Abstract

For composite fault is difficult to diagnose, the characteristics of the large amount of data. This paper presents a method of The Prediction method of Composite Fault Based on data driven to establish intelligence unit Based on a collection of virtual individuals associated with the virtual failure associated collection and virtual behavior associated collection. Composite fault warning engine modeling is proposed, and give the warning value of composite fault finally. This method is fully assessing the future "dominant state" on the basis of the fully aware of current "hidden state". The impact of factors such as disturbance of hidden failures on composite fault prediction are fully considered, to some extent, the long-span composite failure prediction problem is solved, and the experiments show that the method effectively increases the accuracy of composite fault prediction.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.