Article: New machine learning study findings reported from S. Ruan and co-authors.(Report)

"In this paper, we consider a model for the dynamic multiple-fault diagnosis (DMFD) problem arising in online monitoring of complex systems and present a solution. This problem involves real-time inference of the most likely set of faults and their time-evolution based on blocks of unreliable test outcomes over time," investigators in the United States report.

"In the DMFD problem, there is a finite set of mutually independent fault states, and a finite set of sensors (tests) is used to monitor their status. We model the dependence of test outcomes on the fault states via the traditional D-matrix (fault dictionary). The tests are imperfect in the sense that they ...

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