As traditional models and algorithms are less effective in dealing with complex irregular temporal data streams, this work proposed a fuzzy association model as well an algorithm. The core idea is to granulate fuzzify information from both the attribute state dimension dimension. After restructuring extracting features out of information, event rule mining algorithm was constructed. can fully e...

Our goal is to set up Controllability and Observability Theorem of fuzzy discrete event systems (FDESs), in which the observability and controllability of events may be fuzzy instead. In particular, we present a detailed computing flow to verify whether the controllability and observability conditions hold. Thus, this result can decide the existence of supervisors. As well, this computing metho...

Text mining techniques are generally applied for classifying the text, finding fuzzy relations and structures in data sets. This research provides plenty text mining capabilities. One common application is text classification and event extraction, which encompass deducing specific knowledge concerning incidents referred to in texts. The main contribution of this paper is the clarification of a ...

Events discrimination and decision maker in sport field are the subject of many interesting studies in computer vision and artificial intelligence. A large volume of research has been conducted for automatic semantic event detection and summarization of sports videos. Indeed the results of these researches have a very significant contribution, as well to television broadcasts as to the football...

A novel paradigm for adaptation in discrete event dynamic systems control is presented. The general idea is then applied, through simulations, to an inventory system. A fuzzy adaptation module is built from few optimal examples generated using a genetic algorithm. The fuzzy module is then capable of adapting the inventory policy achieving much better results than a static policy.