the goal of this paper is to show how the concept of fuzzy logic can be used to establish a degree to which an investment project belongs to a class of risk. also, the probability of the fuzzy event is presented and is ap-plied to calculate the probability of the fuzzy event “the project x is a good investment”. this process has to enable the decision maker to compare several alternative invest...

In recent years, much attention has been focused on the ability of fuzzy logic to solve problems that were previously assumed difficult to solve. These include, for example, the use of fuzzy logic for control and pattern recognition. However, the application of fuzzy logic to the establishment of correlations between independent and dependent process variables, i.e. regression modeling, has rec...

VHDL high level modelling and implementaiton of fuzzy systems p. 11 Some complexity results on fuzzy description logics p. 19 An evolutionary approach to ontology-based user model acquisition p. 25 Mathematical modeling of passage dynamic function p. 33 Bi-monotonic fuzzy sets lead to optimal fuzzy interfaces p. 39 Conversational agent model in intelligent user interface p. 46 A fuzzy frame-bas...

In this paper, we propose a scalar variable formation of fuzzy regression model based on the axiomatic credibility measure foundation. The fuzzy estimation for fuzzy regression coefficients is investigated. A general M-estimation criterion is developed under Maximum Fuzzy Uncertainty Principle, which resulted in weighted Normal equation with adjusted term for M-estimator of the regression coeff...

abstract nowadays, due to the environmental uncertainty and rapid development of new technologies, economic variables are often predicted by using less data and short-term timeframes. therefore, prediction methods which require fewer amounts of data are needed. auto regressive integrated moving average (arima) model and artificial neural networks (anns) need large amounts of data to achieve acc...

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...