열처리공학회지 (Journal of the Korean Society for Heat Treatment)

  • 제34권5호
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  • Pages.211-217
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  • 2021
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  • 1225-1070(pISSN)
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  • 2508-4046(eISSN)
한국열처리공학회 (The Korean Society for Heat Treatment)
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인공지능을 활용한 기계학습 앙상블 모델 개발

Development of Machine Learning Ensemble Model using Artificial Intelligence

  • Lee, K.W. (School of Advanced Materials Engineering, Kookmin University) ;
  • Won, Y.J. (School of Advanced Materials Engineering, Kookmin University) ;
  • Song, Y.B. (Agency for Defense Development) ;
  • Cho, K.S. (School of Advanced Materials Engineering, Kookmin University)
  • 투고 : 2021.07.22
  • 심사 : 2021.08.30
  • 발행 : 2021.09.30
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⟨ 이전 논문 다음 논문 ⟩

초록

To predict mechanical properties of secondary hardening martensitic steels, a machine learning ensemble model was established. Based on ANN(Artificial Neural Network) architecture, some kinds of methods was considered to optimize the model. In particular, interaction features, which can reflect interactions between chemical compositions and processing conditions of real alloy system, was considered by means of feature engineering, and then K-Fold cross validation coupled with bagging ensemble were investigated to reduce R2_score and a factor indicating average learning errors owing to biased experimental database.

키워드

과제정보

본 논문은 정부(산업통산자원부)의 재원으로 산업기술평가관리원의 지원(No.20012296, 산업기술 알키미스트프로젝트)과 정부(국방부)의 재원으로 방위사업청의 지원을 받아 수행된 연구입니다(계약번호 UD170108GD, 국방과학연구소 연구용역 사업).

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