Conference proceeding
An improved Hopfield model for power system contingency classification
1990 IEEE International Symposium on Circuits and Systems (ISCAS), pp 2925-2928 vol.4
1990
Abstract
A method for designing neural networks (NNs) for classifying contingencies in terms of the number and type of limit violations is presented. Specifically, an optimization method (in contrast to a learning method) for finding the weights and thresholds of an associated Little-Hopfield NN is developed. This optimization method, which uses the linear programming technique, maximizes the probability of classifying the contingency correctly. The contingency classification problem is formulated into a pattern recognition problem. A NN to detect a prescribed set of patterns is then designed.< >
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Details
- Title
- An improved Hopfield model for power system contingency classification
- Creators
- J Chow - Drexel UniversityR Fischl - Drexel UniversityM Kam - Drexel UniversityH.H Yan - Drexel UniversityS Ricciardi - Drexel University
- Publication Details
- 1990 IEEE International Symposium on Circuits and Systems (ISCAS), pp 2925-2928 vol.4
- Publisher
- IEEE
- Resource Type
- Conference proceeding
- Language
- English
- Other Identifier
- 991019346716304721