A significant data mining issue is the effective discovery of association rules. The extraction of association rules faces the problem of the combinatorial explosion of the search space, and the loss of information by the discretizat ion of values. The first problem is confronted effectively by the Frequent Pattern Tree approach of [10 ]. This approach avoids the candidate generation phase of A...

In this paper, we propose a unitary tool for modeling and analysis of discrete event systems monitoring. Uncertain knowledge of such tasks asks specific reasoning and adapted fuzzy logic modeling and analysis methods. In this context, we propose a new fuzzy Petri net called Fuzzy Reasoning Petri Net: the FRPN. The modeling consists in a set of two collaborative FRPN. The first is used for the f...

Construction injury accidents result from different causes. Risk evaluation for cave-ins using traditional fault-tree analysis can be difficult, especially since the variables resulting in cave-ins are unique; in addition, historical data, when available, is often incomplete. In construction, assessment of risk is based on linguistic terms using subjective judgment of linguistic values such as ...

and Conclusions This paper is concerned with the analysis of Event Trees where the branch point event causes are defined using Fault Tree structures. Attention is focussed on the non-trivial situation where there are dependencies amongst the branch point events. The dependencies are due to component failure events featuring in one or more of the fault trees. In these situations it is shown that...

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...

Fuzzy Decision Tree is becoming increasingly significant as it is applied to areas of different platforms in real life. This paper gives an overview of the applications of fuzzy decision tree in heterogeneous fields. It is being actively used in fields as varied as intrusion detection, flexible querying (modus ponens), analysis of cognitive process (Human Computer Interaction), for user authent...

Decision tree induction is one of common approaches for extracting knowledge from a sets of feature-based examples. In real world, many data occurred in a fuzzy and uncertain form. The decision tree must able to deal with such fuzzy data. This paper presents a tree construction procedure to build a fuzzy decision tree from a collection of fuzzy data by integrating fuzzy set theory and entropy. ...