다중 선형 회귀 기반 기계 학습을 이용한 인공지지체의 사각 기공 형태 진단 모델에 관한 연구

A Study on Square Pore Shape Discrimination Model of Scaffold Using Machine Learning Based Multiple Linear Regression

  • 이송연 (한국기술교육대학교대학원 메카트로닉스공학과) ;
  • 허용정 (한국기술교육대학교 메카트로닉스공학부)
  • Lee, Song-Yeon (Mechatronics Engineering, Graduate School of Korea University of Technology and Education) ;
  • Huh, Yong Jeong (Department of Mechatronics Engineering, Korea University of Technology and Education)
  • 투고 : 2020.11.27
  • 심사 : 2020.12.08
  • 발행 : 2020.12.31

초록

In this paper, we found the solution using data based machine learning regression method to check the pore shape, to solve the problem of the experiment quantity occurring when producing scaffold with the 3d printer. Through experiments, we learned secured each print condition and pore shape. We have produced the scaffold from scaffold pore shape defect prediction model using multiple linear regression method. We predicted scaffold pore shapes of unsecured print condition using the manufactured scaffold pore shape defect prediction model. We randomly selected 20 print conditions from various predicted print conditions. We print scaffold five times under same print condition. We measured the pore shape of scaffold. We compared printed average pore shape with predicted pore shape. We have confirmed the prediction model precision is 99 %.

키워드

참고문헌

  1. Song-Yeon Lee and Yong-Jeong Huh, "A Study on Prediction Model of Scaffold Pore Size Using Machine Learning", J. of The Korean Society of Semiconductor & Display Technology, Vol.18, pp. 46-50, 2019.
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  3. Song-Yeon Lee and Yong-Jeong Huh, "A Study on Prediction Model Performance of Scaffold Pore Size Using Machine Learning Regression Method", J. of The Korean Society of Semiconductor & Display Technology, Vol.19, pp. 36-41, 2020.
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