배합 인자를 고려한 Deep Learning Algorithm을 이용한 콘크리트 압축강도 추정 기법에 관한 기초적 연구

A Basic Study on Estimation Method of Concrete Compressive Strength Based on Deep Learning Algorithm Considering Mixture Factor

  • 이승준 (한양대학교 건축시스템공학과) ;
  • 김인수 (여주대학교 건축공학과) ;
  • 이한승 (한양대학교 ERICA캠퍼스 건축학부)
  • 발행 : 2017.11.16

초록

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, seven influential factors (W/B ratio, 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. The purpose of this paper is to estimate compressive strength more accurately by applying it to algorithm of the Deep learning.

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