Machine learning approach to predict physical properties of polypropylene composites: application of mlr, dnn, and random forest to industrial data

HIGHLIGHTS

• who: Chonghyo Joo et al. from the Department of Chemical and Biomolecular Engineering, Yonsei University, Yonsei-ro, Seodaemun-gu have published the research work: Machine Learning Approach to Predict Physical Properties of Polypropylene Composites: Application of MLR, DNN, and Random Forest to Industrial Data, in the Journal: Polymers 2022, 14, x FOR PEER REVIEW of /2022/
• what: The novel and major contributions of this study are as follows: This study proposed and compared prediction models by training recipe-based data from a real PP composites plant. In this study, models were developed for the prediction . . .
  

   

  

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