Name
Title | ||
|---|---|---|
Data quality improvement method based on data correlation for power Internet of Things |
Abstract | ||
|---|---|---|
In the current power Internet of Things, there are confusions in business data management, data models are not unified, and data loss problems are serious. Aiming at the problem of data loss, this paper proposes a new data quality improvement method for power IoT data The method divides the data into time-dependent sequence data and time-random sequence data depending on whether the data has relevance. According to the degree of data loss, the data is divided into severe missing data and a small amount of missing data. Finally, according to the divided data types, the data is complemented by the ARIMA model, the average interpolation method, etc. and the completed data sequence is obtained. After that, experiments were carried out using simulation data based on real data, and the reliability of the method was proved. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ISCID.2019.10142 | 2019 12th International Symposium on Computational Intelligence and Design (ISCID) |
Keywords | DocType | Volume |
Data completion,ARIMA,Data correlation | Conference | 2 |
ISSN | ISBN | Citations |
2165-1701 | 978-1-7281-4654-6 | 0 |
PageRank | References | Authors |
0.34 | 5 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dong Li | 1 | 475 | 67.20 |
| Yan Li | 2 | 141 | 32.35 |
| Y. H. Liu | 3 | 40 | 16.40 |
| Qilin Yin | 4 | 0 | 0.34 |
| Shuangshuang Guo | 5 | 0 | 0.68 |
| Haijie Zheng | 6 | 0 | 0.34 |