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ORCIDAAAI Fall Symposium 2007 - Artificial Intelligence for Prognostics: Arlington, VA, USA
- George J. Vachtsevanos, N. Serdar Uckun, Kai Goebel:
Artificial Intelligence for Prognostics, Papers from the 2007 AAAI Fall Symposium, Arlington, Virginia, USA, November 9-11, 2007. AAAI Technical Report FS-07-02, AAAI Press 2007 - Ali Akoglu, Sonia Vohnout, Justin Judkins:
FPGA Based Fault Detection, Isolation and Healing for Integrated Vehicle Health. 1-8 - Gautam Biswas, Sankaran Mahadevan:
Multi-level Methods for Combined Diagnostics and Prognostics. 9-16 - Piero P. Bonissone, Naresh Iyer:
Soft Computing Applications to Prognostics and Health Management (PHM): Leveraging Field Data and Domain Knowledge. 17-25 - Shunfeng Cheng, Michael G. Pecht:
Multivariate State Estimation Technique for Remaining Useful Life Prediction of Electronic Products. 26-32 - Chris Drummond:
Changing Failure Rates, Changing Costs: Choosing the Right Maintenance Policy. 33-35 - Artur Dubrawski, Michael Baysek, Shannon Mikus, Charles McDaniel, Bradley Mowry, Laurel Moyer, John Östlund, Norman K. Sondheimer, Timothy Stewart:
Applying Outbreak Detection Algorithms to Prognostics. 36-43 - Dustin Garvey, J. Wesley Hines:
Dynamic Prognoser Architecture via the Path Classification and Estimation (PACE) Model. 44-49 - Jie Gu, Donald Barker, Michael G. Pecht:
Uncertainty Assessment of Prognostics of Electronics Subject to Random Vibration. 50-57 - Asif Khalak, Kai Goebel:
Health-Management Driven Control Reconfiguration Approach for Flight Vehicles. 58-62 - James Kozlowski, Karl Reichard, Scott Laurin:
Using Health Information to Reconfigure Platform Operation, Adjust Mission Goals and Extend the Life of the System. 63-72 - Sachin Kumar, Michael G. Pecht:
Health Monitoring of Electronic Products Using Symbolic Time Series Analysis. 73-80 - Sylvain Létourneau, Chunsheng Yang, Zhenkai Liu:
On-Demand Regression to Improve Preciseness of Time to Failure Predictions. 81-87 - Michael J. Roemer, Carl S. Byington, Michael S. Schoeller:
Selected Artificial Intelligence Methods Applied within an Integrated Vehicle Health Management System. 88-96 - Bhaskar Saha, Kai Goebel, Scott Poll, Jon Christophersen:
A Bayesian Framework for Remaining Useful Life Estimation. 97-102 - Abhinav Saxena, George J. Vachtsevanos:
Optimum Feature Selection and Extraction for Fault Diagnosis and Prognosis. 103-107 - Mark Schwabacher, Kai Goebel:
A Survey of Artificial Intelligence for Prognostics. 108-115 - Vadim Smelyanskiy, Serdar Uckun, Nancy J. Lybeck, Brogan Morton, Sean Marble:
Dynamic CMG Model. 116-120 - Vasilis A. Sotiris, Michael G. Pecht:
Support Vector Prognostics Analysis of Electronic Products and Systems. 121-128 - Liang Tang, Gregory J. Kacprzynski, Kai Goebel, Johan Reimann, Marcos E. Orchard, Abhinav Saxena, Bhaskar Saha:
Prognostics in the Control Loop. 129-136 - Alexander Usynin, J. Wesley Hines:
Uncertainty Management in Shock Models Applied to Prognostic Problems. 137-
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