Once the input values are given, the active rules in a fuzzy inference execution have been determined. Based on the observation, our approach is to identify the active rules before fuzzy inference execution. To achieve this goal, our architecture provides the following two mechanisms: (1) a mechanism to ignore the non-active rules before fuzzy inference execution; and (2) a mechanism to arrange...

This work aims to improve simulation performance by introducing fuzzy logic in the discrete event simulation. This paper attempts to develop a new approach to assess the duration of dynamical systems, especially the natural processes. To do, we have used the fuzzy logic theory and particularly the fuzzy inference system combined to the discrete event simulation (DEVS). The process simulation is...

Random fuzzy theory offers an appropriate mechanism to model random fuzzy phenomena, with a random fuzzy variable defined as a function from a credibility space to a collection of random variables. Based on this theory, this paper presents the results of an investigation into the representation of properties of alternating renewal processes that are described by sequences of positive random fuz...

SELECTION OF SIMULATION VARIANCE REDUCTION TECHNIQUES THROUGH A FUZZY EXPERT SYSTEM Adrian Aderemi Adewunmi, BSc In this thesis, the design and development of a decision support system for the selection of a variance reduction technique for discrete event simulation studies is presented. In addition, the performance of variance reduction techniques as stand alone and combined application has be...

The testing of event driven software has significant role to improve overall quality of software. Due to event driven nature of GUI based software many test cases are generated and it is difficult to identify test cases whose fault revealing capability is high. To identify those test cases test suite prioritization is done. Various test suite prioritization methods exists for GUI based software...

In this paper, we present our work in the field of computational intelligence and discrete event systems. Knowledge representation and the inclusion of imperfect knowledge is a key step in an effort to optimally incorporate artificial intelligence methods in a modeling and simulation framework. Fuzzy Inference Systems (FIS) are one of the most used applications of Fuzzy Logic and Fuzzy Sets The...