Neural network model for assessing the quality indicators of the paper industry

Studies of the dependence of the quality of the paper web on the production conditions and properties of raw materials give a significant statistical spread, as a result of which it is impossible to accurately predict the result. This fact became a prerequisite for the use of neural network modeling technology in the development of an intelligent system for monitoring the quality of the paper web. The methodology for determining the estimates of the heterogeneity of the structure of the paper web at the final stage of its production is considered. It is proposed to expand the classification of finished product samples through the use of neurofuzzy interpolation of the linguistic values of such indicators, which will improve the efficiency of the production process

Keywords: paper production, quality assessment, structural heterogeneity assessment, neural network model, neural network classifier


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