Relationship between Strength Properties and Fiber Morphological Characteristics of S. officinarum ?Part-1: Regression and Artificial Neural Networks Analysis
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


Downloads: 111 | Views: 289

Research Paper | Statistics | India | Volume 6 Issue 1, January 2017 | Popularity: 6.8 / 10


     

Relationship between Strength Properties and Fiber Morphological Characteristics of S. officinarum ?Part-1: Regression and Artificial Neural Networks Analysis

Sourabh Monga, B. P. Thapliyal, Sanjay Tyagi, Sanjay Naithani


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


DOI: https://www.doi.org/10.21275/ART20164484


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Sourabh Monga, B. P. Thapliyal, Sanjay Tyagi, Sanjay Naithani, "Relationship between Strength Properties and Fiber Morphological Characteristics of S. officinarum ?Part-1: Regression and Artificial Neural Networks Analysis", International Journal of Science and Research (IJSR), Volume 6 Issue 1, January 2017, pp. 1549-1556, https://www.ijsr.net/getabstract.php?paperid=ART20164484, DOI: https://www.doi.org/10.21275/ART20164484

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