CN111680910A - Tobacco application range positioning method based on cigarette formula efficacy - Google Patents
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Abstract
The invention relates to the technical field of classification of tobacco raw materials, in particular to a tobacco application range positioning method based on cigarette formula effects. The method comprises the following steps: respectively selecting representative tobacco raw material samples with each type of efficacy i; selecting a plurality of tobacco leaf quality characteristic indexes as characteristics J, detecting characteristic values of representative tobacco leaf raw material samples, and determining quality requirements J according to the characteristic valuesij(ii) a For each type of efficacy i, constructing a feature importance comparison matrix according to the scale, and calculating a feature vector of each feature j after normalizing the feature importance comparison matrix; then dividing each feature vector by the sum of all feature vectors to obtain a weight Zij(ii) a Calculating the evaluation weight of applicabilityHeavy Sij=（Zij×100）/Jij(ii) a Determining each characteristic value G of the tobacco leaf raw material to be positionedjThe applicability score H of the tobacco leaf raw material to be positioned under a certain efficacy ii=∑（Gj×Sij). The invention can obtain all the application ranges of the tobacco raw materials, thereby improving the utilization rate of the tobacco raw materials.
Description
Technical Field
The invention relates to the technical field of classification of tobacco raw materials, in particular to a tobacco application range positioning method based on cigarette formula effects.
Background
At present, a large number of cigarette products exist in the market, and different efficacy positions exist among cigarettes of different brands and among different fine-quality products of the same brand, so that different smoking experiences are brought to people. The different cigarette effects are obtained by formulating and applying tobacco leaf raw materials with different qualities and styles in a mode of multiple varieties, multiple grades and proportions. The traditional formula technology is obtained by subjective experience judgment of a formula technician, and in the face of a large number of tobacco raw materials of different varieties and grades, the problems of difficulty in raw material screening and great influence from main observation exist, and one tobacco raw material can be used in cigarette products with different effects when being actually used, so that the tobacco raw material cannot be maximally utilized only by the subjective experience of the formula technician.
Therefore, how to scientifically and reasonably determine the application range of the tobacco leaf raw materials and improve the utilization rate of the tobacco leaf raw materials becomes a problem which needs to be solved urgently.
Patent document CN107589228A discloses a method for predicting the industrial applicability of sorted tobacco leaves by their characteristic appearance indexes, comprising the steps of, sampling; preparing an industrial sorted sample, measuring and calculating the proportion of the sorted sample and quantifying the appearance quality index; sensory evaluation, index quantification and industrial applicability judgment of industrial sorted samples; establishing a tobacco industrial applicability classification prediction model based on appearance indexes, and determining characteristic appearance indexes and index values; establishing a weight proportion fitting curve of the appearance characteristic index and the corresponding appearance characteristic index; and calculating the quantitative predicted value of the industrial applicability of the batch of raw materials according to the appearance characteristic index and the fitting curve. According to the application, industrial applicability evaluation is carried out on the tobacco leaves based on a plurality of tobacco leaf appearance index characteristics, on one hand, the sensory quality of the tobacco leaves is difficult to determine through appearance indexes, and applicability evaluation based on the cigarette formula effect cannot be carried out; on the other hand, several appearance indexes are parallel factors to each other, and actually, the influence of different appearance indexes on the industrial applicability is different. In this application, if the measurement of the appearance index having a small influence on the industrial applicability is largely deviated, the result is largely deviated, and a large error occurs between the predicted result and the actual result.
Disclosure of Invention
The invention aims to solve the problems and provides a positioning method which is based on the efficacy of a cigarette formula and can quickly and accurately judge the application range of tobacco raw materials.
The technical scheme for solving the problems is to provide a tobacco application range positioning method based on the cigarette formula efficacy, which comprises the following steps:
(1) respectively selecting representative tobacco leaf raw material samples with each type of efficacy i according to different formula efficacies of the cigarettes; selecting a plurality of tobacco leaf quality characteristic indexes as characteristics j, and detecting the characteristics jDetermining the quality requirement J of each characteristic J in each type of efficacy i according to the characteristic value of the representative tobacco leaf raw material sampleij；
(2) For each type of efficacy i, constructing a feature importance comparison matrix according to the scale, and calculating a feature vector of each feature j after normalizing the feature importance comparison matrix; then, dividing each feature vector by the sum of all feature vectors to obtain the weight Z of each feature j in each type of efficacy iij；
(3) Calculating a suitability evaluation weight Sij＝(Zij×100)/Jij；
(4) Determining each characteristic value G of the tobacco leaf raw material to be positionedjThe applicability score H of the tobacco leaf raw material to be positioned under a certain efficacy ii＝∑(Gj×Sij)；
(5) If H is presentiMore than or equal to 100, the raw material to be positioned is suitable for the efficacy i.
