Data mining for prognostic of complex equipment with applications in aerospace and railroad

CIM Edmonton 2008
Abstract This talk reports progress on the development of a generic data mining methodology to build prognostic models for complex equipment. The methodology, which relies on readily available operational and maintenance data, addresses various data mining tasks such as automatic labeling, feature extraction, model building, model fusion, and evaluation. Results from application in the aerospace and railroad industries will be presented.
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