Abstracts – Browse Results
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Adeyeye, K (2024) From product to service – strategies for upscaling smart home performance monitoring. Building Research & Information, 52(01–02), 107–28.
Al-Aomar, R, AlTal, M and Abel, J (2024) A data-driven predictive maintenance model for hospital HVAC system with machine learning. Building Research & Information, 52(01–02), 207–24.
Božiček, D, Almezeraani, Y and Košir, M (2024) Making sense of LCA results when evaluating multiple building designs – comparison of interpretation concepts. Building Research & Information, 52(01–02), 129–47.
Calcerano, F, Thravalou, S, Martinelli, L, Alexandrou, K, Artopoulos, G and Gigliarelli, E (2024) Energy and environmental improvement of built heritage: HBIM simulation-based approach applied to nine Mediterranean case-studies. Building Research & Information, 52(01–02), 225–47.
Ghansah, F A, Owusu-Manu, D, Edwards, D J, Thwala, W D, Yamoah Agyemang, D and Ababio, B K (2024) A framework for smart building technologies implementation in the Ghanaian construction industry: a PLS-SEM approach. Building Research & Information, 52(01–02), 148–63.
Kalla, M, Kalaycioglu, O, Hecht, R, Schneider, S and Schmidt, C (2024) Station biophilia – assessing the perception of greenery on railway platforms using a digital twin. Building Research & Information, 52(01–02), 164–80.
Kumari, P, Reddy, S R N and Yadav, R (2024) Indoor occupancy detection and counting system based on boosting algorithm using different sensor data. Building Research & Information, 52(01–02), 87–106.
Lai, H and Chiang, W (2024) Generative design of terraced concert hall – a case study of Taipei music and library centre. Building Research & Information, 52(01–02), 49–67.
Liang, H, Weng, Y, Tang, S W Y and Yeoh, J K W (2024) Automated filtering of façade defect images using a similarity method for enhanced inspection documentation. Building Research & Information, 52(01–02), 194–206.
Prieto, A J, Torres-González, M and Carpio, M (2024) Virtual web-based instruments in the evaluation of functional degradation of heritage timber buildings. Building Research & Information, 52(01–02), 181–93.
Saeidlou, S and Ghadiminia, N (2024) A construction cost estimation framework using DNN and validation unit. Building Research & Information, 52(01–02), 38–48.
- Type: Journal Article
- Keywords: Deep learning; construction cost estimation; framework; validator;
- ISBN/ISSN: 0961-3218
- URL: https://doi.org/10.1080/09613218.2023.2196388
- Abstract:
Accurate construction cost estimation is crucial to completing projects within the planned timeframe and expenditure. The estimation process depends on multiple variables maintaining complex relationships between themselves and the target cost. As a result, an in-depth analysis from an experienced construction consultant is required to estimate construction costs accurately. Machine learning (ML) technology can learn from previous data, which is equivalent to human experience. Many project-specific ML models estimate the construction cost, which misses the generalizability. This paper addresses the gap and designs, develops, implements, and analyzes a deep learning (DL) based novel framework that maps 94.67% of the independent variables with a mean average percentage error (MAPE) of 11.60%. The proposed framework is not limited to any specific project. It estimates the construction cost of similar projects, further validated by an innovative estimator validation unit.
Yıldız, B, Çağdaş, G and Zincir, I (2024) Architectural space classification considering topological and 3D visual spatial relations using machine learning techniques. Building Research & Information, 52(01–02), 68–86.
Yang, X, Zhong, H, Wang, Z, Du, P, Zhou, K, Zhou, H, Lai, X, Lau, Y L, Song, Y and Tang, L (2024) BEKG: A built environment knowledge graph. Building Research & Information, 52(01–02), 19–37.
Zhou, S ( (2024) Platforming for industrialized building: a comparative case study of digitally-enabled product platforms. Building Research & Information, 52(01–02), 4–18.