the traditional event tree analysis uses a single probability to represent each top event. however, it is unrealistic to evaluate the occurrence of each event by using a crisp value without considering the inherent uncertainty and imprecision a state has. the fuzzy set theory is universally applied to deal with this kind of phenomena. the main purpose of this study is to construct an easy metho...

The traditional event tree analysis uses a single probability to represent each top event. However, it is unrealistic to evaluate the occurrence of each event by using a crisp value without considering the inherent uncertainty and imprecision a state has. The fuzzy set theory is universally applied to deal with this kind of phenomena. The main purpose of this study is to construct an easy metho...

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...

Fuzzy sets and fuzzy logic research aims to bridge the gap between the crisp world of math and the real world. Fuzzy set theory was applied to many different areas, from control to databases. Sometimes the number of events in an event-driven system may become very high and unmanageable. Therefore, it is very useful to organize the events into fuzzy event sets also introducing the benefits of th...

2 Zadeh-type fuzzy probability The paper deals with two methods of a fuzzification of the Borel field of events and too the probability measure. The first approach generalizes the Zadeh definition of a crisp probability of fuzzy event. The second method is based on the Yager definition of a fuzzy probability of fuzzy event. The theoretical results obtained can be applied to modeling stochastic ...

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...

this article proposes composition of fuzzy sets theory with discrete-event simulation and puts it into application in order to model uncertain activity duration in simulating a real-world system. the purpose of this paper is to assess the usefulness of fuzzy simulation for modeling uncertain activity duration, especially when insufficient or no sample data is available. in this research, fuzzy ...

This paper gives a decentralized approach to the problem of failure prognosis in the framework of fuzzy discrete event systems (FDES). A notion of co-predictability is formalized for decentralized prognosis of FDESs, where several local agents with fuzzy observability rather than crisp observability are used in the prognosis task. An FDES is said to be co-predictable if each faulty event can be...

In order to more effectively cope with the real world problems of vagueness, imprecise and subjectivity, fuzzy event systems were proposed recently. In this paper, we investigate the controllability and the observability property of two systems that one of them has fuzzy variables and the other one has fuzzy coefficients and fuzzy variables (fully fuzzy system). Also, sufficient conditions for ...

Fuzzy random variable is a combination of fuzzy variable and random variable, and can characterize both fuzziness and randomness in the real world. The mean chance of a fuzzy random event is an important concept in fuzzy random optimization, just like the probability of a stochastic event in stochastic optimization and the credibility of a fuzzy event in fuzzy optimization. In fuzzy random prog...