Name
Title | ||
|---|---|---|
Empirical Sensitivity Analysis of Discretization Parameters for Fault Pattern Extraction From Multivariate Time Series Data |
Abstract | ||
|---|---|---|
It has been a challenge to find patterns in a time series of sensor data for fault detection in a system. Since it is usually not straightforward to discover meaningful features and rules directly from complex time series, data discretization has been popularly employed to reduce data size while preserving meaningful features from the original data, for which the choice of appropriate discretizati... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TCYB.2016.2540657 | IEEE Transactions on Cybernetics |
Keywords | Field | DocType |
Time series analysis,Sensitivity analysis,Market research,Fault detection,Data models,Probability density function,Feature extraction | Data mining,Data modeling,Time series,Discretization,State vector,Data set,Computer science,Fault detection and isolation,Feature extraction,Artificial intelligence,Machine learning,Discretization of continuous features | Journal |
Volume | Issue | ISSN |
47 | 5 | 2168-2267 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sujeong Baek | 1 | 5 | 1.77 |
| Duck Young Kim | 2 | 7 | 3.83 |