Application of BP Neural Network in Evaluation Model of Regional Brand Competitiveness of Agricultural Products

Abstract

There are many regional brands of agricultural products in China. However, they do not have strong competitiveness. This paper studies the regional brand competitiveness of agricultural products. This study preliminarily obtains a number of evaluation indicators by revising the relevant research on the regional brand competitiveness of agricultural products and combining with expert opinions. Exploratory factor analysis is used to determine the evaluation index system of regional brand competitiveness of agricultural products. The BP neural network is used to weight the evaluation indicator system and the triangular whitening weight function of the gray system theory is used to establish the evaluation model of the regional brand competitiveness of agricultural products. The research results indicate that industry association management and coordination, the number of patents granted and the government guidance coordination and management have higher weight. It shows that the government and industry association play a key role in the construction of regional brand competitiveness of agricultural products. Scientific and technological innovation is the internal driving force of product development. At last, this paper puts forward three suggestions to enhance the competitiveness of agricultural products regional brands from industry associations, technological empowerment and cultural empowerment of agricultural product regional brands.