Design and Implementation of Best Master Clock Selection Algorithm Based on FPGA

Liu, Panwang; Yang, Ruijin; Liu, Songyan; He, Qing

doi:10.1109/iiotbdsc57192.2022.00011

Cited by 2 publications

(1 citation statement)

References 12 publications

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“…In terms of data cleaning, currently single data cleaning algorithms mainly include nearest neighbour filling method [6] and mean filling method [7] , while hot card filling method and regression filling method [8] complete data cleaning from statistical level. In terms of data feature extraction, there are feature extraction based on covariance calculation [9] and machine learning methods based on random forest [10] and decision tree classifier [11] .…”

Section: Introductionmentioning

confidence: 99%

LES based power quality data feature extraction and Thompson Tau data cleaning

Liu,

Chen,

et al. 2023

International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2023)

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As power system see increasing application of big data and artificial intelligence, the new generation of power quality data requires cross-platform interaction, larger database support volume, and higher data processing speed, which makes traditional power quality data collection and processing methods difficult to adapt to the power grid development. This paper proposes a power quality Thompson tau algorithm data cleaning strategy based on LES feature extraction, first extract LES feature value of power quality data and cluster partition of the eigenvalues, and then, according to the power quality characteristics of the data partition, divide the sub-interval step flexibly for Thompson tau data cleaning and multipoint interpolation data filling. Finally, power quality data from a practical power grid is taken as an example and the simulation results verify the feasibility and accuracy of the proposed method.

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Section: Introductionmentioning

confidence: 99%