CN108596448A - A method of oil tea weather quality ratings are established based on fuzzy mathematics method - Google Patents
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Abstract
The invention discloses a kind of methods for establishing oil tea weather quality ratings based on fuzzy mathematics method, it is analyzed by the climatic effect factor to tea seed quality, smaller and big to the Growth of Camellia oleifera and qualitative effects multiple climatic effect factors of related coefficient between the selection factor, based on climatic effect factor related data, dimensionless by establishing weight matrix, climatic factor handles, establishes climatic factor evaluate collection, fuzzy evaluation operation, to obtaining the grading of oil tea weather quality.The method of the present invention is directly analyzed and is judged to weather conditions data information, realizes the grading of the weather grade of oil tea, and just, objective, rapid and convenient, method is ripe, has practical directive significance and application value.
Description
Technical field
The present invention relates to fuzzy mathematics method technical field, specially one kind establishing oil tea weather product based on fuzzy mathematics method
The method of matter grading.
Technical background
Oil tea is Theaceae Camellia evergreen dungarunga, is the distinctive woody oil tree species in Subtropic of China Hills.Tea
Oil is good edible oil, contains unsaturated fatty acid 94% or so, is easily digested and assimilated for human body.Oil tea enjoyed light temperature avoid it is cold, with
It is best that Mid-subtropical regions cultivate economic benefit.
It is many to influence oil tea product qualitative factor, there is cultural factors, kind factor, processing method factor etc..Weather is to oil
The influence of tea includes three aspects, i.e.,：Influence to growth, the influence to yield, the influence to quality.
There are many advantageous meteorological condition during the Growth of Camellia oleifera of Anhui Tongchen area, and heat condition either average temperature of the whole year is also
The needs of oil tea is to meteorological condition can be met by being winter most cold monthly mean temperature or >=10 DEG C of active accumulated temperature, especially
The frost-free period high temperature number of days of longer, 8~September max. daily temperature >=35 DEG C is less, florescence temperature is higher, to Growth of Camellia oleifera and its
The formation of better quality is particularly advantageous；Moisture condition can meet Growth of Camellia oleifera needs substantially, wherein 7, August is abundant, to oil tea
Fruit and oil and fat accumulation are highly advantageous；Illumination condition comparative superiority, especially annual percentage of sunshine is larger, the illumination of 6~August
Intensity is stronger, and advantageous Growth of Camellia oleifera forms good quality.And unfavorable meteorologic factor mainly has：(1) a small number of florescence in time gas
Temperature is relatively low, and the later stage of especially blooming, which is often attacked by cold air, to be influenced, and temperature drops sharply to oil tea and blooms the facing of requirement
Below boundary's temperature；There is rainy weather in some florescences in time, and rainfall, rain day are all relatively more, these unfavorable meteorologic factors are neither
It blooms pollination conducive to oil tea, is also unfavorable for forming preferable oil tea quality.(2) a small number of time winter temperatures are low, cause oil tea new
Raw branch dead, young fruit of largely enduring cold endures cold and falls off.It is extremely minimum if super cold wave occurs in Tongcheng on January 23rd~25,2016
- 10.5 DEG C of temperature, -12 DEG C of part oil tea producing region Annual lowest climate temperature is hereinafter, have greatly not Growth of Camellia oleifera and quality responses
Profit influences.(3) in terms of long-run average, 7, August part precipitation be fully able to meet Property of Tea oil Tree Fruit and expand requirement to precipitation, but by
During the period precipitation annual change is larger, often has arid generation, influences tea-oil tree yield and quality responses.
Influence of the weather conditions to Growth of Camellia oleifera is most important, and the judge of weather conditions objective can reflect the product of oil tea
Matter, but currently, there is no a set of relative maturities and the objective method for being directed to oil tea weather quality ratings.
Invention content
It is an object of the invention to：A kind of method for establishing oil tea weather quality ratings based on fuzzy mathematics method is provided, it can
Weather conditions data information is analyzed and be judged, the grading of the weather grade of oil tea is realized, it is just, objective, quickly just
Victory, method is ripe, has practical directive significance and application value.
