Cyclone Performance Prediction Using Linear Regression Techniques

• Marina Corral Bobadilla ^[1] ; Roberto Fernandez Martinez ^[2] ; Rubén Lostado Lorza ^[1] ; Fátima Somovilla Gomez ^[1] ; Vergara Gonzalez, Eliseo P. ^[1]
  1. [1] Universidad de La Rioja

     Universidad de La Rioja

     Logroño, España

     
  2. [2] Universidad del País Vasco/Euskal Herriko Unibertsitatea

     Universidad del País Vasco/Euskal Herriko Unibertsitatea

     Leioa, España

     
• Localización: International Joint Conference SOCO’16-CISIS’16-ICEUTE’16: San Sebastián, Spain, October 19th-21st, 2016 Proceedings / coord. por Manuel Graña Romay, José Manuel López Guede, Oier Etxaniz, Álvaro Herrero Cosío, Héctor Quintián Pardo, Emilio Santiago Corchado Rodríguez, 2017, ISBN 978-3-319-47364-2, págs. 53-62
• Idioma: inglés
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• Resumen

  • 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.