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Random forest based model for preventing large-scale emergencies in power systems

Статья в журнале
Tomin N.V., Zhukov, A., Sidorov D.N., Kurbatsky V.G., Spiryaev V.A., Panasetsky D.A.
International Journal of Artificial Intelligence
International Journal of Artificial Intelligence. Vol.3. No.1. P.211-228.
2015
Random forest based model for preventing large-scale emergencies in power systems
The novel adaptive hybrid models are proposed for time series forecasting and features classification problems. The proposed forecasting model combines the Hilbert–Huang transform and random forests. The efficiency of proposed adaptive approaches is demonstrated on two cases studies: wind power ramps prediction and detection of alarm states in a power systems.

Библиографическая ссылка

Tomin N.V., Zhukov, A., Sidorov D.N., Kurbatsky V.G., Spiryaev V.A., Panasetsky D.A. Random forest based model for preventing large-scale emergencies in power systems // International Journal of Artificial Intelligence. Vol.3. No.1. 2015. P.211-228. http://www.ceserp.com/cp-jour/index.php?journal=ijai&page=article&op=view&path%5B%5D=3583
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