An ontology for automated fault detection & diagnostics of HVAC using BIM and machine learning concepts-Reference-Cited by-同舟云学术

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An ontology for automated fault detection & diagnostics of HVAC using BIM and machine learning concepts

Published:2024-07 Issue:8 Volume:30 Page:972-988
ISSN:2374-4731
Container-title:Science and Technology for the Built Environment
language:en
Short-container-title:Science and Technology for the Built Environment

Author:

Hosseini Gourabpasi Arash¹^ORCID,Nik-Bakht Mazdak¹^ORCID

Affiliation:

1. Compleccity Lab, Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, QC, Canada

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/23744731.2024.2363104

Reference42 articles.

1. Abdoul-Wali, F. 2019. Fault detection and localization using IFC: A case study of BIM-based visualisation of BAS-related faults. CIBSE Technical Symposium, 17.

2. ASHRAE’s BACnet Committee Project Haystack and Brick Schema Collaborating to Provide Unified Data Semantic Modeling Solution | Ashrae.Org. 2024. Accessed March 9. https://www.ashrae.org/about/news/2018/ashrae-s-bacnet-committee-project-haystack-and-brick-schema-collaborating-to-provide-unified-data-semantic-modeling-solution

3. Brick : Metadata schema for portable smart building applications

4. A novel approach for learning ontology from relational database: from the construction to the evaluation

5. Blazegraph Database. 2023. Accessed July 24. https://blazegraph.com/

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