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About Combining Deep Learning and Survival Analysis For Asset Health Management
This document proposes combining deep learning and survival analysis to predict asset health. Specifically, it proposes a three-layer model with a Long Short Term Memory layer to extract features from sequential input data, a neural network layer to further learn representations, and a survival model layer to predict failure probabilities. This combined approach integrates feature extraction and prediction into a single optimization task. The model was tested on datasets from mining haul trucks and hard drives, showing promising results in producing "individualized" failure probability assessments for each asset.
Detailed Information
| Author: | ['gadjo95'] |
|---|---|
| Publication Year: | 2017 |
| Pages: | 7 |
| Language: | English |
| Format: | |
| Price: | FREE |
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