In many real-life situations, uncertainty can be naturally described as a combination of several components, components which are described by probabilistic, fuzzy, interval, etc. granules. In such situations, to process this uncertainty, it is often beneficial to take this granularity into account by processing these granules separately and then combining the results. In this paper, we show th...

The information-theoretical entropy is an effective measure of uncertainty connected with an information source. Its transfer from the classical probabilistic information theory models to the fuzzy set theoretical environment is desirable and significant attempts were realized in the existing literature. Nevertheless, there are some open topics for analysis in the suggested models of fuzzy entr...

This paper presents a fuzzy approach to the identification of organizational values and culture. The proposed approach has been developed from crisp assessment methods in the literature and has been applied to the Industrial Engineering Department (IED) at a state university in Turkey. Highly subjective judgments and ambiguity regarding the presence of values and the culture type of the organiz...

Preference analysis is an important task in multi-criteria decision making. The rough set theory has been successfully extended to deal with preference analysis by replacing equivalence relations with dominance relations. The existing studies involving preference relations cannot capture the uncertainty presented in numerical and fuzzy criteria. In this paper, we introduce a method to extract f...

In this paper, we introduce the concept of complex multi-fuzzy sets (CMkFSs) as a generalization of the concept of multi-fuzzy sets by adding the phase term to the definition of multi-fuzzy sets. In other words, we extend the range of multi-membership function from the interval [0,1] to unit circle in the complex plane. The novelty of CMkFSs lies in the ability of complex multimembership functi...

Fault tree analysis (FTA) is a widely used method for analyzing a system’s failure logic and calculating overall reliability. However, application of conventional FTA has some shortcomings, e.g. in handling the uncertainties, allowing the use of linguistic variables, and integrating human error in failure logic model. Hence, Fuzzy set theory has been proposed to overcome the limitation of conve...

Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate the merits and problems when dealing with uncertainty in machine learning and to give an overview about methodologies which fall under the framework of neurofuzzy methods, in particular fuzzy-clustering on the one side...

In the field of pattern recognition, clustering is used to group the data into different clusters based on the similarity among them. There are a number of clustering techniques developed in the past using different distance/similarity measure. Due to the high versatility in data, researchers have used various distance measure like Hamming distance, Euclidean distance etc. to solve the clusteri...

In occupational safety, prevention and protection usually involve the use of some sort of barriers. To estimate accurately safety barriers effectiveness it is of paramount importance to assure its performance and consequently keep the risks on adequate levels. But, what is safety barrier effectiveness? How to estimate it without statistical reliable data? Estimate the effectiveness of safety ba...

An optimal maintenance strategy mix is necessary for increasing availability and reliability levels of production facilities without significantly increasing operational costs. The selection of maintenance strategies is a typical Multiple Criteria Decision-Making (MCDM) problem with conflicting goals. Consideration of interdependence among the criteria and alternative policies for maintenance s...