Name
Title | ||
|---|---|---|
Discriminative Deep Belief Networks with Ant Colony Optimization for Health Status Assessment of Machine. |
Abstract | ||
|---|---|---|
On-line health status monitoring, a key part of prognostics and health management, provides various benefits, such as preventing unexpected failure and improving safety and reliability. In this paper, a data-driven approach for health status assessment is presented. A novel method based on discriminative deep belief networks (DDBN) and ant colony optimization (ACO) is used to predict health status... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TIM.2017.2735661 | IEEE Transactions on Instrumentation and Measurement |
Keywords | Field | DocType |
Prognostics and health management,Maintenance engineering,Data models,Machine learning,Ant colony optimization,Monitoring | Ant colony optimization algorithms,Data modeling,Data mining,Boltzmann machine,Prognostics,Deep belief network,Support vector machine,Artificial intelligence,Discriminative model,Maintenance engineering,Mathematics,Machine learning | Journal |
Volume | Issue | ISSN |
66 | 12 | 0018-9456 |
Citations | PageRank | References |
4 | 0.42 | 16 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Meng Ma | 1 | 82 | 12.29 |
| Chuang Sun | 2 | 70 | 8.35 |
| XueFeng Chen | 3 | 441 | 55.44 |