To achieve the goals above, the present invention provides the following technical solutions：
A method of oil tea weather quality ratings are established based on fuzzy mathematics method, are included the following steps：
S1, climatic factor selection：It is analyzed by the climatic effect factor to tea seed quality, chooses correlation between the factor
Smaller and big to the Growth of Camellia oleifera and qualitative effects multiple climatic effect factor X of coefficient；
S2, weight matrix is established：Using expert graded, marking evaluation is carried out to each climatic effect factor X, and to each gas
The scores of the time factor remake normalized after carrying out synthesis, it is established that weight matrix A；
The dimensionless processing of S3, climatic factor：(0,1) is carried out to each climatic effect factor X data using empirical method and changes nothing
Dimension processing, obtains dimensionless data Y；
S4, climatic factor evaluate collection is established：Degree of membership of each climatic factor to tea seed qualitative effects is analyzed, with weather shadow
It rings factor X nondimensionalizations treated that data Y is foundation, set up out weather factor evaluation collection R；
S5, fuzzy evaluation operation：Fuzzy evaluation operation is carried out to weight matrix A and climatic factor evaluate collection R, using matrix
Multiplication obtains fuzzy row matrix B, to obtain the grading of oil tea weather quality；The fuzzy row matrix B, calculation formula are：
B=A oR (wherein " o " indicates blurring mapping).
Preferably, in S1 steps, the climatic effect factor X is four, respectively,
X1：The temperature on average (DEG C) of mid-October prior year to early November,
X2：The sunshine total hour (hour) of mid-October prior year to early November,
X3：The high temperature number of days (day) of max. daily temperature >=35 DEG C during 7~August of current year,
X4:The gross precipitation R ' of 7~August of current year -7~August of current year intra day ward >=25 millimeter number of days (day) n*25
(millimeter), i.e. X4=R '-n*25, wherein R ' are the gross precipitation of 7~August of current year, and n is current year 7~August intra day ward
>=25 millimeters of numbers of days (day)；
In S3 steps, the dimensionless processing calculation formula is：
Preferably, in S2 steps, the expert graded is：Seven oil tea kinds are selected in manufacturing enterprise and units concerned
It plants, the expert of management aspect, marking evaluation is carried out to each climatic effect factor X respectively, wherein each expert is to these weathers
The sum of scoring of impact factor X is 100 points, and then synthesis goes out the sum of each expert analysis mode of each climatic effect factor X b respectivelyi, most
After remake normalized, it is established that weight matrix A；
The normalized calculation is：
(wherein m is the number of climatic effect factor X)；
The weight matrix A is：
A=(ω1, ω2, ω3, ω4, ωm), wherein m is climatic effect factor number.
Preferably, the S4 steps are established in climatic factor evaluate collection, are specifically comprised the following steps：
S4-1, tea seed weather quality single pollution assessment index is established：When oil tea weather quality grade is classified, using one
As, good, excellent, special excellent four grades, indicated with the vector of the degree of membership (i.e. similarity degree) relative to four grades, specifically
For：Generally [0,0.25) it is, good [0.25,0.5), it is excellent [0.5,0.75), special excellent [0.75,1]；
S4-2, it establishes climatic effect factor evaluation collection R and determines table：
According to the evaluation index of the single factor, the critical value in evaluate collection section is respectively：A1=0.25, a2=0.5, a3
=0.75；
For degree of membership for 1, the degree of membership of remaining rank is 0 when being located at intermediate quantity (i.e. section is hit exactly) of two boundaries with factor X；
When X leaves midpoint in section to be moved to the left or right, the degree of membership of region is reduced since 1, while other areas
The degree of membership in domain increases since 0, and the climatic effect factor evaluation collection R of foundation determines that table is as follows：
Factor evaluation collection R determines table
(wherein, Y is the data that climatic effect factor X carries out that (0,1) changes dimensionless processing, a1、a2、a3Respectively oil tea gas
The critical value in quality grade evaluate collection section is waited, respectively：a1=0.25, a2=0.5, a3=0.75)；
The R Matrix Calculatings calculation of S4-3, each climatic effect factor X：
Table is determined using climatic effect factor evaluation collection R, calculates the R matrixes of each climatic effect factor X, respectively：R1
(R11, R12, R13, R14)、R2(R21, R22, R23, R24)、 R3(R31, R32, R33, R34)、······、Rm(Rm1, Rm2, Rm3,
Rm4), wherein m is climatic effect factor number；
S4-4, summarize climatic factor evaluate collection R：The R matrixes of each climatic effect factor X of comprehensive previous step, summarize
Climatic factor evaluate collection R, specially：
Wherein m is climatic effect factor number.
