A novel approach towards predicting faults in power systems using machine learning
Author:
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Electrical and Electronic Engineering
Link
https://link.springer.com/content/pdf/10.1007/s00202-021-01428-w.pdf
Reference23 articles.
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3. Li TK, Tsai CH, Hsu HC (2012) A fast fault-identification algorithm for bijective connection graphs using the PMC model. Inf Sci 187:291–297. https://doi.org/10.1016/j.ins.2011.10.022
4. Cardoso G, Rolim JG, Zürn H (2004) Application of neural network modules to electric power system fault section estimation. IEEE Trans Power Deliv. https://doi.org/10.1109/PES.2004.1372767
5. Srinivasan D, Cheu RL, Poh YP, Ng AKC (2000) Automated fault detection in power distribution networks using a hybrid fuzzy–genetic algorithm approach. Eng Appl Artif Intell 13(4):407–418. https://doi.org/10.1016/S0952-1976(00)00012-9
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