When in use, the applicability score H of the tobacco leaf raw material to be positioned in a certain efficacy iiThe larger the size, the more suitable the tobacco leaf raw material to be positioned is as the raw material for preparing the cigarette with the efficacy i. The applicability score H of the tobacco leaf raw material to be positioned if the raw material has a certain efficacy iiMore than or equal to 100, the tobacco leaf raw material is considered to be suitable for the efficacy i, and the tobacco leaf raw material can be used as a raw material of any cigarette brand and then directly used on a production process line of the cigarette brand. Therefore, the present application is also directed to providing an efficient cigarette production method, wherein the cigarette production comprises two steps, i.e., selecting the tobacco material and preparing the tobacco material into finished cigarettes. Starting with the selection step of the tobacco raw materials, the cigarette production efficiency and the finished product quality are improved by improving the speed and the precision of raw material screening.
Preferably, in the step (1), the selected tobacco leaf quality characteristic indexes comprise: quality of fragrance, amount of fragrance, penetrability, miscellaneous gas, fineness, softness, mellow feeling, irritation, dryness, aftertaste, smoke concentration and strength ratio.
The tobacco leaf quality characteristic indexes, namely characteristic values, are obtained through non-detection, numerical values of the tobacco leaf quality characteristic indexes are obtained through evaluation and scoring of smokers, corresponding standards are various in the tobacco industry, and the tobacco leaf quality characteristic indexes are preferably evaluated and scored through a tobacco industry standard YC/T530 + 2015 tobacco leaf quality style characteristic sensory evaluation method to obtain the characteristic values.
In the step (1), the quality requirement J of each characteristic J in each type of efficacy i is determined through the characteristic valuesijThe specific method of (1) is generally: calculating the average value of all characteristics of all representative tobacco leaf raw material samples classified in the same efficacy i, wherein the quality requirement is that the average value is more than or equal to JijThe values of (A) are averaged.
In the step (2), the importance comparison matrix is obtained by comparing the importance of each feature, the maximum feature root of the matrix is calculated, the feature vector of the maximum feature root is obtained, and the weight of each feature can be obtained after normalization processing.
The scale may be various, such as 1-9 scale method and 0-2 three scale method, 9/9-9/1 fractional scale method with improved accuracy on 1-9 scale method, 10/10-18/2 fractional scale method, 1-1 three scale method and 2-2 five scale method with improved accuracy on 0-2 three scale method, and the like.
Since the more scale values, the more accurate the measurement of things is relatively, the preferred method of the invention is to construct the feature importance comparison matrix according to the score scaling method of 9/9-9/1 in step (2).
The construction criteria for the 9/9-9/1 fractional scaling method are shown in Table 1 below.
Table 1.
When the importance comparison matrix is constructed, the characteristics are compared pairwise, and the corresponding scale value is taken according to the value meaning in the table 1.
Because when constructing the significance comparison matrix of the features, the features are compared pairwise, in order to avoid the occurrence: the case of B > C, C > D, and B < D, as preferred in the present invention, requires a consistency check on the constructed index comparison matrix.
First, the maximum eigenvalue of each importance comparison matrix is calculated as following formula 1:
formula 1.
Wherein A represents an importance comparison matrix of efficacy i, Z represents a weight matrix of efficacy i, and n represents the number of features.
The consistency index is then calculated as following formula 2:
and (3) formula 2.
The more uniform the c.i. ═ 0 is, the more inconsistent the c.i. is.
Preferably, the method further comprises the step of calculating a random consistency ratio c.r. according to the consistency index c.i. and the following formula 3.
And (3) formula.
When c.r. <0.1, the consistency test was met.
Wherein, r.i. represents an average random consistency index, which is a constant and can be looked up in a scale according to the order, and the r.i. value scale is as shown in table 2 below.
