Version 1
: Received: 23 July 2023 / Approved: 24 July 2023 / Online: 25 July 2023 (03:41:09 CEST)
How to cite:
Liu, H.; Jia, H.; Zhang, S.; Yan, L.; Zhao, Q.; Jiang, P.; Zhang, J. Knowledge Graph Construction and Application of Spatial Arrangement of Underground Powerhouse. Preprints2023, 2023071639. https://doi.org/10.20944/preprints202307.1639.v1
Liu, H.; Jia, H.; Zhang, S.; Yan, L.; Zhao, Q.; Jiang, P.; Zhang, J. Knowledge Graph Construction and Application of Spatial Arrangement of Underground Powerhouse. Preprints 2023, 2023071639. https://doi.org/10.20944/preprints202307.1639.v1
Liu, H.; Jia, H.; Zhang, S.; Yan, L.; Zhao, Q.; Jiang, P.; Zhang, J. Knowledge Graph Construction and Application of Spatial Arrangement of Underground Powerhouse. Preprints2023, 2023071639. https://doi.org/10.20944/preprints202307.1639.v1
APA Style
Liu, H., Jia, H., Zhang, S., Yan, L., Zhao, Q., Jiang, P., & Zhang, J. (2023). Knowledge Graph Construction and Application of Spatial Arrangement of Underground Powerhouse. Preprints. https://doi.org/10.20944/preprints202307.1639.v1
Chicago/Turabian Style
Liu, H., Peiqi Jiang and Jiaqi Zhang. 2023 "Knowledge Graph Construction and Application of Spatial Arrangement of Underground Powerhouse" Preprints. https://doi.org/10.20944/preprints202307.1639.v1
Abstract
Many parameters and complex boundaries are involved in the spatial arrangement of an under-ground powerhouse for a hydropower station, which requires reference to many relevant cases and specifications. However, in practical applications, retrieving relevant cases or specifications is difficult, and there is a lack of knowledge of cascading logic among design parameters. For this question, a targeted knowledge graph based on knowledge graph management technology is established to support subsequent applications. This paper proposes a new concept of con-structing a knowledge graph for building information modeling (BIM) underground power-houses of hydropower stations. Firstly, the ontology skeleton of hydropower station spatial ar-rangement design, which represents the knowledge organization structure of the knowledge graph, is reconstructed by carefully analyzing the requirements for intelligent modeling of un-derground powerhouses. A large amount of unstructured data is identified based on optical character recognition (OCR) technology and is divided into words to extract correlation knowledge based on THULAC. In the next step, the knowledge triad of the spatial arrangement of the underground powerhouse is extracted based on ChatGPT and stored in a Neo4j knowledge base to build a knowledge graph. Finally, the knowledge graph is serviced to realize the query of knowledge and parameter recommendation to assist the digital intelligent design of spatial arrangement of an underground powerhouse of pumped storage hydropower stations.
Keywords
Knowledge graph; Underground powerhouse of hydropower station; spatial arrangement; Digital intelligent design
Subject
Engineering, Architecture, Building and Construction
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
