<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>With the development of smart grids, power grids have accumulated massive amounts of data in various links such as power generation, transmission, substation, distribution, power consumption, and dispatch. More and more big data applications are beginning to be applied in various professional fields of the power grid. Promote the application and value discovery of smart grid big data through data fusion inside and outside the grid. Grid data has become an important asset for enterprise development, but power grid enterprises lack effective technical means to solve the whole life cycle monitoring and relationship of power grid data assets. Aiming at the relationship between power grid data assets, this paper proposes a set of grid data asset relationship and intelligent classification framework that integrates knowledge graph and Internet of Things. First, the grid knowledge graph extraction relationship is carried out by ProjE algorithm. Then, the relationship between power grid data assets and intelligent classification framework that integrates knowledge graph and Internet is proposed. Finally, the corresponding classification application is proposed by using intelligent classification algorithm. Experimental results show that the intelligent classification accuracy rate can reach 93.12% under the relationship between the knowledge graph and the Internet data assets, which has a new idea for the future development of the relationship between power grid data assets.</p>
</abstract>

With the development of smart grids, power grids have accumulated massive amounts of data in various links such as power generation, transmission, substation, distribution, power consumption, and dispatch. More and more big data applications are beginning to be applied in various professional fields of the power grid. Promote the application and value discovery of smart grid big data through data fusion inside and outside the grid. Grid data has become an important asset for enterprise development, but power grid enterprises lack effective technical means to solve the whole life cycle monitoring and relationship of power grid data assets. Aiming at the relationship between power grid data assets, this paper proposes a set of grid data asset relationship and intelligent classification framework that integrates knowledge graph and Internet of Things. First, the grid knowledge graph extraction relationship is carried out by ProjE algorithm. Then, the relationship between power grid data assets and intelligent classification framework that integrates knowledge graph and Internet is proposed. Finally, the corresponding classification application is proposed by using intelligent classification algorithm. Experimental results show that the intelligent classification accuracy rate can reach 93.12% under the relationship between the knowledge graph and the Internet data assets, which has a new idea for the future development of the relationship between power grid data assets.

Grid data asset relationship and intelligent classification integrating knowledge graph and Internet of Things

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

With the development of smart grids, power grids have accumulated massive amounts of data in various links such as power generation, transmission, substation,...

Grid data asset relationship and intelligent classification integrating knowledge graph and Internet of Things

Online veröffentlicht: 28. Apr. 2023

Seitenbereich: -

Eingereicht: 06. März 2022

Akzeptiert: 17. Juli 2022

DOI: https://doi.org/10.2478/amns.2023.1.00059

Schlüsselwörter
Knowledge graph, Internet of Things, Grid data asset relationships, Intelligent classification, Big data

© 2023 Le Ma et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Grid data asset relationship and intelligent classification integrating knowledge graph and Internet of Things

Online veröffentlicht: 28. Apr. 2023

Seitenbereich: -

Eingereicht: 06. März 2022

Akzeptiert: 17. Juli 2022

DOI: https://doi.org/10.2478/amns.2023.1.00059

SchlüsselwörterKnowledge graph, Internet of Things, Grid data asset relationships, Intelligent classification, Big data

© 2023 Le Ma et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Knowledge graph, Internet of Things, Grid data asset relationships, Intelligent classification, Big data