This paper describes a novel approach, based on intuitionistic fuzzy set theory for reliability analysis of series and parallel network. The triangular intuitionistic fuzzy sets are used to represent the failure possibility of each basic (terminal) event to get more comprehensive results for the failure possibility of the top event. The proposed technique is demonstrated on a web server LOG dat...

A hybrid system is a system containing a mixture of discrete event components and continuous variable components. The existing hybrid system modeling methods are effective to handle crisp cases but can be difficult to represent deterministic uncertainties and subjectivity inherited in many real-world applications. We generalize the crisp hybrid system framework to a fuzzy hybrid system framewor...

In this paper we investigate an intelligent discrete event method suitable for modeling, simulation and control of hybrid systems. More in detail, a Fuzzy logic approach based on Discrete Event System Specification (DEVS), which is a main part of Intelligent-DEVS (I-DEVS), is emphasized in the present work. We show that the resulting Discrete Event Fuzzy Logic (DEFuL) is faster than conventiona...

Formal analysis of functional properties of system requirements needs precise descriptions. However, the stakeholders sometimes describe the system with ambiguous, vague or fuzzy terms, hence formal frameworks for modeling and verifying such requirements are desirable. The Fuzzy If-Then rules have been used for imprecise requirements representation, but verifying their functional properties sti...

Task assignment processes and its control implying reasoning about objects and resources and their changing states are dominated by discrete or stochastic-event dynamics or both. Estimating the components position of the mobile robot provided by sensor generates unknown, hidden variables which will be model by the means of probabilistic inference taking into account incomplete and uncertain inf...

Traditional stochastic discrete event simulation method requires the users to fit the task duration data with an empirical probability function or a theoretical probability density function. This has limited the application of discrete event simulation techniques from research stage to construction practice due to the tedious data fitting tasks required for the construction operation planners l...

In business process management, decision situations are often characterized by fuzziness. This means that the decision premises are not available in the form of mathematic models or numeric values, but rather as fuzzy conditions, such as “low processing time” or “high quality”. This article will show how fuzzy conditions and vaguely formulated goals in business process models can be considered ...

This article introduces a general framework of multi-granulation fuzzy probabilistic roughsets (MG-FPRSs) models in multi-granulation fuzzy probabilistic approximation space over twouniverses. Four types of MG-FPRSs are established, by the four different conditional probabilitiesof fuzzy event. For different constraints on parameters, we obtain four kinds of each type MG-FPRSs...