Data processing: structural design – modeling – simulation – and em – Modeling by mathematical expression
Reexamination Certificate
2005-08-30
2005-08-30
Teska, Kevin J. (Department: 2123)
Data processing: structural design, modeling, simulation, and em
Modeling by mathematical expression
C703S022000
Reexamination Certificate
active
06937966
ABSTRACT:
Predictive models are widely used for tasks in many domains. The present invention addresses the problem of prediction of non-stationary processes by dynamically managing multiple models. The system comprises a model assessor, a model adapter, a plurality of sub-models, a plurality of model combiner functions, training data that is used to estimate model parameters, and test data that is used to test for change points. Two processes are described, one for handling data updates and another that addresses prediction requests.
REFERENCES:
patent: 5251262 (1993-10-01), Suzuki et al.
patent: 5793429 (1998-08-01), Kim et al.
patent: 5798949 (1998-08-01), Kaub
patent: 5862507 (1999-01-01), Wu et al.
patent: 6230062 (2001-05-01), Shah
patent: 6338066 (2002-01-01), Martin et al.
patent: 6430615 (2002-08-01), Hellerstein et al.
patent: 6474153 (2002-11-01), Yamanaka et al.
patent: 6513025 (2003-01-01), Rosen
patent: 6529887 (2003-03-01), Doya et al.
patent: 6542894 (2003-04-01), Lee et al.
patent: 6546379 (2003-04-01), Hong et al.
patent: 6826521 (2004-11-01), Hess et al.
Karimi et al., “Robust adaptive control of a flexible transmission system using multiple models”, IEEE 1998.
Basseville et al., “A unified framework for statistical change detction”, IEEE 1991.
Hellerstein et al., “Characterizing Normal operations of a Web server: Application to workload Forecasting and Problem Detection”, Proceedings of the 1998 Conference of the computer measurement Group, Dec. 1998.
Riis, “Combining Neural networks for protein Secondary structure prediction”, IEEE 1995.
J.L. Hellerstein et al., “An Approach to Predictive Detection for Service Level Management,” Integrated Network Management VI, edited by M. Sloman et al., IEEE Publishing, pp. 309-322, May 1999.
V. Kadirkamanathan et al., “A Stochastic Method for Neural-Adaptive Control of Multi-Modal Nonlinear Systems,” UKACC International Conference on Control, pp. 49-53, Sep. 1998.
R. Rao, “Dynamic Appearance-Based Recognition,” IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 540-546, Jun. 1997.
P. Eide et al., “An MMAE Failure Detection System for the F-16,” IEEE Transactions on Aerospace and Electronic Systems, vol. 32, No. 3, pp. 1125-1136, Jul. 1996.
M. Basseville et al., “Detection of Abrupt Changes: Theory and Application,” Prentice Hall, pp. 29-42, 1993.
Hellerstein Joseph L.
Zhang Fan
International Business Machines - Corporation
Perez-Pineiro Rafael
Ryan & Mason & Lewis, LLP
Teska Kevin J.
Thangavelu Kandasamy
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