Food safety risk prediction method based on hidden Markov model

Abstract

The invention provides a food safety risk prediction method based on the hidden Markov model. The method comprises the steps: analyzing every step of a food supply chain, and finding out a critical control point of each step; analyzing the critical control point of each step and using the critical control point as a quantitative index of the HMM (hidden Markov model), and establishing a HMM; initializing parameters of the HMM, and training the parameters of the HMM according to a visible state sequence of the HMM and the real state of a system; and performing the risk assessment and value-at-risk calculation on the risk grade of the food supply chain. According to the invention, the HMM is adopted to assess the food quality and safety, the dynamics of every step is considered, the risk state can be responded in real time, a quantitative and qualitative-combined assessment method is adopted, the degree of the supply chain risk can be more precisely described than before, and the method is helpful for decision maker to timely adopt corresponding measures. The risk assessment model can assess the dairy product and has strong expansibility so as to apply to other fields of food safety.

Description

technical field [0001] The invention belongs to the field of food safety and computer data modeling, and in particular relates to a food safety risk prediction method based on a hidden Markov model. Background technique [0002] Frequent food safety incidents not only seriously threaten the health of the masses, but also bring social instability, trigger a crisis of trust, and affect economic development. In recent years, the prevention and governance of food safety issues have received high attention. Among them, risk assessment is the basis of risk early warning and governance, and has received special attention. Risk assessment is the process of confirming security risks and their size, that is, using appropriate risk assessment tools and methods to determine asset risk levels and priority control sequences. The purpose of food safety risk assessment is to fully grasp the overall situation of supply chain risks, so as to provide decision support for implementing effectiv...

AI Technical Summary

Problems solved by technology

[0007] SVM has good classification and generalization capabilities in the case of small samples, and is not suitable for the analysis and processing of large sample data. At the same time, the classic SVM only gives a two-class classification algorithm, which is difficult to solve multi-classification problems.

[0008] Although the artificial neural network has a high degree of self-adaptive ability, its learning speed is slow, and the possibility of the a...

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