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Title: Dependence of softness perception on tissue physical properties and development of neural model for predicting softness
Authors: Rastogi V.
Großmann H.
Ray A.K.
Greiffenberg I.
Published in: IPPTA: Quarterly Journal of Indian Pulp and Paper Technical Association
Abstract: Tissue papers are distinguished and graded specifically based on several properties, but softness is the most desirable one for the customer. Several efforts are still being made for the accurate prediction of softness, but till date its evaluation is difficult. Hence, the development of a standard assessment procedure for the softness evaluation of tissue products is an absolute necessity for manufacturers, converters and consumers alike. This study mainly focuses on development of a neural model for softness prediction. By using the Artificial Neural Network (ANN) the impact of tissues physical properties on tissue softness were determined. Neural network was trained properly with the given set of inputs and outputs values to find the appropriate weights which minimizes the error of the network and after which new inputs were given to trained network for finding out the predicted softness through simulation. This model was able to predict the facial tissue softness very well and a high degree of correlation was achieved for predicted softness and panel softness.
Citation: IPPTA: Quarterly Journal of Indian Pulp and Paper Technical Association (2017), 29(2): 128-135
Issue Date: 2017
Appears in Collections:Journal Publications [PT]

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