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The Study on a Neural Network Model of Tea Quality Evaluation Based on Chemical Compositions

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Pp. 15-21 in Proceedings of the World Congress of Computers in Agriculture and Natural Resources (13-15, March 2002, Iguacu Falls, Brazil)  701P0301.(doi:10.13031/2013.8306)
Authors:   Hongchun Yuan and Fanlun Xiong
Keywords:   Function Link Network, Tea quality evaluation, multiple-linear regression

This paper studies a neural network model of tea quality evaluation based on the chemical compositions such as fiber, nitrogen, infused contents and water. Function Link Network (FLN), which is a kind of forward neural network consisting of two layers, is adopted in this research. The preprocessing of data, the construction of neural network for tea quality evaluation and the training of the network are discussed. The result of an experiment shows that applying FLN in tea quality evaluation is better than using multiplelinear regression.

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