Food-borne disease pathogenic factor prediction method and system based on BP neural network

Abstract

The invention discloses a food-borne disease pathogenic factor prediction method based on a BP neural network, and the method comprises the following steps: S1, collecting data, collecting and arranging food-borne disease accident cases, building a food-borne disease sample analysis database, and recording the feature items contained in each sample; and S2, determining a training set and a test set, and performing attribute selection and neuron definition. The method has the beneficial effects that the deep BP neural network model is established, the network structure is improved by increasingthe number of hidden layers of the neural network, the network calculation complexity is optimized, the food-borne disease epidemiological pathogenic factor accurate analysis and prediction network model is established, and real-time updating and overlapping are performed through the dynamic migration network with a self-learning function; the execution efficiency and sensitivity of the discrimination model network for food-borne disease pathogenic factor prediction are improved; and missing data is preprocessed, data containing missing items is reconstructed and analyzed, and the data is made to participate in effective network calculation.

Description

Technical field: [0001] The invention belongs to the technical field of pathogenic factor prediction, and particularly relates to a method and system for predicting pathogenic factors of foodborne diseases based on BP neural network. Background technique: [0002] Foodborne diseases are defined as "diseases caused by human ingestion of contaminated food, including parasites, chemicals and pathogenic bacteria that contaminate food in different stages of food production and preparation. Covers a wide range of diseases". Foodborne diseases have caused great harm to public health, the healthy development of the food industry and social stability. At present, many countries have carried out foodborne disease monitoring. The purpose of the foodborne disease surveillance system is to identify and control foodborne disease outbreaks, analyze and determine pathogenic factors; identify susceptible populations, high-risk foods and poor food handling procedures; clarify the foodborne t...

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to provide a method and system for predicting pathogenic factors of foodborne diseases based on BP neural network in order to solve the above problems, which solves the problem of attribute selection and accurate definition of neurons in the existing small sample sparse data conditions And the shortcomings of the prediction accuracy, sensitivity and specificity of the pathogenic factors of foodborne diseases under the condition of a large number of data containing missing items

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