Open AccessEFFECTIVE EVENT DERIVATION OF UNCERTAIN EVENTS IN RULE-BASED SYSTEMS
Author(s) -
Gaddam Prasad,
Mr.D.Murahari Reddy
Publication year - 2013
Publication title -
international journal of communication networks and security
Language(s) - English
Resource type - Journals
ISSN - 2231-1882
DOI - 10.47893/ijcns.2013.1076
Subject(s) - computer science , event (particle physics) , process (computing) , data mining , complex event processing , outcome (game theory) , machine learning , artificial intelligence , mathematics , physics , quantum mechanics , mathematical economics , operating system
There is a growing need for systems that react automatically to events. While some events are generated externally and deliver data across distributed systems, others need to be derived by the system itself based on available information. Unpredictability of future events which influence the outcome of the present decisions but have not yet occurred and no one can predict what they will be like. In this process, it finds out the uncertain events using the rules. Here it uses the Event Instance Data for find out the efficient process. This performs the two mechanisms are select ability is for calculation of the exact probability space and sampling techniques. For this process it uses the efficient algorithms that are calculate selectable EID and Rule stamp algorithm. In this paper, we also emphasized the important role that event select ability plays in uncertain event derivation. We demonstrated not only that it plays a significant semantic role, but also, that the proper usage of select ability can significantly improve performance, and result in a framework that is much more suited to applications with a high event throughput. This system provides the better results and provides the efficient process.