한국공간구조학회지 제20권 제4호 (p.111-121)

대공간 구조물의 UHPC 적용을 위한 기계학습 기반 강도예측기법

Machine Learning Based Strength Prediction of UHPC for Spatial Structures
키워드 :
UHPC,Spatial structure,Machine learning,Strength prediction,Deep learning

목차

Abstract
1. 서론
2. 데이터 세트
   2.1 110 데이터 샘플
   2.2 데이터 샘플의 통계적 분석
3. 특성 엔지니어링
   3.1 특성 선별
   3.2 특성 구축
4. UHPC 데이터를 위한 회귀모델
   4.1 CatBoost
   4.2 평가 기법
   4.3 하이퍼파라미터 조정
5. 결과 및 고찰
6. 결론
References

초록

There has been increasing interest in UHPC (Ultra-High Performance Concrete) materials in recent years. Owing to the superior mechanical properties and durability, the UHPC has been widely used for the design of various types of structures. In this paper, machine learning based compressive strength prediction methods of the UHPC are proposed. Various regression-based machine learning models were built to train dataset. For train and validation, 110 data samples collected from the literatures were used. Because the proportion between the compressive strength and its composition is a highly nonlinear, more advanced regression models are demanded to obtain better results. The complex relationship between mixture proportion and concrete compressive strength can be predicted by using the selected regression method.