Downloads: 111
Research Paper | Statistics | India | Volume 6 Issue 1, January 2017
Relationship between Strength Properties and Fiber Morphological Characteristics of S. officinarum ?Part-1: Regression and Artificial Neural Networks Analysis
Sourabh Monga [2] | B. P. Thapliyal [2] | Sanjay Tyagi [3] | Sanjay Naithani [2]
Abstract: The impact of different pulp morphological properties on paper properties has been the subject of interest for paper makers. Relationships between the physical strength properties of S. officinarum pulp, like tensile index, tear index, burst index & double fold number, and the morphological characteristics of pulp fiber after at beating levels is developed in the present work. Multiple linear regression (MLR) and artificial neural networks (ANN) analysis are used to develop relationship models which can be useful to monitor and control quality of the paper products. The results have indicated that the MLR and ANN approaches can be successfully used to model the effects of beating on strength parameters of S. officinarum pulp.
Keywords: Multiple linear regression, Artificial neural network, S officinarum, Morphological characteristics
Edition: Volume 6 Issue 1, January 2017,
Pages: 1549 - 1556
Similar Articles with Keyword 'Multiple linear regression'
Downloads: 116
Research Paper, Statistics, India, Volume 6 Issue 1, January 2017
Pages: 1557 - 1564Relationship between Strength Properties and Fiber Morphological Characteristics of E. tereticornis ?Part-2. Regression and Artificial Neural Networks Analysis
Sourabh Monga [2] | B. P. Thapliyal [2] | Sanjay Tyagi [3] | Sanjay Naithani [2]
Downloads: 122
Research Paper, Statistics, India, Volume 4 Issue 12, December 2015
Pages: 1307 - 1312Comparing Neural Network and Multiple Regressions Models to Estimate Monthly Rainfall Data
Satyvan Yashwant | S.L.Sananse