Dong Yang

Control and Systems Engineering · with Wang · 2019

A researcher in the Science corpus: 1 paper; trusts 17 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Dong Yang trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Haidong Shao
  2. Charles R. Farrar
  3. Zhuyun Chen
  4. Abdenour Soualhi
  5. Zhiwei Gao
  6. David W. Hosmer Jr.
  7. Feng Jia
  8. Hongkai Jiang
  9. Chen Lu
  10. P. J. García Nieto

Papers from Dong Yang's perspective

Ordered by how strongly the researchers Dong Yang trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Deep Learning
  2. A sparse auto-encoder-based deep neural network approach for induction motor faults classification
  3. Bearing Health Monitoring Based on Hilbert–Huang Transform, Support Vector Machine, and Regression (IEEE Transactions on Instrumentation and Measurement)
  4. Bearing Fault Detection by a Novel Condition-Monitoring Scheme Based on Statistical-Time Features and Neural Networks (IEEE transactions on industrial electronics (1982. Print))
  5. Deep neural networks: A promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data
  6. Accurate bearing remaining useful life prediction based on Weibull distribution and artificial neural network
  7. An enhancement deep feature fusion method for rotating machinery fault diagnosis
  8. A novel bearing fault diagnosis model integrated permutation entropy, ensemble empirical mode decomposition and optimized SVM
  9. Random Forests
  10. Deep learning and its applications to machine health monitoring (Mechanical systems and signal processing)

Their papers