배합 인자를 고려한 Machine Learning Algorithm 기반 콘크리트 압축강도 추정 기법에 관한 연구

Title
배합 인자를 고려한 Machine Learning Algorithm 기반 콘크리트 압축강도 추정 기법에 관한 연구
Other Titles
A Study on the Estimation Method of Concrete Compressive Strength Based on Machine Learning Algorithm Considering Mixture Factor
Author
이한승
Keywords
압축강도; 배합 인자; 머신 러닝; Compressive Strength; Mixture Factor; Machine Learning
Issue Date
2017-05
Publisher
한국건축시공학회
Citation
2017년 춘계학술발표대회 논문집, v. 17, No. 1, Page. 152-153
Abstract
In the construction site, it is necessary to estimate the compressive strength of concrete in order to adjust the demolding time of the form, and establish and adjust the construction schedule. The compressive strength of concrete is determined by various influencing factors. However, the conventional method for estimating the compressive strength of concrete has been suggested by considering only 1 to 3 specific influential factors as variables. In this study, six influential factors (Water, Cement, Fly ash, Blast furnace slag, Curing temperature, and humidity) of papers opened for 10 years were collected at three conferences in order to know the various correlations among data and the tendency of data. After using algorithm of various methods of machine learning techniques, we selected the most suitable regression analysis model for estimating the compressive strength.
URI
http://kic.or.kr/wp2017a/SessionView.asp?code=13&idx=1492http://repository.hanyang.ac.kr/handle/20.500.11754/72060
Appears in Collections:
COLLEGE OF ENGINEERING SCIENCES[E](공학대학) > ARCHITECTURE(건축학부) > Articles
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