Application of Big Data Analytics and Machine Learning to Large-Scale Synchrophasor Datasets: Evaluation of Dataset ‘Machine Learning-Readiness’

Application of Big Data Analytics and Machine Learning to Large-Scale Synchrophasor Datasets: Evaluation of Dataset ‘Machine Learning-Readiness’

This manuscript presents a data quality analysis and holistic ‘machine learning-readiness’ evaluation of a representative set of large-scale, real-world phasor measurement unit (PMU) datasets provided under the United States Department of Energy-funded FOA 1861 research program...

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Bibliographic Details
Main Authors: Philip Hart, Lijun He, Tianyi Wang, Vijay S. Kumar, Kareem Aggour, Arun Subramanian, Weizhong Yan
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Open Access Journal of Power and Energy
Subjects:
Phasor measurement units
synchrophasor datasets
statistical analysis
data quality analysis
label quality
nonymized datasets
Online Access:https://ieeexplore.ieee.org/document/9852477/

Internet

https://ieeexplore.ieee.org/document/9852477/

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