Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Introduction to Bayesian Networks
Introduction to Bayesian Networks
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Generally, an IPCS should reconcile two contradictory properties: reacting in real time to the solicitations of the environment and operating out some evolved reasoning in order to meet these solicitations. This paper, proposes an approach where the system is considered as composition of three sub-systems. A reactive sub-system taking into account the control, the surveillance of the IP. An evaluating sub-systems that watch out for the functioning safety and the breakdowns prediction. A supervising sub-system taking into account the diagnosis and the supervision of the IP. This approach proposes a diagnosis architecture using the Data Mining techniques. These techniques enable to answer different tasks of the diagnosis such as the selection of pertinent indicators, the generation of breakdown cases, the prediction and more particularly, the temporal and spatial dependencies of the IP.