Fuzzy comprehensive evaluation method for safety risks of chemical hazardous substances in food

Abstract

A first purpose of the present invention is to provide a fuzzy comprehensive evaluation method for safety risks of chemical hazards in a food. The method comprises the following steps: S1, detecting the content of each chemical hazardous substance in the food, determining the evaluation value of each chemical hazardous substance, and constructing an evaluation factor set; S2, establishing a comment set of fuzzy comprehensive evaluation: evaluating the food safety risk by taking the national limit standard MRL of food safety as an evaluation standard and adopting a zero / micro, low, medium, highand ultrahigh five-level scaling method; S3, taking the evaluation value of each chemical hazardous substance in step S1 as a calculation basis, and determining the weight of the multi-level risk factor by adopting an entropy algorithm, wherein the original detection data normalization method in the step S1 is revised by adopting a fixed coefficient method; and S4, calculating the safety risk comprehensive evaluation index FSI of the chemical hazard substances at all levels in the food by adopting a fuzzy comprehensive evaluation technology. The calculation method is objective and unified, and participation of subjective factors is effectively avoided.

Description

technical field [0001] The invention relates to a fuzzy comprehensive evaluation method for the safety risk of chemical hazards in food, belonging to the field of food safety. Background technique [0002] Since ancient times, "food is the paramount necessity of the people". With the continuous development of the modern social economy and the continuous improvement of the level of life science and technology, people's demand for food is no longer just satisfied with "sufficiency", nutrition, delicacy, health, and variety have become the gourmet pursuits of the public in today's society. , Safety is the most fundamental requirement for food quality, and it has "one-vote veto power" to measure the quality of food. "Food safety first", under the current market economy operation and management mode, scientifically carry out food quality supervision and sampling inspection and risk assessment, actively carry out risk communication, and actively, timely and comprehensively grasp ...

AI Technical Summary

Problems solved by technology

The artificial neural network is an algorithm with nonlinear adaptive information processing capabilities. It obtains the implicit laws of the system through large sample training, so as to realize the state prediction based on the existing quantitative and qualitative knowledge, but it is this "black box" model , resulting in the inability to objectively analyze the rationality and accuracy of the data prediction model, which ultimately affects the credibility and availability of the prediction results

[0005] In addition, due to the many factors affecting food safety, in order to realize the comprehensiveness of risk evaluation in previous research reports, the structure of evaluation indicators is often cumbersome and various, such as food quality level, food consumption level, risk factor exposure level, food safety public opinion, etc. indicators, and food quality inspection is often just one of them

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