Prediction of Five Softwood Paper Properties from its Density using Support Vector Machine Regression Techniques

Prediction of Five Softwood Paper Properties from its Density using Support Vector Machine Regression Techniques

Predicting paper properties based on a limited number of measured variables can be an important tool for the industry. Mathematical models were developed to predict mechanical and optical properties from the corresponding paper density for some softwood papers using support vector machine regression...

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Bibliographic Details
Main Authors: Esperanza García-Gonzalo, António J. A. Santos, Javier Martínez-Torres, Helena Pereira, Rogério Simões, Paulino José García-Nieto, Ofélia Anjos
Format: Article
Language:English
Published: North Carolina State University 2016-01-01
Series:BioResources
Subjects:
Paper properties
Kraft pulp
Vector machine regression
Pinus pinaster
Pinus sylvestris
Cupressus lusitanica
Cupressus sempervirens
Cupressus arizonica
Online Access:http://ojs.cnr.ncsu.edu/index.php/BioRes/article/view/BioRes_11_1_1892_Garcia_Gonzalo_Prediction_Five_Softwood_Paper_Properties

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http://ojs.cnr.ncsu.edu/index.php/BioRes/article/view/BioRes_11_1_1892_Garcia_Gonzalo_Prediction_Five_Softwood_Paper_Properties

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