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2008.09384
Cited By

Evaluating Machine Learning Models for the Fast Identification of
Contingency Cases

Evaluating Machine Learning Models for the Fast Identification of Contingency Cases

21 August 2020

Florian Schaefer

ArXiv (abs)PDF HTML

Papers citing "Evaluating Machine Learning Models for the Fast Identification of Contingency Cases"

5 / 5 papers shown

Robust N-1 secure HV Grid Flexibility Estimation for TSO-DSO coordinated
Congestion Management with Deep Reinforcement Learning

Robust N-1 secure HV Grid Flexibility Estimation for TSO-DSO coordinated Congestion Management with Deep Reinforcement Learning

83

5

0

10 Nov 2022

Fast Power system security analysis with Guided Dropout

Fast Power system security analysis with Guided Dropout

Benjamin Donnot

Isabelle M Guyon

Marc Schoenauer

124

29

0

30 Jan 2018

Supervised Learning for Optimal Power Flow as a Real-Time Proxy

Supervised Learning for Optimal Power Flow as a Real-Time ProxyIEEE PES Innovative Smart Grid Technologies Conference (ISGT), 2016

Raphaël Canyasse

Gal Dalal

117

40

0

20 Dec 2016

XGBoost: A Scalable Tree Boosting System

XGBoost: A Scalable Tree Boosting System

Carlos Guestrin

1.4K

47,793

0

09 Mar 2016

SMOTE: Synthetic Minority Over-sampling Technique

SMOTE: Synthetic Minority Over-sampling TechniqueJournal of Artificial Intelligence Research (JAIR), 2002

Kevin W. Bowyer

1.2K

28,439

0

09 Jun 2011