M. A. El-Sharkawi and S. S. Huang, "Query-based learning neural network approach to power system dynamic security assessment," in Proc. 1993. Home/Search Document Not in Database Summary Related Articles Check |
This paper is cited in the following contexts:
Inversion of Feedforward Neural Networks.. - Jensen, Reed.. (1999) (2 citations) Self-citation (El-sharkawi) (Correct)
....their protection systems, resulting in a further disturbance to the system. This is called a cascading outage and may lead to a breach in system security such as a blackout. Neural networks have shown promise in the fast screening and detection of operating conditions that may lead to blackouts [19], 20] In these applications, neural networks are trained to classify a power system as secure or insecure based on a set of features of the prefault system such as transmission line flows, generation settings, or system voltage levels. The neural networks are then used during the everyday ....
M. A. El-Sharkawi and S. S. Huang, "Query-based learning neural network approach to power system dynamic security assessment," in Proc. 1993.
Inversion of Feedforward Neural Networks.. - Jensen, Reed, II, .. (1999) (2 citations) Self-citation (El-sharkawi) (Correct)
....classification accuracy. Boundary marking is a technique whereby evenly spaced boundary points can be generated for eventual presentation to the oracle. Query based learning has been applied to a number of applications, include cytology screening [16] 17] power system security assessment [18] [19], 20] and classification of incomplete data [23] Example 2: Query based Learning Applied to Power System Security Assessment An application of neural network query learning using boundary marking is in the field of power system security assessment. This deals with the ability of a large scale ....
....their protection systems, resulting in a further disturbance to the system. This is called a cascading outage and may lead to a breach in system security such as a blackout. Neural networks have shown promise in the fast screening and detection of operating conditions that may lead to blackouts [19], 20] In these applications, neural networks are trained to classify a power system as secure or insecure based on a set of features of the prefault system such as transmission line flows, generation settings, or system voltage levels. The neural networks are then used during the everyday ....
M. A. El-Sharkawi and S. S. Huang, "Query-Based Learning Neural Network Approach to Power System Dynamic Security Assessment," 1993 International Symposium on Nonlinear Theory and Its Applications (NOLTA'93), Hawaii, USA, December, 1993.
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