Abstract
This study uses regression model and artificial neural network model to apply food safety index in food safety trend predication and makes policy advices in the construction and release of an authoritative food safety index, The results showed that the BP neural network was high-precision, fast and objective, which could be used to food safety evaluation of circulation links of production, processing and sales.
Highlights
It is the foundation of life, stability and the source of wealth for People
Food safety evaluation model is a political model that transformed the inputs into outputs
Talents, equipments, technologies and some other information resources that evaluation required; it is the service that food safety evaluation services outputs; while it is conversion that completed the process from the input to the output
Summary
It is the foundation of life, stability and the source of wealth for People. Food safety concerns born economic development and social stability, which relate to the image of Government and nation. It has become an extremely prominent society Problem (Jiang, 2001). The supervision departments still use the traditional violation ratio evaluation which has the advantages of reliability, objectivity and simplicity, but has low identify ability. To compensate for this shortcoming, the accuracy of the food safety evaluation model directly influences the accuracy of food safety situation assessment and forecast. Based on the artificial neural network model, a food safety evaluation index system was established from the perspective of the food supply chain. The food safety model considering “violation ratio” and “violation degree”, which are key attributes describing food safety, has higher identifiability
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