Table 2.
| Number of indexes | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 |
| R.I. | 0 | 0 | 0.58 | 0.9 | 1.12 | 1.24 | 1.38 | 1.41 | 1.46 | 1.49 | 1.52 | 1.54 |
The invention has the beneficial effects that:
through the weight obtained by the application, the applicability score H of any one tobacco leaf raw material in a certain efficacy i can be calculatediIf H is presentiGreater than or equal to 100, the tobacco leaf material is considered suitable for use in the efficacy i. If the tobacco leaf material is at H of multiple efficacy iiThe number of the tobacco raw materials is more than or equal to 100, which indicates that the tobacco raw materials are applicable to the effects i, namely the application range of the tobacco raw materials is determined, the utilization rate of the tobacco raw materials can be improved, and technical guidance can be provided for formulation of schemes such as overall use of formula raw materials and design of threshing and redrying formula modules.
Detailed Description
The following are specific embodiments of the present invention and further describe the technical solutions of the present invention, but the present invention is not limited to these examples.
A tobacco application range positioning method based on cigarette formula efficacy comprises the following steps:
(1) and respectively selecting representative tobacco leaf raw material samples with each type of efficacy i according to different formula efficacies of the cigarettes.
In this embodiment, 197 tobacco raw material samples with grades capable of representing each efficacy location of each cigarette brand are selected according to the style, characteristics and efficacy locations of different cigarette brands for tobacco raw materials allocated in the enterprise in the last three years, as shown in table 3 below.
Table 3.
10 efficacies are obtained, which in turn are defined as natural numbers 1-10, i.e. i e {1,2,3 … … 10 }.
Selecting 12 tobacco leaf quality characteristic indexes including aroma quality, aroma amount, permeability, miscellaneous gas, fineness, softness, mellow feeling, irritation, dryness, aftertaste, smoke concentration and strong ratio as characteristic J, sequentially expressing the characteristic J by natural numbers 1-12, namely J ∈ {1,2,3 … … 12}, evaluating and scoring through a tobacco industry standard YC/T530 + 2015 tobacco leaf quality and style characteristic sensory evaluation method to obtain characteristic values of various representative tobacco leaf raw material samples, calculating the average value of various characteristics of all tobacco leaf raw material samples classified in the same efficacy i, and taking the average value as the quality requirement J of each characteristic J in each efficacy iijThe results are shown in Table 4 below.
Table 4.
(2) And for each type of efficacy i, constructing feature importance comparison matrixes according to a score scaling method of 9/9-9/1 to obtain 10 importance comparison matrixes. Since the importance matrix also needs to be normalized separately: and dividing the scale value of each column by the sum of the scale values of the column to obtain a normalized matrix. And summing the data of each row of the normalized matrix to obtain the feature vector of the corresponding feature. Finally, all the feature vectors need to be summed, and each feature vector is divided by the sum value to obtain the weight of the corresponding feature. For simplicity, the normalization matrix and the significance comparison matrix are counted in the same table, as shown in tables 5-14 below.
TABLE 5 comparison matrix and normalization matrix for significance of each feature of efficacy 1
TABLE 6 comparison matrix and normalization matrix for significance of each feature of efficacy 2
TABLE 7 comparison matrix and normalization matrix for significance of each feature of efficacy 3
TABLE 8 efficacy 4 feature importance comparison matrix and normalization matrix
TABLE 9 comparison matrix and normalization matrix for significance of each feature of efficacy 5
TABLE 10 comparison matrix and normalization matrix for significance of each feature of efficacy 6
TABLE 11 comparison matrix and normalization matrix for significance of each feature of efficacy 7
TABLE 12 comparison matrix and normalization matrix for significance of each feature of efficacy 8
TABLE 13 efficacy 9 feature importance comparison matrix and normalization matrix
TABLE 14 comparison matrix and normalization matrix for significance of each feature of efficacy 10
And (3) checking consistency:
the maximum characteristic root of each efficacy i is calculated according to the maximum characteristic root formula (formula 1), and c.i. is calculated through the consistency index formula (formula 2), and c.r. is calculated through the random consistency ratio formula (formula 3), and the calculation results are as shown in table 15 below.
Table 15.
| Efficacy of | Efficacy 1 | Efficacy 2 | Effect 3 | Effect 4 | Effect 5 | Effect 6 | Effect 7 | Effect 8 | Efficacy 9 | Efficacy 10 |
| Root of maximum feature | 12.027 | 12 | 12.025 | 12.205 | 12.278 | 12.028 | 12.284 | 12.027 | 12.031 | 12.024 |
| CI | 0.0025 | 0 | 0.0022 | 0.0186 | 0.0253 | 0.0026 | 0.0258 | 0.00251 | 0.00282 | 0.0022 |
| CR | 0.0016 | 0 | 0.0015 | 0.0122 | 0.0166 | 0.0017 | 0.0169 | 0.00165 | 0.00186 | 0.00144 |
As can be seen from table 15, the c.r. value for each efficacy i is less than 0.1, consistent with the compliance test.
