Paper Title:
Study on the Relation between Waxberry Color and its Nutrition Composition Based on BP Neural Network
  Abstract

The color of farm produce is a very important index of quality, its nutrition is correlative with itself color. At present, most of the analyses for pigment and nutrient composition still depend on chemical method; therefore the relation is studied between waxberry color and its nutrition composition based on BP neural network. The conversion relation is expressed by three-layer BP network, which hidden layer has 11 node numbers and its transfer function adopts tansig function; transfer function of output layer selects purelin function. The neural network and linear model of nutrition composition is compared respectively. The MSE value of linear model is 0.300892, and that training error of neural network is 0.0219585. From this result,we can find that the conversion relation between waxberry color and its nutrition composition is a complex non-linear relation, so neural network is adopted to complete this conversion.

  Info
Periodical
Edited by
Jerry Tian
Pages
268-273
DOI
10.4028/www.scientific.net/AMR.304.268
Citation
H. X. Zhao, Z. X. Liu, Z. Y. Luo, G. Y. Xiao, "Study on the Relation between Waxberry Color and its Nutrition Composition Based on BP Neural Network", Advanced Materials Research, Vol. 304, pp. 268-273, 2011
Online since
July 2011
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