Yong Guan
Automotive Engineering · with Wu · 2016–2017
A researcher in the Science corpus: 2 papers; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Automotive Engineering — 17 citations into it
- Control and Systems Engineering — 13 citations into it
- Safety, Risk, Reliability and Quality — 11 citations into it
- Mechanical Engineering — 5 citations into it
- Mechanics of Materials — 5 citations into it
Whom Yong Guan trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Papers from Yong Guan's perspective
Ordered by how strongly the researchers Yong Guan trusts endorse each paper. Same corpus, a different order for every researcher.
- Prognostics of lithium-ion batteries based on DempsterShafer theory and the Bayesian Monte Carlo me
- A review on prognostics and health monitoring of Li-ion battery
- An ensemble model for predicting the remaining useful performance of lithium-ion batteries (Microelectronics and reliability)
- Health diagnosis and remaining useful life prognostics of lithium-ion batteries using data-driven methods
- A Survey on Transfer Learning
- Remaining useful life estimation - A review on the statistical data driven approaches (European Journal of Operational Research)
- Remaining useful life prediction of lithium-ion battery with unscented particle filter technique (Microelectronics and reliability)
- A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches (IEEE transactions on industrial electronics (1982. Print))
- Learning and Transferring Mid-level Image Representations Using Convolutional Neural Networks
- Deep neural networks: A promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data