Method for realizing food risk assessment based on improved neural network

Abstract

The invention discloses a method for realizing food risk assessment based on an improved neural network. The method comprises the following steps: 1) acquiring a sample food data set; 2) preprocessing the sample food data set, and dividing the preprocessed sample data set into a training set and a test set; 3) inputting the training set into the improved DCN network model for training, and obtaining an optimal improved DCN network model after training is completed; and 4) inputting the test set into the optimal improved DCN network model for testing, and obtaining a final prediction value of the sample food after testing, which is a risk assessment prediction score corresponding to each sample food. According to the method, the feature extraction technology of the neural network is combined with food risk assessment, data features are mined through a residual calculation method of the decision tree and a feature cross calculation method in the deep cross network, prediction of sample food risk assessment is realized by using the model, and thus the problem that food risk prediction consumes labor is effectively relieved.

Description

technical field [0001] The invention relates to the technical field of feature extraction and food safety risk assessment, in particular to a method for realizing food risk assessment based on an improved neural network. Background technique [0002] Since the beginning of the 21st century, the country's economic development and people's living standards have been continuously improved, and food-related industries have gradually formed an independent food industry system, becoming a pillar industry of the national economy, and the development of the food industry has also become the largest in my country. manufacturing. The development of my country's food manufacturing industry has made food safety risks a challenge that the health sector must face and solve. [0003] At present, in food risk assessment in my country, the establishment of a national food safety risk assessment expert committee is mainly adopted to complete the food safety assessment work. That is, manual o...

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Problems solved by technology

[0004] The purpose of the present invention is to overcome the shortcomings and deficiencies of the prior art, and propose a method for food risk assessment based on an improved neural network, which breaks through the problem that traditional food risk assessment requires a lot of labor and time, and cleverly utilizes data with A neural network model with mining capabilities to assist in the assessment, reducing the workload of food risk assessment experts, using feature crossover to capture complex interactions between features, combining multiple residuals and cross feature extraction to strengthen feature mining of samples , to further improve the model's assessment of risk prediction results

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