(3) Calculating a suitability evaluation weight Sij＝(Zij×100)÷Jij(ii) a For example, efficacy 1 and suitability evaluation weight S of fragrance quality 111＝(Z11×100)÷J110.108 × 100 ÷ 3.3, all SijThe calculation results of (a) are shown in the following Table 16.
For simplification of the table, the average value J shown in table 4 isijBy leaving a decimal place to be roundedThe values after the treatment, similarly, weights Z described in tables 5 to 14ijThe results are all values after leaving three decimal places and rounding. In calculating the suitability evaluation weight, it is preferable to directly use the numerical values without the decimal place left and without the rounding process for calculation to improve the accuracy, and the numerical values obtained in table 16 are calculated using the numerical values without the decimal place left, so that the data in table 16 slightly differs from the data obtained by the table calculation.
Table 16.
(4) Determining each characteristic value G of the tobacco leaf raw material to be positionedjThe applicability score H of the tobacco leaf raw material to be positioned under a certain efficacy ii＝∑(Gj×Sij) Wherein j is used as a variable for summing. For example, the suitability score H for a tobacco leaf feedstock at efficacy 11＝G1×S11+G2×S12+G3×S13+G4×S14+G5×S15+G6×S16+G7×S17+G8×S18+G9× S19+G10×S110+G11×S111+G12×S112. The larger the applicability score of the tobacco leaf raw material to be positioned in a certain efficacy i is, the more suitable the tobacco leaf raw material to be positioned is as a raw material for preparing cigarettes with the efficacy i.
The 11 grades of tobacco leaves allocated in a certain tobacco leaf base are taken, the characteristic values of the tobacco leaves are measured, the applicability score is calculated, and the calculation results are shown in the following table 17.
Table 17.
| Variety of (IV) C | Grade | Efficacy 1 | Efficacy 2 | Effect 3 | Effect 4 | Effect 5 | Effect 6 | Effect 7 | Effect 8 | Efficacy 9 | Efficacy 10 |
| Yunyan 87 | C2F | 108.60 | 115.97 | 129.10 | 111.45 | 124.97 | 122.12 | 118.73 | 124.79 | 132.35 | 133.47 |
| Yunyan 87 | C1F | 107.51 | 114.22 | 128.16 | 110.40 | 121.40 | 120.55 | 115.25 | 117.86 | 131.50 | 133.46 |
| Yunyan 87 | C2L | 105.10 | 111.73 | 125.15 | 107.75 | 118.07 | 117.88 | 112.31 | 114.84 | 128.86 | 130.41 |
| Yunyan 87 | C1L | 104.27 | 110.85 | 124.29 | 107.09 | 118.33 | 116.85 | 112.11 | 115.38 | 127.38 | 129.31 |
| Yunyan 87 | C3F | 104.81 | 111.75 | 125.37 | 107.41 | 118.47 | 118.18 | 111.39 | 114.50 | 128.73 | 130.89 |
| K326 | C1L | 101.95 | 109.17 | 122.24 | 104.44 | 115.53 | 115.44 | 108.07 | 111.66 | 125.22 | 127.43 |
| K326 | C2L | 98.48 | 105.79 | 118.36 | 100.59 | 111.68 | 112.18 | 103.75 | 108.10 | 121.65 | 123.64 |
| Yunyan 87 | C3L | 95.04 | 101.79 | 113.48 | 97.31 | 107.78 | 107.41 | 101.64 | 105.68 | 116.55 | 117.79 |
| Yunyan 87 | B1F | 93.78 | 99.07 | 110.63 | 97.30 | 107.97 | 103.49 | 104.27 | 108.21 | 113.49 | 113.50 |
| Yunyan 87 | B2F | 92.37 | 97.65 | 109.15 | 96.05 | 107.28 | 101.96 | 103.26 | 107.79 | 111.79 | 111.91 |
| Yunyan 87 | C4F | 93.08 | 99.50 | 111.27 | 95.68 | 106.88 | 104.97 | 100.62 | 105.07 | 113.85 | 115.54 |
(5) As can be seen from table 17, the applicability scores of C2F, C1F, C2L, C1L, C3F in the cloud cigarette 87 and C1L in the K326 in each efficacy are all greater than 100, and therefore, all of them can be used as raw materials for preparing any one of the efficacy 1-10 cigarette products, that is, their applicable range is efficacy 1-10. And the C2L in the K326 has the applicability score of less than 100 under the effect 1 and the applicability score of more than 100 under the effects 2-10, so that the cigarette is not suitable for being used as a raw material for preparing the cigarette product with the effect 1, but can be used as a raw material for any one of the cigarette products with the effects 2-10, namely, the application range of the cigarette product is 2-10. C3L in the cloud cigarette 87 is not suitable for preparing cigarette products with effects 1 and 4, and B1F, B2F and C4F in the cloud cigarette 87 are not suitable for preparing cigarette products with effects 1,2 and 4, but can be used for preparing cigarette products with other effects.
