Lifecycle Cost Analysis of Buildings Integrating BIM and Big Data Technologies
This study proposes a comprehensive system integrating Building Information Modeling (BIM) with big data and ensemble machine learning techniques to significantly enhance the accuracy of building lifecycle cost predictions, reducing mean squared error from 160,000 to 54,280 and achieving a coefficient of determination of 0.93 based on an analysis of over 3,500 years of data from 120 buildings.
Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
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