Name
Title | ||
|---|---|---|
Application Of Knowledge Graph Technology In Unified Management Platform For Wind Power Data |
Abstract | ||
|---|---|---|
The data from the field has reached a new stage in scale and type with the development of the wind power industry. They are scattered in each business department, it will be of great help to the industry if these data are managed and applied uniformly. Therefore, a wind power data management method knowledge graph-based is proposed. Firstly, the knowledge graph elements including entity, relation, and property are extracted from multi-source wind power data. And the extraction methods for structured and unstructured data are given respectively in this step. Then, the obtained elements are used to construct a panoramic knowledge graph of wind power data in the graph database Neo4j to complete the connection between different types and business data. Finally, the typical case such as fault reasoning and business query is compared with the traditional management mode based on relational database, the results show that the method proposed in this paper has a better application effect. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/IECON43393.2020.9255141 | IECON 2020: THE 46TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY |
Keywords | DocType | ISSN |
wind power data, knowledge graph, Neo4j graphical database, fault reasoning, business query | Conference | 1553-572X |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mengping Lv | 1 | 0 | 0.34 |
| Bin Duan | 2 | 0 | 0.34 |
| Haihui Jiang | 3 | 0 | 0.34 |
| Dong Deng | 4 | 0 | 0.34 |