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Smart contract research for data outlier detection and processing of ARIMA model

  • Min, Youn-A (Applied Software Engineering, Hanyang Cyber University)
  • Received : 2022.09.20
  • Accepted : 2022.09.25
  • Published : 2022.11.30

Abstract

In this study, in order to efficiently detect data patterns and outliers in time series data, outlier detection processing is performed for each section based on a smart contract in the data preprocessing process, and parameters for the ARIMA model are determined by generating and reflecting the significance and outlier-related parameters of the data. It was created and applied to the modified arithmetic expression to lower the data abnormality. To evaluate the performance of this study, the normality of the data was compared and evaluated when the parameters of the general ARIMA model and the ARIMA model through this study were applied, and a performance improvement of more than 6% was confirmed.

Keywords

References

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