Preferably, in S5 steps, the fuzzy row matrix
The grading of oil tea weather quality is judged to obscure the maximum value of four numbers in row matrix B, if maximum value is first
Number is then rated general；If maximum value is second number, it is rated good；If maximum value is third number, it is rated
It is excellent；If maximum value is the 4th number, it is rated special excellent.
The beneficial effects of the present invention are：
A kind of method that oil tea weather quality ratings are established based on fuzzy mathematics method of the present invention, by tea seed quality
The climatic effect factor is analyzed, smaller and big to the Growth of Camellia oleifera and qualitative effects multiple weathers of related coefficient between the selection factor
Impact factor, be based on climatic effect factor related data, through foundation weight matrix, climatic factor dimensionless handle,
Climatic factor evaluate collection, fuzzy evaluation operation are established, to obtaining the grading of oil tea weather quality.The method of the present invention,
Directly weather conditions data information is analyzed and judged, realizes the grading of the weather grade of oil tea, it is just, objective, quick
Convenient, method is ripe, has practical directive significance and application value.
Specific implementation mode
In order to facilitate the understanding of those skilled in the art, with reference to specific embodiment, the present invention is further illustrated.
A method of oil tea weather quality ratings are established based on fuzzy mathematics method, are included the following steps：
S1, climatic factor selection：It is analyzed by the climatic effect factor to tea seed quality, chooses correlation between the factor
Smaller and big to the Growth of Camellia oleifera and qualitative effects multiple climatic effect factor X of coefficient, finally determine four climatic effects because
Son, respectively,
X1：The temperature on average (DEG C) of mid-October prior year to early November,
X2：The sunshine total hour (hour) of mid-October prior year to early November,
X3：The high temperature number of days (day) of max. daily temperature >=35 DEG C during 7~August of current year,
X4:The gross precipitation R ' of 7~August of current year -7~August of current year intra day ward >=25 millimeter number of days (day) n*25
(millimeter), i.e. X4=R '-n*25, wherein R ' are the gross precipitation of 7~August of current year, and n is current year 7~August intra day ward
>=25 millimeters of numbers of days (day).
S2, weight matrix is established：Using expert graded, marking evaluation is carried out to each climatic effect factor X, and to each gas
The scores of the time factor remake normalized after carrying out synthesis, it is established that weight matrix A；
The expert graded is：Manufacturing enterprise and units concerned select seven oil teas plantations, management aspect expert,
Marking evaluation is carried out to each climatic effect factor X respectively, wherein scoring the sum of of each expert to these climatic effect factors X
It it is 100 points, then synthesis goes out the sum of each expert analysis mode of each climatic effect factor X b respectivelyi, normalized is finally remake, is built
Erect weight matrix A；
The normalized calculation is：
(wherein m is the number of climatic effect factor X)；
The weight matrix A is：
A=(ω1, ω2, ω3, ω4, ωm), wherein m is climatic effect factor number.
When climatic effect factor X be four, and use expert graded, obtain each climatic effect Factor Weight statistics,
(being shown in Table 1) specific as follows：
1 each Factor Weight of table counts
It can thus be concluded that weight matrix A is：
A=(0.221,0.286,0.150,0.343).
