.png){kind=icon}
返回
Time-based detection of changes to multivariate patterns
.png){kind=icon}
PRE
AI
DOI：10.1007/s10479-009-0610-8.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Detection of changes to multivariate patterns is an important topic in a number of different domains. Modern data sets often include categorical and numerical data and potentially complex in-control regions. Given a flexible, robust decision rule for this environment that signals based on an individual observation vector, an important issue is how to extend the rule to incorporate time-based information. A decision rule can be learned to detect shifts through artificial data that transforms the problem to one of supervised learning. Then class probability ratios are derived from a relationship to likelihood ratios to form the basis for time-weighted updates of the monitoring scheme.
Keyword:
Time-based detection of changes
Multivariate patterns
Supervised learning
期刊
IF:
4.5
论文数:
8.1K
被引数:
2.1W
机构
引用论文
分享收藏Real-Time Analysis of a Modified State Observer for Sensorless Induction Motor Drive Used in Electric Vehicle Applications.png)
Energies
OAAI
EnergiesIF0
OAAI分享收藏分享收藏
查看更多内容