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A method for predicting the nnk of flue gas from grilled slices based on robust regression modeling

A robust regression and flue gas technology, applied in the direction of complex mathematical operations, can solve problems such as laborious, high cost, and time-consuming, and achieve the effects of reducing detection costs, ensuring robustness, and improving detection efficiency

Active Publication Date: 2019-11-26
CHINA TOBACCO YUNNAN IND
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] In order to solve the problems of time-consuming, laborious, and extremely high cost in the process of detecting the NNK data of the flue gas of the grilled sheet in the prior art, the present invention proposes a method for predicting the NNK of the flue gas of the grilled sheet based on robust regression modeling

Method used

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  • A method for predicting the nnk of flue gas from grilled slices based on robust regression modeling
  • A method for predicting the nnk of flue gas from grilled slices based on robust regression modeling
  • A method for predicting the nnk of flue gas from grilled slices based on robust regression modeling

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0050] (1) Correspondingly list the physical and chemical data of the known baked slices with the smoke NNK data, and establish a data sample set, in which the physical and chemical data include total sugar, reducing sugar, nicotine, total volatile alkali, total nitrogen, nicotine nitrogen, protein , Shimuke value, nitrogen-alkali ratio, chlorine, potassium, sugar-alkali ratio and ammonia alkali, as shown in the following table:

[0051]

[0052] (2) Calculate the column vector x of each physical and chemical data in the data sample set obtained in step (1) 1 ~x n and the column vector y of the flue gas NNK data, the linear correlation coefficient r between each physical and chemical data and the flue gas NNK is calculated by the following formula:

[0053] (1)

[0054] In the formula: x is a column vector of some physical and chemical data, y is the column vector of the flue gas NNK data; the linear correlation coefficient r between the physical and chemical data of a...

Embodiment 2

[0098] Same as steps (1) to (3) of Example 1, only replace other roasted slices to be tested, step (4) is as follows:

[0099] According to the characteristic index items selected in step (2), the corresponding physical and chemical data of the baked slices to be tested, that is, total sugar = 25.94, reducing sugar = 22.43, total volatile alkali = 0.28, total nitrogen = 1.9, protein = 9.43, Shimu Ke Value=2.75, Potassium=1.91, Sugar-base Ratio=11.48, Ammonia Alkali=0.04 are used as input variables and applied to the prediction model in step (3), that is, the model prediction value Y of the smoke NNK of the grilled sheet to be tested can be calculated and calculated =5.23286-0.20846*total sugar-0.57605*reducing sugar-78.93016*total volatile alkali+37.96131*total nitrogen-4.68500*protein+5.43078*Shimuke value-0.59917*potassium-0.35104*sugar-alkaline ratio+75.20158*ammonia alkali =5.519. In order to verify the reliability of the prediction results of the model, the traditional d...

Embodiment 3

[0101] Same as steps (1) to (3) of Example 1, only replace other roasted slices to be tested, step (4) is as follows:

[0102] According to the characteristic index items selected in step (2), the corresponding physical and chemical data of the baked slices to be tested, that is, total sugar = 28.01, reducing sugar = 24.86, total volatile alkali = 0.29, total nitrogen = 1.8, protein = 8.66, Shimu Ke value = 3.24, potassium = 2.03, sugar-alkaline ratio = 11.67, ammoniacal alkali = 0.04 as input variables and applied to the prediction model in step (3), that is, the model prediction value Y of the smoke NNK of the grilled sheet to be tested can be calculated and calculated =5.23286-0.20846*total sugar-0.57605*reducing sugar-78.93016*total volatile alkali+37.96131*total nitrogen-4.68500*protein+5.43078*Shimuke value-0.59917*potassium-0.35104*sugar-alkaline ratio+75.20158*ammonia alkali =5.233. In order to verify the reliability of the prediction results of the model, the traditi...

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Abstract

The invention provides a method for predicting cured piece smoke NNK on the basis of robust regression modeling. A model from a physicochemical index item to the smoke NNK is built according to existing cured piece physicochemical data and smoke NNK data, and a cured piece smoke NNK value of an unknown cured piece smoke NNK sample can be directly predicted through physicochemical component data. By means of the method, the steps of rolling, burning, smoke capturing, detection and the like of a traditional chemical mode are omitted. Meanwhile, a robust regression model is adopted so that defects caused by singular values in the physicochemical data or in the smoke data can be effectively avoided, robustness of the model is guaranteed to a large extent, and compared with a common linear regression modeling, robust regression modeling has the advantage of better guaranteeing robustness. As is proved in practice, the cured piece smoke NNK value can be effectively predicted through the model, detection efficiency is greatly improved, and detection cost is lowered.

Description

technical field [0001] The invention relates to a method for predicting NNK of flue gas of grilled slices based on robust regression modeling, and belongs to the technical field of specific calculation models. Background technique [0002] Tobacco smoke is an extremely complex mixture produced by the burning, cracking and distillation of tobacco during cigarette smoking. The harmfulness of cigarette products to the human body is produced through the process of burning and smoking. The harmful components in the smoke are mainly formed during the combustion process, and the chemical characteristics of the smoke change with the internal chemical components of the tobacco leaf raw materials. Therefore, the chemical properties of raw materials of cigarette tobacco leaves determine the chemical properties and safety of cigarette smoke. The full name of NNK is 4-(N-methyl-N-nitrosamine)-1-(3-pyridyl)-butanone (4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone), NNK exists in large ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/10
Inventor 白晓莉彭国岗魏帅朱勇谢志强周桂圆王保兴刘挺段如敏
Owner CHINA TOBACCO YUNNAN IND
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