The dimensionless processing of S3, climatic factor：(0,1) is carried out to each climatic effect factor X data using empirical method and changes nothing
Dimension processing, obtains dimensionless data Y；
Wherein dimensionless processing calculation formula be：
S4, climatic factor evaluate collection is established：Degree of membership of each climatic factor to tea seed qualitative effects is analyzed, with weather shadow
It rings factor X nondimensionalizations treated that data Y is foundation, set up out weather factor evaluation collection R, specifically comprise the following steps：
S4-1, tea seed weather quality single pollution assessment index is established：When oil tea weather quality grade is classified, using one
As, good, excellent, special excellent four grades, indicated with the vector of the degree of membership (i.e. similarity degree) relative to four grades, specifically
For：Generally [0,0.25) it is, good [0.25,0.5), it is excellent [0.5,0.75), special excellent [0.75,1]；
S4-2, it establishes climatic effect factor evaluation collection R and determines table：
According to the evaluation index of the single factor, the critical value in evaluate collection section is respectively：A1=0.25, a2=0.5, a3
=0.75；
For degree of membership for 1, the degree of membership of remaining rank is 0 when being located at intermediate quantity (i.e. section is hit exactly) of two boundaries with factor X；
When X leaves midpoint in section to be moved to the left or right, the degree of membership of region is reduced since 1, while other areas
The degree of membership in domain increases since 0, and the climatic effect factor evaluation collection R of foundation determines that table is following (being shown in Table 2)：
2 factor evaluation collection R of table determines table
(wherein, Y is the data that climatic effect factor X carries out that (0,1) changes dimensionless processing, a1、a2、a3Respectively oil tea gas
The critical value in quality grade evaluate collection section is waited, respectively：a1=0.25, a2=0.5, a3=0.75)；
The R Matrix Calculatings calculation of S4-3, each climatic effect factor X：
Table is determined using climatic effect factor evaluation collection R, calculates the R matrixes of each climatic effect factor X, respectively：R1
(R11, R12, R13, R14)、R2(R21, R22, R23, R24)、 R3(R31, R32, R33, R34)、······、Rm(Rm1, Rm2, Rm3,
Rm4), wherein m is climatic effect factor number.
S4-4, summarize climatic factor evaluate collection R：The R matrixes of each climatic effect factor X of comprehensive previous step, summarize
Climatic factor evaluate collection R, specially：
Wherein m is climatic effect factor number.
When climatic effect factor X is four (i.e. m=4), respectively X1、X2、X3、X4When, climatic factor evaluate collection R, specifically
For：
S5, fuzzy evaluation operation：Fuzzy evaluation operation is carried out to weight matrix A and climatic factor evaluate collection R, using matrix
Multiplication obtains fuzzy row matrix B, to obtain the grading of oil tea weather quality；The fuzzy row matrix B, calculation formula are：
B=A oR (wherein " o " indicates blurring mapping).
When climatic effect factor X is four (i.e. m=4), fuzzy row matrix
(wherein, in S2, establish in weight matrix step, using expert graded, obtained weight matrix A be (0.221,
0.286,0.150,0.343), i.e. ω1=0.221, ω2=0.286, ω3=0.150, ω4=0.343).
The grading of oil tea weather quality is judged to obscure the maximum value of four numbers in row matrix B, if maximum value is first
Number is then rated general；If maximum value is second number, it is rated good；If maximum value is third number, it is rated
It is excellent；If maximum value is the 4th number, it is rated special excellent.
Embodiment 1：
When grading to the oil tea weather quality in 2001 annual Anhui Province Tongcheng City regions, it is based on using one kind of the present invention
The method that fuzzy mathematics method establishes oil tea weather quality ratings, and especially by above-mentioned implementation steps, can be obtained：
(1), X is obtained by inquiring the weather meteorological data data in Anhui Province Tongcheng City region1：Prior year (2000) 10
The temperature on average of the middle of the month to early November is 12.6 (DEG C), X2：The day of (2000) mid-October to early November prior year
It is 101.6 (hours), X according to total hour3：The day with high temperature of max. daily temperature >=35 DEG C during current year (2001) 7~August
Number is 20 (days), X4:Gross precipitation P- current years (2001) 7~August intra day ward of current year (2001) 7~August >=
25 millimeters of number of days (day) n*25 are 271.2 (millimeters)；
(2) in described previously, using expert graded, obtaining weight matrix A is：
A=(0.221,0.286,0.150,0.343).
