The regulatory warning model of regional product quality based on the back-propagation artificial neural network

Abstract

Accidents of product quality occur in food, medicine and industrial products, posing a major risk to consumers. Prediction and control of accidents spread are difficult, mainly due to the complexity of the interaction between stakeholders involved. The regulatory policies formulated by the government play a key role in the regional product quality. In the perspective of government regulation, this paper focuses on the regulatory warning model of regional product quality. In reference to the regional competitiveness index and customer satisfaction index system, the regulatory warning index system is established, according to the four aspects of regional economic development, residential living standard, situation of industrial enterprise and government regulation. In this work, the warning model based on back-propagation artificial neural network is introduced; the quantitative results shows that the predicted value is highly consistent with the actual value after conducting the empirical research on the warning model, using the data of Shandong Province from 2000 to 2013. The study demonstrates that early warning indicators could be useful for the prediction of accidents of regional product quality through back-propagation artificial neural network model. The results may also be useful to government to improve the performance of regulation.