K-means and alternative clustering methods in modern power systems

SM Miraftabzadeh, CG Colombo, M Longo… - Ieee …, 2023 - ieeexplore.ieee.org
As power systems evolve by integrating renewable energy sources, distributed generation,
and electric vehicles, the complexity of managing these systems increases. With the …

A systematic literature review of IoT time series anomaly detection solutions

A Sgueglia, A Di Sorbo, CA Visaggio… - Future Generation …, 2022 - Elsevier
The rapid spread of the Internet of Things (IoT) devices has prompted many people and
companies to adopt the IoT paradigm, as this paradigm allows the automation of several …

Adarnn: Adaptive learning and forecasting of time series

Y Du, J Wang, W Feng, S Pan, T Qin, R Xu… - Proceedings of the 30th …, 2021 - dl.acm.org
Time series has wide applications in the real world and is known to be difficult to forecast.
Since its statistical properties change over time, its distribution also changes temporally …

A deep neural network for unsupervised anomaly detection and diagnosis in multivariate time series data

C Zhang, D Song, Y Chen, X Feng, C Lumezanu… - Proceedings of the AAAI …, 2019 - aaai.org
Nowadays, multivariate time series data are increasingly collected in various real world
systems, eg, power plants, wearable devices, etc. Anomaly detection and diagnosis in …

Identification and classification of construction equipment operators' mental fatigue using wearable eye-tracking technology

J Li, H Li, W Umer, H Wang, X **_Measures_of_Cognitive_Impairment_in_the_Real_World_from_Consumer-Grade_Multimodal_Sensor_Streams/links/5ebecefb92851c11a86c1737/Develo**-Measures-of-Cognitive-Impairment-in-the-Real-World-from-Consumer-Grade-Multimodal-Sensor-Streams.pdf" data-clk="hl=sv&sa=T&oi=gga&ct=gga&cd=7&d=8427419775238302113&ei=o6e9Z5LkO8mr6rQP1uX_CA" data-clk-atid="oWkunKI19HQJ" target="_blank">[PDF] researchgate.net

Develo** measures of cognitive impairment in the real world from consumer-grade multimodal sensor streams

R Chen, F Jankovic, N Marinsek, L Foschini… - Proceedings of the 25th …, 2019 - dl.acm.org
The ubiquity and remarkable technological progress of wearable consumer devices and
mobile-computing platforms (smart phone, smart watch, tablet), along with the multitude of …

E2usd: Efficient-yet-effective unsupervised state detection for multivariate time series

Z Lai, H Li, D Zhang, Y Zhao, W Qian… - Proceedings of the ACM …, 2024 - dl.acm.org
Cyber-physical system sensors emit multivariate time series (MTS) that monitor physical
system processes. Such time series generally capture unknown numbers of states, each …

Multiview unsupervised shapelet learning for multivariate time series clustering

N Zhang, S Sun - IEEE Transactions on Pattern Analysis and …, 2022 - ieeexplore.ieee.org
Multivariate time series clustering has become an important research topic in the time series
learning task, which aims to discover the correlation among multiple sequences and …