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researcher

Rui Fan

4 papers hereh-index 13866 citations31 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • eess.SP2
  • cs.LG1
  • eess.SY1
same name
  • Rui Fan — 54 papers, h 31
  • Rui Fan — 19 papers, h 11
  • Rui Fan — 10 papers, h 8
  • Rui Fan — 7 papers, h 8
  • Rui Fan — 7 papers, h 5
  • Rui Fan — 5 papers, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedAdaptive Power System Emergency Control using Deep Reinforcement Learning

17 citations · 35 across the 4 of their papers we have counts for

collaborators

4 papers

eess.SP2019★ 7 cited

Parameters Calibration for Power Grid Stability Models using Deep Learning Methods

Renke Huang, Rui Fan, Tianzhixi Yin +2

This paper presents a novel parameter calibration approach for power system stability models using automatic data generation and advanced deep learning technology. A PMU-measuremen…

cs.LG2019★ 17 cited

Adaptive Power System Emergency Control using Deep Reinforcement Learning

Qiuhua Huang, Renke Huang, Weituo Hao +3

Power system emergency control is generally regarded as the last safety net for grid security and resiliency. Existing emergency control schemes are usually designed off-line based…

eess.SP2019★ 8 cited

Convolutional Neural Network and Transfer Learning for High Impedance Fault Detection

Rui Fan, Tianzhixi Yin

This letter presents a novel high impedance fault (HIF) detection approach using a convolutional neural network (CNN). Compared to traditional artificial neural networks, a CNN off…

eess.SY2017★ 3 cited

A Comparative Study of Interface Techniques for Transmission and Distribution Dynamic Co-Simulation

Qiuhua Huang, Renke Huang, Rui Fan +5

Transmission and distribution dynamic co-simulation is a practical and effective approach to leverage existing simulation tools for transmission and distribution systems to simulat…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.