On-line Soft Sensor Based on Regression Models and Feature Selection Techniques for Predicting Rubber Properties in Mixture Processes

E. Sodupe-Ortega, R. Urraca, J. Antonanzas, M. Alia-Martinez, A. Sanz-Garcia, F. J. Martínez-de-Pisón

Research output: Chapter in Book/Report/Conference proceedingChapterScientificpeer-review

Original languageEnglish
Title of host publicationProject Management and Engineering
EditorsJosé Luis Ayuso Muñoz, José Luis Yagüe Blanco, Salvador F. Capuz-Rizo
Number of pages11
PublisherSpringer International Publishing AG
Publication date2015
Pages235-245
ISBN (Print)978-3-319-12753-8
ISBN (Electronic)978-3-319-12754-5
DOIs
Publication statusPublished - 2015
MoE publication typeA3 Book chapter

Publication series

NameLecture Notes in Management and Industrial Engineering
PublisherSpringer International Publishing
Number6
Volume2015
ISSN (Print)2198-0772

Fields of Science

  • On-line soft sensor
  • Rubber mixture process
  • Rheological rubber properties
  • Parsimony prediction model
  • Feature selection
  • 317 Pharmacy

Cite this

Sodupe-Ortega, E., Urraca, R., Antonanzas, J., Alia-Martinez, M., Sanz-Garcia, A., & Martínez-de-Pisón, F. J. (2015). On-line Soft Sensor Based on Regression Models and Feature Selection Techniques for Predicting Rubber Properties in Mixture Processes. In J. L. Ayuso Muñoz, J. L. Yagüe Blanco, & S. F. Capuz-Rizo (Eds.), Project Management and Engineering (pp. 235-245). (Lecture Notes in Management and Industrial Engineering; Vol. 2015, No. 6). Springer International Publishing AG. https://doi.org/10.1007/978-3-319-12754-5_18