Open Access Open Access  Restricted Access Subscription or Fee Access

A Hybrid Algorithm for BP Neural Network and Logistic Regression Model

Yan Zhang, Shuhui Wen, Wei Wu, Ying Cui

Abstract


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.

Keywords


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

Full Text:

PDF


Disclaimer/Regarding indexing issue:

We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information.