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A Hybrid Algorithm for BP Neural Network and Logistic Regression Model

Yan Zhang, Shuhui Wen, Wei Wu, Ying Cui


According to the background that our country’s degree of agricultural standardization production is not high, this paper investigated the influential factors of agricultural standardization production, and presented a hybrid model of SPSS analysis based on BP neural network model and logistic regression model. This model firstly used the logistic regression model to extract the important index, and then put these indexes as the input nodes of BP neural network model to train the neural network. This hybrid model extracted and fused the advantages of the two models, which not only simplified the structure of network, but also improved the generalization of network. The simulation results showed that the proposed hybrid model of SPSS analysis based on BP neural network model and Logistic regression model, had a good effect on the analysis of influential factors of agricultural standardization production.


logistic regression model, BP neural network model, agricultural standardization production, analysis of influential actors, SPSS analysis.

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