Abstract
This chapter introduces practical application examples that are described throughout the book. The examples highlight key benefits of concurrent learning and information processing methods. (All underlined terms in this chapter and the rest of the book appear in the Glossary.) The examples are arranged in this chapter, just as they are arranged throughout this book, into three main application areas: adaptive monitoring (see section 1.1), forecasting (see section 1.2), and control (see section 1.3). This chapter describes another important aspect of concurrent learning as well: automatic model refinement (see section 1.4).
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
R.J. Jannarone, “Concurrent Information Processing, I: An Applications Overview,” Applied Computing Review, Vol. I, pp. 1 – 6, 1993.
G.E. Weeks, W.E. Daniel, R E. Edwards, Jr., S.N. Palakodety, S.S. Joshi, D, Qian, & R.J. Jannarone, “Holledge Gauge Failure Testing using Concurrent Information Processing Algorithm,” Proceedings of the International Topic Meeting on Nuclear and Hazardous Waste Management, American Nuclear Society, Inc., La Grange Park, IL, Vol. 3, pp. 2261 – 2268, 1996.
“Industrial Instrument Monitoring,” RCNS Technical Report Series, No. APP95-06, Rapid Clip Neural Systems, Inc., Atlanta, GA, 1996.
S. N. Joshi, A General-Purpose Concurrent Information Processing Prototype, Unpublished Masters Thesis, University of South Carolina, 1994.
S. S. Palakodety, A Special-Purpose Concurrent Information Processing System, Unpublished Masters Thesis, University of South Carolina, 1994.
Y. Hu, “Automated Real-Time Neural Computing for Defense Waste Processing,” Proceedings of the International Topic Meeting on Nuclear and Hazardous Waste Management, American Nuclear Society, Inc., La Grange Park, IL, Vol. 1, pp. 534 – 540, 1992.
S.D. Durham, Z.Q. Li, R.J. Jannarone, R.E. Edwards, Jr., & J.S. Lyons, “Welder Parametric Study: Preliminary Statistical Analysis,” SCUREF — Westinghouse Savannah River Laboratory Technical Report, April 1992.
T.L. Huntsberger & N. Navlani, “Welder Parametric Study: Nonparametric Neurocomputing Analysis,” SCUREF — Westinghouse Savannah River Laboratory Technical Report, April 1992.
“Structural Testing of Aircraft Components,” RCNS Technical Report Series, No. APP96-01, Rapid Clip Neural Systems, Inc., Atlanta, GA, 1996.
“Health Monitoring, Management, and Advisement,” RCNS Technical Report Series, No. APP96-03, Rapid Clip Neural Systems, Inc., Atlanta, GA, 1996.
“A Commodity Price Forecasting Example,” RCNS Technical Report Series, No. APP96-02, Rapid Clip Neural Systems, Inc., Atlanta, GA, 1996.
“Vehicle Tracking Applications,” RCNS Technical Report Series, No. APP96-04, Rapid Clip Neural Systems, Inc., Atlanta, GA, 1996.
K.J. Aström & T.J. McAvoy, “Intelligent Control: an Overview and Evaluation,” in D A. White & D A. Sofge (Eds.), Handbook of Intelligent Control, Van Nostrand Reinhold, New York, 1992.
B. Kosko, Neural Networks and Fuzzy Systems, Prentice-Hall, Englewood Cliffs, NJ, 1992.
Y. Hu, Concurrent Information Processing with pattern Recognition Applications, Unpublished Doctoral Dissertation, University of South Carolina, 1994.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 1997 Chapman & Hall
About this chapter
Cite this chapter
Jannarone, R.J. (1997). Rapid Learning Applications. In: Concurrent Learning and Information Processing. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-0431-9_1
Download citation
DOI: https://doi.org/10.1007/978-1-4613-0431-9_1
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-8049-8
Online ISBN: 978-1-4613-0431-9
eBook Packages: Springer Book Archive