Name
Abstract | ||
|---|---|---|
The technological development of the energy sector also produced complex data. In this study, the relationship between smart grid and big data approaches have been investigated. After analyzing which areas of the smart grid system use big data technologies and technologies, big data technologies for detecting smart grid attacks have received attention. Big data analytics can produce efficient solutions and it is especially important to choose which algorithms and metrics to use. For this reason, an application prototype has been proposed that uses a big data method to detect attacks on the smart grid. The algorithm with high accuracy was determined to be 92% for random forests and 87% for decision trees. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/IWCMC.2019.8766348 | 2019 15TH INTERNATIONAL WIRELESS COMMUNICATIONS & MOBILE COMPUTING CONFERENCE (IWCMC) |
Field | DocType | ISSN |
Decision tree,Smart grid,Computer science,Complex data type,Random forest,Energy sector,Big data,Distributed computing | Conference | 2376-6492 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| ZhiFeng Li | 1 | 1073 | 55.45 |
| Yintao Li | 2 | 0 | 0.68 |
| peng lin | 3 | 39 | 12.10 |