Method for predicting raw material processing suitability based on BP artificial neural network

An artificial neural network and suitability technology, applied in neural learning methods, biological neural network models, predictions, etc., can solve the problems of unreported raw material processing suitability prediction, achieve high accuracy, improve the rationality of association, The effect of promoting development

Pending Publication Date: 2019-03-01
INST OF AGRO FOOD SCI & TECH CHINESE ACADEMY OF AGRI SCI
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In recent years, the application of BP neural network model in the field of processing industry has been increasing, including identification, classification and classification, simulation and control of processing process, single index value prediction, etc., and achieved certain results. Not yet reported

Method used

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  • Method for predicting raw material processing suitability based on BP artificial neural network
  • Method for predicting raw material processing suitability based on BP artificial neural network
  • Method for predicting raw material processing suitability based on BP artificial neural network

Examples

Experimental program
Comparison scheme
Effect test

example 1

[0038] The turbidity of apple juice used to evaluate the suitability of apple processing is selected as a single index, including the following steps:

[0039] (1) Select an apple sample

[0040] 41 apple varieties from all over the country were selected as experimental raw materials. The names and origins of some varieties are shown in Table 1. The fruits were sampled during the ripening period, without mechanical damage, and without pests and diseases;

[0041] Table 1 Partial apple variety names and origin

[0042]

[0043] (2) Determine the apple raw material index, and obtain the apple raw material index data and apple juice turbidity data;

[0044] (3) Screen the core indicators of apple raw materials;

[0045] Establish the correlation between apple raw material index data and apple juice turbidity data, and conduct correlation analysis on apple juice turbidity data and apple raw material index data. The results are shown in Table 2, and the fruit core size, pulp L...

example 2

[0056] The comprehensive score of apple juice used to evaluate the suitability of apple processing is selected as a single index, including the following steps:

[0057] (1) Select an apple sample

[0058] 33 apple varieties from all over the country were selected as experimental raw materials. The names and origins of some apple varieties are shown in Table 4. The fruits were sampled during the ripening period, without mechanical damage, no pests and diseases;

[0059] Table 4 Partial Apple Variety Names and Origins

[0060]

[0061] (2) Determine the evaluation method for the comprehensive score of apple juice

[0062] Taking many indicators of apples as variables, processing technology and parameters as quantitative raw materials processing, recording and sorting out historical data, and measuring data of apple juice, the data of apple juice includes soluble solids, titratable acid, crude fiber, crude protein, Vc, Reducing sugar, total sugar content, juice L value, jui...

example 3

[0087] The comprehensive score of apple juice used to evaluate the suitability of apple processing is selected as a single index, including the following steps:

[0088] (1) Select an apple sample

[0089] 30 apple varieties from all over the country were selected as experimental raw materials. The names and origins of some apple varieties are shown in Table 9. The fruits were sampled during the ripening period, without mechanical damage, and without pests and diseases;

[0090] Table 9 Partial Apple Variety Names and Origins

[0091]

[0092] (2) Determine the evaluation method for the comprehensive score of apple juice

[0093] Taking many indicators of apples as variables, processing technology and parameters as quantitative raw materials processing, recording and sorting out historical data, and performing sensory evaluation on apple juice, the scoring standards are shown in Table 10, and the scoring results are shown in Table 11;

[0094] Table 10 Apple juice sensory...

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Abstract

The invention discloses a method for predicting raw material processing suitability based on BP artificial neural network, which comprises the following steps: selecting a single index of a processedproduct used for evaluating the raw material processing suitability, and determining a plurality of indexes of related raw materials according to the single index of the processed product; taking manyindexes of raw materials as variables, processing technology and parameters as quantitative raw materials processing, recording and sorting historical data to form samples; taking the raw material index data of the training sample set as the input layer and the single index data of the processed product of the training sample set as the output layer, the model is trained to the artificial neuralnetwork model to be stable performing optimization of artificial neural network model; predicating single indicator of processed products. The invention can relate raw material index and processed product quality, and has high accuracy while seeking complex non-linear correspondence between variables objectively, qualitatively or quantitatively, and can realize predicting processed product qualityqualitatively or quantitatively based on raw material index.

Description

technical field [0001] The invention relates to the field of processing. More specifically, the present invention relates to a method for predicting the processing suitability of raw materials by a BP artificial neural network. Background technique [0002] Raw material characteristics are the basis for producing high-quality processed products. Therefore, correlating raw material characteristics and product quality, clarifying the suitability of raw material processing, and screening high-quality processing raw materials are of great significance to enterprise efficiency, social income increase and industrial development. At present, the research on the suitability of raw material processing mostly uses methods such as analytic hierarchy process and gray correlation to analyze the quality of raw materials or product quality separately, which can only evaluate the processing characteristics of the species studied, and cannot predict the processing performance of unknown samp...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06G06N3/08
CPCG06N3/084G06Q10/04G06Q50/06
Inventor 毕金峰刘璇张彪吕健吴昕烨陈芹芹
Owner INST OF AGRO FOOD SCI & TECH CHINESE ACADEMY OF AGRI SCI
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