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Advances in Informatics and Computing in Civil and Construction Engineering最新文献

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The BIM maturity process to the digital twin for lean strategic facility management 从BIM到数字化孪生的成熟过程,实现精益战略设施管理
Pub Date : 2023-07-10 DOI: 10.35490/ec3.2023.325
Alex Mbabu, J. Underwood, M. Munir
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引用次数: 0
A blockchain-based token economic model for incentivizing ESG in the construction industry 基于区块链的token经济模型,用于激励建筑行业的ESG
Pub Date : 2023-07-10 DOI: 10.35490/ec3.2023.235
Rui Zhao, Jiajia Wang, Fan Xue
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引用次数: 0
Ontology-based semantic labeling for RGB-D and point cloud datasets 基于本体的RGB-D和点云数据集语义标注
Pub Date : 2023-07-10 DOI: 10.35490/ec3.2023.241
Fabian Kaufmann, Mahdi Chamseddine, Suresh Guttikonda, Christian Glock, D. Stricker, J. Rambach
,
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引用次数: 0
Comparison of current common data environment tools in the construction industry 当前建筑行业常用数据环境工具的比较
Pub Date : 2023-07-10 DOI: 10.35490/ec3.2023.315
Klaudia Jaskula, E. Papadonikolaki, D. Rovas
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引用次数: 1
The RINNO solution: a holistic assessment framework for supporting building renovation projects RINNO解决方案:支持建筑改造项目的整体评估框架
Pub Date : 2023-07-10 DOI: 10.35490/ec3.2023.231
Vasileios Sougkakis, Ioannis Mamounakis, Petros Iliadis, Andreas Seitaridis, E. E. Lithoxoidou, Omar Doukari, Enrico Scoditti, N. Nikolopoulos, M. Kassem
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引用次数: 0
Representing modelica models as knowledge graphs using the moont ontology 使用月球本体将modelica模型表示为知识图
Pub Date : 2023-07-10 DOI: 10.35490/ec3.2023.173
Elisabeth Eckstädt, K. Menzel, H. Pruvost, D. Mayer
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引用次数: 0
Using machine learning for automated detection of ambiguity in building requirements 使用机器学习自动检测建筑需求中的模糊性
Pub Date : 2023-07-10 DOI: 10.35490/ec3.2023.211
Zijing Zhang, Ling Ma
The rule interpretation step is yet to be fully automated in the compliance checking process, which hinders the automation of compliance checking. Whilst existing research has developed numerous methods for automated interpretation of building requirements, none of them can identify or address ambiguous requirements. As part of interpreting ambiguous clauses automatically, this research proposed a supervised machine learning method to detect ambiguity automatically, where the best-performing model achieved recall, precision and accuracy scores of 99.0%, 71.1%, and 78.2%, respectively. This research contributes to the body of knowledge by developing a method for automated detection of ambiguity in building requirements to support automated compliance checking.
在遵从性检查过程中,规则解释步骤尚未完全自动化,这阻碍了遵从性检查的自动化。虽然现有的研究已经开发了许多自动解释建筑需求的方法,但它们都不能识别或处理模糊的需求。作为自动解释歧义从句的一部分,本研究提出了一种有监督的机器学习方法来自动检测歧义,其中表现最好的模型分别达到了99.0%,71.1%和78.2%的召回率,精度和准确度得分。本研究通过开发一种自动检测构建需求中的模糊性的方法来支持自动遵从性检查,从而为知识体系做出了贡献。
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引用次数: 0
Increasing the accuracy of low-resolution commercial smart heat meter data and analysing its error 提高低分辨率商用智能热量表数据的精度及误差分析
Pub Date : 2023-07-10 DOI: 10.35490/ec3.2023.208
Markus Schaffer, D. Leiria, J. E. Vera-Valdés, A. Marszal-Pomianowska
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引用次数: 0
Design of an IoT infrastructure during bridge renovation: a practical experience from mosore project 桥梁改造过程中物联网基础设施的设计:来自更多项目的实践经验
Pub Date : 2023-07-10 DOI: 10.35490/ec3.2023.322
S. Rinaldi, P. Ferrari, A. Flammini, Adriano Reggia, G. Plizzari, G. Maternini
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引用次数: 0
Requirements and framework for Gaia-x-based building permit processes 基于gaia -x的建筑许可流程的要求和框架
Pub Date : 2023-07-10 DOI: 10.35490/ec3.2023.216
J. Fauth, C. Strnadl, Hannes Heitzhausen, Morris Florek, M. Brenner, S. Seiß, Pintu Nakrani, Aurica Poetz, Joaquín Díaz, Wolfgang Mueller
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引用次数: 0
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Advances in Informatics and Computing in Civil and Construction Engineering
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