Change-point detection in industrial data streams based on online dynamic mode decomposition with control
We propose a novel change-point detection method based on online Dynamic Mode
Decomposition with control (ODMDwC). Leveraging ODMDwC's ability to find and track …
Decomposition with control (ODMDwC). Leveraging ODMDwC's ability to find and track …
Identification of Rock Layer Interface Characteristics Using Drilling Parameters
S Long, Z Yue, WV Yue, H Hu, Y Feng, Y Yan… - Rock Mechanics and …, 2024 - Springer
Characteristics of interface between rock layers significantly affect the stability of the support
structure in underground excavation. However, there is a lack of in-situ test to probe …
structure in underground excavation. However, there is a lack of in-situ test to probe …
[HTML][HTML] Non-intrusive load monitoring based on MoCo_v2, time series self-supervised learning
T Chen, J Gao, Y Yuan, S Guo, P Yang - Energy and Buildings, 2024 - Elsevier
Traditional non-intrusive load monitoring (NILM) methods rely on massive historical labeled
data. However, due to the privacy and high labeling cost of datasets, their generality and …
data. However, due to the privacy and high labeling cost of datasets, their generality and …
Normalizing self-supervised learning for provably reliable Change Point Detection
Change point detection (CPD) methods aim to identify abrupt shifts in the distribution of input
data streams. Accurate estimators for this task are crucial across various real-world …
data streams. Accurate estimators for this task are crucial across various real-world …