstly analyze how to extract complex linguistic data summaries based on fuzzy logic. Then, we formalize lingui...

This paper is a continuation of the formal theory of intermediate quantifiers (expressions such as most, few, almost all, a lot of, many, a great deal of, a large part of, a small part of ) introduced by Novák in [12]. The theory is a fuzzy-logic formalization of the concept introduced by Peterson in his book [17]. In this paper, we syntactically prove that 105 generalized Aristotle’s syllogism...

This work has as its main objective to apply the distributed agency methodology, which consists of several techniques used in computer science, to solve complex social problems. This approach allows the possibility of analyzing data from a macro level to a micro level where the intermediate part is highlighted, all in an organized integration of a social simulation displayed on geographic infor...

In this paper, we discuss three tasks of mining information from time series, namely finding intervals with monotonous trend, evaluation of it in sentences of natural language, and summarizing information using intermediate quantifiers. The mined information is presented in simple sentences of natural language. For estimation of the trend of time series, we apply the theory of first-degree F-tr...

This paper introduces a semantic model for vague quantifiers (VQs) combining Fuzzy Theory (FT) and Supervaluation Theory (ST), which are the two main theories on vagueness, a common source of uncertainty in natural language. After comparing FT and ST, I will develop the desired model and a numerical method for evaluating truth values of vague quantified statements, called the Modified Glöckner’...

Software projects are often described by linguistic variables such as the experience of programmers and the complexity of modules. Because the existing software projects similarity measures take into account only numerical data, we have proposed a set of measures based on fuzzy logic to evaluate the similarity between two software projects when they are described by linguistic values. In this w...