인공신경망 기반 석면 해체·제거작업 후 비산 석면 농도 예측 모델 개발

Development of an ANN based Model for Predicting Scattering Asbestos Concentration during Demolition Works

  • 김도현 (인하대학교 건축학부(건축공학전공)) ;
  • 김민수 (인하대학교 건축학부(건축공학전공)) ;
  • 이재우 (인하대학교 건축학부(건축공학전공)) ;
  • 한승우 (인하대학교 건축학부)
  • 발행 : 2022.11.10

초록

There is an increasing demand for prediction of asbestos concentration which has an fatal effect on human body. While demolishing asbestos, the dust scatters and makes workers be exposed to danger. Up to this date, however, factors that particularly influences have not considered in predicting asbestos concentration. Most of the studies could not quantify the distribution of asbestos. Also, they did not use nominal data on buildings as important factors. Therefore, this study aims to build an asbestos concentration prediction model by quantifying distribution of asbestos and using nominal data of buildings based on Artificial Neural Network (ANN). This model can give significant contribution of improving the safety of workers and be useful for finding effective ways to demolish asbestos in planning.

키워드

과제정보

본 논문은 한국연구재단의 지원(과제번호 2021R1A2C1007467)으로 수행된 연구이며, 이에 감사를 드립니다.