Machine Learning Approach to Predict Physical Properties of Polypropylene Composites: Application of MLR, DNN, and Random Forest to Industrial Data

Manufacturing polypropylene (PP) composites to meet customers’ needs is difficult, time-consuming, and costly, owing to the ever-increasing diversity and complexity of the corresponding specifications and the trial-and-error method currently used to satisfy the required physical properties. To addre...

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Detalles Bibliográficos
Autores principales: Joo, Chonghyo, Park, Hyundo, Kwon, Hyukwon, Lim, Jongkoo, Shin, Eunchul, Cho, Hyungtae, Kim, Junghwan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9459971/
https://www.ncbi.nlm.nih.gov/pubmed/36080575
http://dx.doi.org/10.3390/polym14173500

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9459971/
https://www.ncbi.nlm.nih.gov/pubmed/36080575
http://dx.doi.org/10.3390/polym14173500

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