A Food Safety Risk Warning Method Based on BP Neural Network

doi:10.3969/j.issn.1006-2475.2025.01.004

Abstract

Abstract: This paper proposes a food safety risk warning method based on BP neural network. Firstly， a comprehensive food safety risk assessment index system is constructed through screening and integration， and the weights of each indicator are calculated by using the three scale analytic hierarchy process. Then， 7 key indicators are selected as input indicators for early warning research to fully reflect the food safety risk situation. Finally， the BP neural network is used for food safety risk warning， and the connection weights and thresholds of the BP neural network are optimized through genetic algorithm to make the output results closer to the expected output. The experimental results show that the risk warning time data range of this method is 7.23 s~10.23 s， and the accuracy data range of risk warning is 94.05% ~98.44%， indicating that the BP neural network has good practical application effect in food safety risk warning and has practicability.

Key words: , BP neural network, food, safety, risk early warning, machine learning

CLC Number:

TP391

XU Shengchao, CHEN Fuqiang. A Food Safety Risk Warning Method Based on BP Neural Network[J]. Computer and Modernization, 2025, 0(01): 20-24.

References

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