Tutorial [electronic resource] : Neural networks and their potential application in nuclear power plants
- Washington, D.C. : United States. Dept. of Energy, 1989. and Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy.
- Physical Description:
- Pages: (11 pages) : digital, PDF file
- Additional Creators:
- University of Tennessee, Knoxville, United States. Department of Energy, and United States. Department of Energy. Office of Scientific and Technical Information
- A neural network is a data processing system consisting of a number of simple, highly interconnected processing elements in an architecture inspired by the structure of the cerebral cortex portion of the brain. Hence, neural networks are often capable of doing things which humans or animals do well but which conventional computers often do poorly. Neural networks have emerged in the past few years as an area of unusual opportunity for research, development and application to a variety of real world problems. Indeed, neural networks exhibit characteristics and capabilities not provided by any other technology. Examples include reading Japanese Kanji characters and human handwriting, reading a typewritten manuscript aloud, compensating for alignment errors in robots, interpreting very noise'' signals (e.g. electroencephalograms), modeling complex systems that cannot be modelled mathematically, and predicting whether proposed loans will be good or fail. This paper presents a brief tutorial on neural networks and describes research on the potential applications to nuclear power plants.
- Published through SciTech Connect., 01/01/1989., "conf-890634-5", "DE93002120", Expert systems applications for the electric power industry conference, Orlando, FL (United States), 5-8 Jun 1989., and Uhrig, R.E. . Dept. of Nuclear Engineeri.
- Funding Information:
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