Correlation analysis method for corn starch process parameters and starch milk DE value

Abstract

The embodiment of the invention provides a correlation degree analysis method for corn starch process parameters and starch milk DE values, and belongs to the field of process modeling of big data. Comprising the following steps: performing feature extraction processing and dimension reduction processing on initial input data by applying a principal component analysis method to obtain a feature vector of the initial input data and principal component input data of the initial input data; training the principal component input data by using a convolutional neural network model, and calculating a total weight matrix of the trained convolutional neural network model; taking a matrix formed by sequentially combining the feature vectors of the initial input data as a weight matrix of the initial input data; and taking a matrix obtained by multiplying the total weight matrix of the convolutional neural network model by the weight matrix of the initial input data as a correlation matrix of the corn starch process sites corresponding to the DE values of the starch milk products. According to the correlation condition of the corn starch process site and the DE value of the starch milk product, a process adjustment scheme can be quickly formed for different raw materials, and the DE value of the starch milk is increased.

Description

technical field [0001] The invention relates to the field of process modeling of big data, in particular to a correlation degree analysis method between corn starch process parameters and starch milk DE value. Background technique [0002] The corn starch industry is the basic industry of carbohydrate derivatives, and the corn starch in its products is an important raw material for food processing. In terms of national life, economy and agricultural industrialization development, the starch industry in food processing is an important part of my country's food industry and one of the most important links in corn deep processing. [0003] Corn raw materials from different sources have different corresponding suitable processing parameters in the processing process. With the refinement of management, the data collected by corn deep processing enterprises in the production process has become increasingly complex, and the amount of data has exploded, and the data are all time-se...

AI Technical Summary

Problems solved by technology

Faced with massive data records, it is difficult for production managers to accurately analyze the relationship between data only relying on production experience

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