| Keywords
|
Recurrent Neural Networks, time series forecasting, supervised learning, Prognostics and Health Management, fault detection +
|
| Level
|
Master +
|
| OneLineSummary
|
Construct and optimise Recurrent Neural Networks for industrial applications on machine prognostics; Augmenting industrial data for supervised learning +
|
| Prerequisites
|
Artificial Intelligence and Learning Systems courses; good knowledge in machine learning and neural networks; programming skills for implementing machine learning algorithms +
|
| StudentProjectStatus
|
Finished +
|
| Supervisors
|
Sławomir Nowaczyk +
, Sepideh Pashami +
, Yuantao Fan +
|
| ThesisAuthor
|
Kunru Chen +
|
| TimeFrame
|
Fall 2017 +
|
| Title
|
Recurrent and Deep Learning for Machine Prognostics +
|
| Categories |
StudentProject +
|
| Modification dateThis property is a special property in this wiki.
|
14 October 2018 18:05:33 +
|
