Cyclone performance prediction using linear regression techniques

  1. Bobadilla, M.C. 2
  2. Martinez, R.F. 1
  3. Lorza, R.L. 2
  4. Gomez, F.S. 2
  5. Vergara Gonzalez, E.P. 2
  1. 1 Universidad del País Vasco/Euskal Herriko Unibertsitatea
    info

    Universidad del País Vasco/Euskal Herriko Unibertsitatea

    Lejona, España

    ROR https://ror.org/000xsnr85

  2. 2 Universidad de La Rioja
    info

    Universidad de La Rioja

    Logroño, España

    ROR https://ror.org/0553yr311

Livre:
Advances in Intelligent Systems and Computing

ISSN: 2194-5357

ISBN: 978-331947363-5

Année de publication: 2017

Volumen: 527

Pages: 53-62

Type: Chapitre d'ouvrage

DOI: 10.1007/978-3-319-47364-2_6 SCOPUS: 2-s2.0-84992445218 WoS: WOS:000405330000006 GOOGLE SCHOLAR

Résumé

A wide range of industrial fields utilize cyclone separators and so, evaluating their performance according to different materials and varying operating conditions could contribute useful information and could also save these industries significant amounts of capital. This study models cyclone performance using linear regression techniques and low errors were obtained in comparison with the values obtained from real experiments. Linear regression and generalized linear regression techniques, simple and enhanced with Gradient Boosting techniques, were used to create linear models with low errors of approximately 0.83 % in cyclone performance. © Springer International Publishing AG 2017.