Electronic Science and Technology ›› 2022, Vol. 35 ›› Issue (6): 35-42.doi: 10.16180/j.cnki.issn1007-7820.2022.06.006

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A GA-BP Neural Network for Predicting the Structure of Leaf Tobacco

ZHANG Chongchong,HUANG Yayu   

  1. Faculty of Mechanical and Electrical Engineering,Kunming University of Science and Technology,Kunming 650500,China
  • Received:2020-12-09 Online:2022-06-15 Published:2022-06-20
  • Supported by:
    Yunnan Provincial Major Science and Technology Special Plan(202002AD080001)


In view of the problem that it is difficult to predict the structure of tobacco during the threshing process of redrying plant, a GA-BP neural network prediction model based on MATLAB image processing is proposed. For the classification of tobacco leaf, the obtained tobacco leaf images are preprocessed using of the MATLAB software. Then, the main characteristic variables that measure the structure of the tobacco are extracted, and industry standards and cluster analysis algorithms are used to classify the data. Through the standard mathematical method of statistics, the BP neural network prediction model optimized by genetic algorithm is constructed to predict and optimize the main influencing parameters. The research results show that the method proposed in this study has high prediction accuracy, and the prediction range is less than 0.059, which indicates that the method can effectively solve the problem of prediction of slices of tobacco in the process of threshing.

Key words: MATLAB, image processing, cluster analysis, leave-one-out-cross-validation, BP neural network, genetic algorithm, GA-BP neural network, binarization

CLC Number: 

  • TP29