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- W2079682314 abstract "Machine learning methods are promising tools for transient stability assessment (TSA) of power system. Support vector machine (SVM) is used to assess the transient stability of power system after faults occur on transmission lines. Single machine attributes is studied as inputs of the SVM classifier. Experimental results in IEEE 50-generator test system shows that, attributes of single machine with small inertia coefficient are effective in TSA, and the SVM classifier with RBF kernel using these single machine attributes can achieve satisfying classification accuracy." @default.
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- W2079682314 date "2007-01-01" @default.
- W2079682314 modified "2023-09-27" @default.
- W2079682314 title "Transient Stability Assessment of Power System Based on Support Vector Machine" @default.
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- W2079682314 doi "https://doi.org/10.2991/iske.2007.143" @default.
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