A knowledge driven approach to aerospace condition monitoring-Reference-Cited by-同舟云学术

A knowledge driven approach to aerospace condition monitoring

Published:2011-08 Issue:6 Volume:24 Page:915-927
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Phillips Paul,Diston Dominic

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference19 articles.

1. C. Byington, M. Watson, D. Edwards, P. Stoetling, A model-based approach to prognostics and health management for flight control actuators, in: Proceedings of the IEE Aerospace Conference, 2004.

2. A fuzzy approach to the evaluation of image complexity;Cardaci;Fuzzy Sets and Systems,2009

3. Model-based approach for fault diagnosis. 1. Principles of deep model algorithm;Chang;Industrial and Engineering Chemistry Research,2002

4. S. Engel, B. Gilmartin, K. Bongort, A. Hess, Prognostics, the real issues involved with predicting life remaining, in: IEEE Aerospace Conference Proceedings, Big Sky, MT, 2000.

5. A review of data fusion models and architectures: towards engineering guidelines;Esteban;Neural Computing and Applications,2005

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