The specific embodiments described herein are merely illustrative of the spirit of the invention. Various modifications or additions may be made to the described embodiments or alternatives may be employed by those skilled in the art without departing from the spirit or ambit of the invention as defined in the appended claims.
Claims (7)
1. A tobacco application range positioning method based on cigarette formula efficacy is characterized in that: the method comprises the following steps:
respectively selecting representative tobacco leaf raw material samples with each type of efficacy i according to different formula efficacies of the cigarettes; selecting a plurality of tobacco leaf quality characteristic indexes as characteristics J, detecting characteristic values of the representative tobacco leaf raw material samples, and determining the quality requirement J of each characteristic J in each type of efficacy i according to the characteristic valuesij；
For each type of efficacy i, constructing a feature importance comparison matrix according to the scale, and calculating a feature vector of each feature j after normalizing the feature importance comparison matrix; then, dividing each feature vector by the sum of all feature vectors to obtain the weight Z of each feature j in each type of efficacy iij；
Calculating a suitability evaluation weight Sij=（Zij×100）/ Jij；
Determining each characteristic value G of the tobacco leaf raw material to be positionedjThe applicability score H of the tobacco leaf raw material to be positioned under a certain efficacy ii=∑（Gj×Sij）；
If H is presentiMore than or equal to 100, the raw material to be positioned is suitable for the efficacy i.
2. The method for positioning the applicable range of tobacco leaves based on the cigarette formula efficacy according to claim 1, wherein the method comprises the following steps: in the step (2), a feature importance comparison matrix is constructed according to a 9/9-9/1 score scaling method.
3. The method for positioning the applicable range of tobacco leaves based on the cigarette formula efficacy according to claim 1, wherein the method comprises the following steps: in the step (2), a consistency checking step is further included: and calculating the maximum eigenvalue of each feature importance comparison matrix, and calculating a consistency index according to a consistency index formula.
4. The tobacco application range positioning method based on cigarette formula efficacy according to claim 3, characterized in that: further comprising the step of calculating a random consistency ratio from the consistency indicator.
5. The method for positioning the applicable range of tobacco leaves based on the cigarette formula efficacy according to claim 1, wherein the method comprises the following steps: in the step (1), the selected tobacco leaf quality characteristic indexes comprise: quality of fragrance, amount of fragrance, penetrability, miscellaneous gas, fineness, softness, mellow feeling, irritation, dryness, aftertaste, smoke concentration and strength ratio.
6. The method for positioning the applicable range of tobacco leaves based on the cigarette formula efficacy according to claim 1, wherein the method comprises the following steps: and evaluating and scoring a plurality of tobacco leaf quality characteristic indexes through a tobacco industry standard YC/T530 + 2015 tobacco leaf quality style characteristic sensory evaluation method to obtain characteristic values.
7. The method for positioning the applicable range of tobacco leaves based on the cigarette formula efficacy according to claim 1, wherein the method comprises the following steps: in the step (4), the greater the applicability score of the tobacco leaf raw material to be positioned to a certain efficacy i is, the more suitable the tobacco leaf raw material to be positioned is as a raw material for preparing cigarettes with the efficacy i.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115486553A (en) * | 2022-09-16 | 2022-12-20 | 江苏中烟工业有限责任公司 | Method for representing threshold value of tobacco leaf raw material with low applicability in leaf group formula |
| CN115669979A (en) * | 2022-11-11 | 2023-02-03 | 云南省烟草农业科学研究院 | Classification formula threshing and redrying method of cinnabar smoke |
| CN116183834A (en) * | 2023-03-06 | 2023-05-30 | 江苏中烟工业有限责任公司 | Method for evaluating applicability of tobacco leaf raw materials to cigarettes of different circumferences |
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