(3) calculation formula is handled by dimensionless, the dimensionless of climatic factor is handled, Y is obtained1=0.389, Y2=
0.393、Y3=0.375, Y4=0.929；
(4) 2 climatic effect factor evaluation collection R of the table of comparisons determines table, because of Y1=0.389, meet condition
(wherein a1=0.25, a2=0.5, a3=0.75),
So
Similarly, it determines table using 2 climatic effect factor evaluation collection R of table, and combines Y2=0.393, Y3=0.375, Y4=
0.929, calculate R21=0.023364, R22=0.929909, R23=0.035045, R24=0.011682, R31=0, R32=
1, R33=0, R34=0, R41=0.023568, R42=0.047136, R43=0.070705, R44=0.858591.
The climatic factor evaluate collection R summarized, specially：
(5) fuzzy evaluation operation is carried out to weight matrix A and climatic factor evaluate collection R, using matrix multiplication, i.e.,
In this fuzzy row matrix B, 0.640838 is maximum, while 0.640838 is in second position i.e. second number,
So the oil tea weather quality ratings in 2001 annual Anhui Province Tongcheng City regions are good.
Embodiment 2：
When grading to the oil tea weather quality in 2017 annual Anhui Province Tongcheng City regions, it is based on using one kind of the present invention
The method that fuzzy mathematics method establishes oil tea weather quality ratings, specific implementation step is identical with embodiment 1, can be obtained：
(1), X is obtained by inquiring the weather meteorological data data in Anhui Province Tongcheng City region1：15.6 (DEG C), X2：72.2
(hour), X3：19 (days), X4:(303.1 millimeter)；
(2) in described previously, using expert graded, obtaining weight matrix A is：
A=(0.221,0.286,0.150,0.343).
(3) calculation formula is handled by dimensionless, the dimensionless of climatic factor is handled, Y is obtained1=0.941, Y2=
0.213、Y3=0.406, Y4=0.692；
(4) 2 climatic effect factor evaluation collection R of the table of comparisons determines table, because of Y1=0.941, meet condition Y ＞ a3(wherein a1=
0.25、a2=0.5, a3=0.75),
So
Similarly, it determines table using 2 climatic effect factor evaluation collection R of table, and combines Y2=0.213, Y3=0.406, Y4=
0.692, calculate R21=0.574864, R22=0.212568, R23=0.141712, R24=0.070856, R31=
0.041667, R32=0.875, R33=0.0625, R34=0.020833, R41=0.044608, R42=0.089215, R43=
0.732354, R44=0.133823.
The climatic factor evaluate collection R summarized, specially：
(5) fuzzy evaluation operation is carried out to weight matrix A and climatic factor evaluate collection R, using matrix multiplication, i.e.,
In this fuzzy row matrix B, 0.314098 is maximum, while 0.314098 is in third position i.e. third number,
So the oil tea weather quality ratings in 2017 annual Anhui Province Tongcheng City regions are excellent.
Embodiment 3：
When grading to the oil tea weather quality in 2002 annual Anhui Province Tongcheng City regions, it is based on using one kind of the present invention
The method that fuzzy mathematics method establishes oil tea weather quality ratings, specific implementation step is identical with embodiment 1, and difference is：
Weather meteorological data data by inquiring Anhui Province Tongcheng City region obtains X1：14.8 (DEG C), X2：193.6 is (small
When), X3：13 (days), X4:(166.9 millimeter).
By the method for the invention, calculating fuzzy row matrix B is：
B=(0.056951,0.117027,0.444141,0.381881)
In this fuzzy row matrix B, 0.444141 is maximum, while 0.444141 is in third position i.e. third number,
So the oil tea weather quality ratings in 2002 annual Anhui Province Tongcheng City regions are excellent.
