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Research on Neural-Network-Based Transient Stability Assessment

Author: ZhangWenChao
Tutor: GuXuePing
School: North China Electric Power University
Course: Proceedings of the
Keywords: Transient Stability Assessment Artificial Neural Networks Pattern Classification Feature selection Separability criterion Sample set compression
CLC: TM712
Type: Master's thesis
Year: 2002
Downloads: 136
Quote: 3
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Abstract


Input feature selection and input space dimensionality reduction is the most important issue of the neural network - based transient stability assessment . Stable classification results accuracy rate is mainly determined by the separability of the input space composed by the selected feature . This paper summarizes proposed for stability classification system characteristics , several classification input transient stability analysis of the spatial separability , and Tabu search technology from a dimension larger feature set selected characteristics , and achieved good results ; Fisher linear recognition technology to compress the training sample set method , greatly reducing the the ANN training burden , to improve the performance of the ANN convergence .

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CLC: > Industrial Technology > Electrotechnical > Transmission and distribution engineering, power network and power system > Theory and Analysis > Power system stabilizer
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