DocumentCode :
2664089
Title :
On-line security classification using an artificial neural network
Author :
Thomas, R.J. ; Sakk, E. ; Hashemi, K. ; Ku, B.Y. ; Chiang, H.D.
Author_Institution :
Sch. of Electr. Eng., Cornell Univ., Ithaca, NY, USA
fYear :
1990
fDate :
1-3 May 1990
Firstpage :
2921
Abstract :
A neural network classifier for the class of problems associated with transmission-line faults is described. Faults are considered to be modeled by continuous parameters. The solution is then embedded in a set that results from a map of the current stable equilibrium point to the set of all 4-cycle-fault-on post-fault operating points. An experimental analysis of the application of a single-layer feedforward network to the problem of security screening is presented
Keywords :
fault currents; neural nets; power engineering computing; power transmission lines; 4-cycle-fault-on post-fault operating points; artificial neural network; continuous parameters; current stable equilibrium point; security classification; security screening; single-layer feedforward network; transmission-line faults; Artificial neural networks; Biological neural networks; Biology computing; Computer networks; Neural networks; Power systems; Scattering; System testing; Training data; Voltage;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 1990., IEEE International Symposium on
Conference_Location :
New Orleans, LA
Type :
conf
DOI :
10.1109/ISCAS.1990.112622
Filename :
112622
Link To Document :
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