원문정보
국제인공지능학회(구 한국인터넷방송통신학회)
International Journal of Internet, Broadcasting and Communication
Vol.14 No.4
2022.11
pp.140-147
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
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 outlierrelated 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.
목차
Abstract
1. Introduction
2. Related work
2.1 ARIMA
2.2 Smart contract
3. Smart contract research for data outlier detection and processing of ARIMA model
3.1 Modeling & Research method
3.2 Experiment and performance evaluation
4. Discussion
References
1. Introduction
2. Related work
2.1 ARIMA
2.2 Smart contract
3. Smart contract research for data outlier detection and processing of ARIMA model
3.1 Modeling & Research method
3.2 Experiment and performance evaluation
4. Discussion
References
키워드
저자정보
참고문헌
자료제공 : 네이버학술정보