Correlativity analysis method of physical, chemical data and sensing index of formulation product

A technology of correlation analysis and physical and chemical indicators, applied in the direction of electrical digital data processing, special data processing applications, digital computer parts, etc., can solve problems such as high cost time, improvement and optimization, sensory error, etc.

Inactive Publication Date: 2006-09-06
OCEAN UNIV OF CHINA
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  • Abstract
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AI Technical Summary

Problems solved by technology

Although the manufacturers of formula products have accumulated a certain amount of expert evaluation data through long-term production management, since the quality evaluation is performed by individuals, there are inevitably many human factors in these evaluation data.
For example, in the process of quality evaluation, experts will be interfered by factors such as their own emotions, physical conditions, personal sensory preferences, and the degree of fatigue, and there will be sensory errors objectively, which will ultimately be reflected in the inaccurate classification of formula products and the difficulty To further improve and optimize the production process
Moreover, organizing experts to conduct quality assessment also requires high costs and a lot of time

Method used

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  • Correlativity analysis method of physical, chemical data and sensing index of formulation product
  • Correlativity analysis method of physical, chemical data and sensing index of formulation product
  • Correlativity analysis method of physical, chemical data and sensing index of formulation product

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Embodiment 1

[0066] Example 1, such as figure 1 As shown, the method flow for the correlation analysis between the physicochemical data of the formula product and the sensory index is:

[0067] Actually test the physical and chemical indicators of formula products and organize industry experts to evaluate the finished products, accumulate and record the obtained evaluation data, and form a data sample set;

[0068] Eliminate errors or idiosyncratic samples in the above-mentioned data sample set based on the industry experience of experts, in order to map the correlation between physical and chemical data and sensory indicators as intuitively as possible and the size of the program;

[0069] According to the place of origin, grade, style and other indicators, the sorted physical and chemical data sample set is divided into a training sample set and a verification sample set;

[0070] Using the ladder analysis method to construct several ladder samples for knowledge extraction and correlati...

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PUM

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Abstract

With the SVM gradient analysis, building a technique process to determine former correlation; then, finding out the correlated parameters to sense index, and creating the detection sample. This invention can provide quantitative analysis data for quality evaluation and level partition.

Description

technical field [0001] The invention relates to a method flow for data analysis, in particular to realize the correlation analysis between physical and chemical data and sensory indicators, so as to guide the quality evaluation and classification of formula products. Background technique [0002] In the existing formula product manufacturing industry, sensory quality evaluation needs to be carried out in the process of production quality management and raw material classification for the formula used in the product and its composition. For example, cigarette products are usually evaluated by indicators such as fragrance style, irritation, strength, etc., so as to indicate their different grades to consumers. [0003] For industrially produced formula products, the previous evaluation process mainly relied on tasting experts to classify the grades, advantages and disadvantages through on-site tasting and personal sensory experience. Although the manufacturers of formula prod...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F15/18G06F17/00
Inventor 杨宁刘挺贺英傅昕宇马琳涛侯瑞春丁香乾王鲁生周志明魏旭
Owner OCEAN UNIV OF CHINA
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