Acknowledgement
본 논문은 2022년 국토교통부/국토교통과학기술진흥원 연구사업(과제번호: 22AATD-C163269-02)의 일환으로 수행된 연구임을 밝히며 이에 감사를 드립니다.
Proceedings of the Korean Institute of Building Construction Conference (한국건축시공학회:학술대회논문집)
- 2022.04a
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- Pages.123-124
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- 2022
A Study on the Prediction Model of the Total Quantity of the Wall Finishing Structure Member Based on BIM Object Information Using Deep Learning
딥러닝을 활용한 BIM 객체정보기반의 벽마감 구조틀 부재 수량 예측모델에 관한 연구
- Published : 2022.04.20
Abstract
The work of modeling and calculating the quantity of detailed parts requires a lot of time and effort. However, The information of BIM Model can be used to predict the amount of uncreated parts with Deep Learning. In this study, Deep Learning was used to predict the total length of the member of frame that was not created. As a result, it was confirmed that the error rate was inside or outside 3%. And predicting other components in this way will increase productivity in Architectural field.