Knowledge graph construction and Internet of Things optimisation for power grid data knowledge extraction

Problems exist in power grid data management that have unclear relationships, weak security and low accuracy. By analysing the knowledge graph construction characteristics of smart grid data information and knowledge extraction, the grid data management platform is reshaped architecturally, and the...

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Main Authors: Sun Xiangju, Hao Ting, Li Xing
Format: Article
Language:English
Published: Sciendo 2023-01-01
Series:Applied Mathematics and Nonlinear Sciences
Subjects:
Online Access:https://doi.org/10.2478/amns.2021.2.00283
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author Sun Xiangju
Hao Ting
Li Xing
author_facet Sun Xiangju
Hao Ting
Li Xing
author_sort Sun Xiangju
collection DOAJ
description Problems exist in power grid data management that have unclear relationships, weak security and low accuracy. By analysing the knowledge graph construction characteristics of smart grid data information and knowledge extraction, the grid data management platform is reshaped architecturally, and the knowledge graph construction technology is embedded in the grid data management framework. For the aforementioned problems, the knowledge graph construction and Internet of Things optimisation framework of power grid data knowledge extraction are proposed in this article. Firstly, the semantic search (KGSS) algorithm based on the knowledge graph is used. The KGSS algorithm extracts knowledge from structured, semi-structured and unstructured grid data through the massively parallel processing acquisition model and Hadoop database, and constructs knowledge entities, attributes and inter-entity relationships. Then, it optimises and predicts through the knowledge graph construction and Internet of Things optimisation framework extracted from power grid data knowledge. Finally, the experimental results show that the accuracy rate of the KGSS algorithm is 92%. The experimental results also show that it provides new ideas and research directions for power grid data under big data in the future.
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spelling doaj.art-fe488b52ea36421d8ef46ea3304330712023-09-11T07:01:08ZengSciendoApplied Mathematics and Nonlinear Sciences2444-86562023-01-01812729273810.2478/amns.2021.2.00283Knowledge graph construction and Internet of Things optimisation for power grid data knowledge extractionSun Xiangju0Hao Ting1Li Xing21Internet Division of State Grid Gansu Electric Power Company, Lanzhou, 730030, China1Internet Division of State Grid Gansu Electric Power Company, Lanzhou, 730030, China2Gansu Tongxing Intelligent Technology Development Co. LTD, Lanzhou, 730030, ChinaProblems exist in power grid data management that have unclear relationships, weak security and low accuracy. By analysing the knowledge graph construction characteristics of smart grid data information and knowledge extraction, the grid data management platform is reshaped architecturally, and the knowledge graph construction technology is embedded in the grid data management framework. For the aforementioned problems, the knowledge graph construction and Internet of Things optimisation framework of power grid data knowledge extraction are proposed in this article. Firstly, the semantic search (KGSS) algorithm based on the knowledge graph is used. The KGSS algorithm extracts knowledge from structured, semi-structured and unstructured grid data through the massively parallel processing acquisition model and Hadoop database, and constructs knowledge entities, attributes and inter-entity relationships. Then, it optimises and predicts through the knowledge graph construction and Internet of Things optimisation framework extracted from power grid data knowledge. Finally, the experimental results show that the accuracy rate of the KGSS algorithm is 92%. The experimental results also show that it provides new ideas and research directions for power grid data under big data in the future.https://doi.org/10.2478/amns.2021.2.00283grid dataknowledge extractionknowledge graphinternet of thingspower grid
spellingShingle Sun Xiangju
Hao Ting
Li Xing
Knowledge graph construction and Internet of Things optimisation for power grid data knowledge extraction
Applied Mathematics and Nonlinear Sciences
grid data
knowledge extraction
knowledge graph
internet of things
power grid
title Knowledge graph construction and Internet of Things optimisation for power grid data knowledge extraction
title_full Knowledge graph construction and Internet of Things optimisation for power grid data knowledge extraction
title_fullStr Knowledge graph construction and Internet of Things optimisation for power grid data knowledge extraction
title_full_unstemmed Knowledge graph construction and Internet of Things optimisation for power grid data knowledge extraction
title_short Knowledge graph construction and Internet of Things optimisation for power grid data knowledge extraction
title_sort knowledge graph construction and internet of things optimisation for power grid data knowledge extraction
topic grid data
knowledge extraction
knowledge graph
internet of things
power grid
url https://doi.org/10.2478/amns.2021.2.00283
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AT haoting knowledgegraphconstructionandinternetofthingsoptimisationforpowergriddataknowledgeextraction
AT lixing knowledgegraphconstructionandinternetofthingsoptimisationforpowergriddataknowledgeextraction