Embodiment 4-14：
When grading respectively to the oil tea weather quality in the year Anhui Province 2006-2016 Tongcheng City region, using this hair
A kind of bright method for establishing oil tea weather quality ratings based on fuzzy mathematics method, specific implementation step is identical with embodiment 1, different
Point is：
Weather meteorological data data by inquiring Anhui Province Tongcheng City region obtains X1、X2、 X3、X4, specific as follows (see
Table 3)：
The meteorological data of 3 2006-2016 year oil tea weather quality ratings of table
By the method for the invention, the oil tea weather quality in the year Anhui Province 2006-2016 Tongcheng City region is calculated separately out
The fuzzy row matrix B of grading, and its specific grade is judged out, it is (being shown in Table 4) specific as follows：
The fuzzy row matrix B and its grading table of 4 2006-2016 year oil tea weather quality ratings of table
It is above-mentioned that invention is exemplarily described, it is clear that present invention specific implementation is not subject to the restrictions described above, only
Use this insubstantial improvement of inventive concept and technical scheme of the present invention progress, or the not improved design by invention
Other occasions are directly applied to technical solution, within protection scope of the present invention.
Claims (5)
1. a kind of method for establishing oil tea weather quality ratings based on fuzzy mathematics method, which is characterized in that include the following steps：
S1, climatic factor selection：It is analyzed by the climatic effect factor to tea seed quality, chooses related coefficient between the factor
Smaller and big to Growth of Camellia oleifera and qualitative effects multiple climatic effect factor X；
S2, weight matrix is established：Using expert graded, marking evaluation carried out to each climatic effect factor X, and to each weather because
The scores of son remake normalized after carrying out synthesis, it is established that weight matrix A；
The dimensionless processing of S3, climatic factor：(0,1) is carried out to each climatic effect factor X data using empirical method and changes dimensionless
Processing, obtains dimensionless data Y；
S4, climatic factor evaluate collection is established：Analyze degree of membership of each climatic factor to tea seed qualitative effects, with climatic effect because
Sub- X nondimensionalizations treated data Y is foundation, sets up out weather factor evaluation collection R；
S5, fuzzy evaluation operation：Fuzzy evaluation operation is carried out to weight matrix A and climatic factor evaluate collection R, using Matrix Multiplication
Method obtains fuzzy row matrix B, to obtain the grading of oil tea weather quality；The fuzzy row matrix B, calculation formula are：B
=A oR (wherein " o " indicates blurring mapping).
2. a kind of method for establishing oil tea weather quality ratings based on fuzzy mathematics method according to claim 1, feature
It is,
In S1 steps, the climatic effect factor X is four, respectively,
X1：The temperature on average (DEG C) of mid-October prior year to early November,
X2：The sunshine total hour (hour) of mid-October prior year to early November,
X3：The high temperature number of days (day) of max. daily temperature >=35 DEG C during 7~August of current year,
X4:The gross precipitation R ' of 7~August of current year -7~August of current year intra day ward >=25 millimeter number of days (day) n*25 (millis
Rice), i.e. X4=R '-n*25, wherein R ' are the gross precipitation of 7~August of current year, and n is 7~August of current year intra day ward >=25
Millimeter number of days (day)；
In S3 steps, the dimensionless processing calculation formula is：
3. a kind of method for establishing oil tea weather quality ratings based on fuzzy mathematics method according to claim 1, feature
It is, in S2 steps, the expert graded is：Seven oil tea plantations, managers are selected in manufacturing enterprise and units concerned
The expert in face carries out marking evaluation to each climatic effect factor X respectively, wherein each expert is to these climatic effect factors X
The sum of scoring be 100 points, then respectively it is comprehensive go out each climatic effect factor X the sum of each expert analysis mode bi, finally remake and return
One change is handled, it is established that weight matrix A；
The normalized calculation is：
(wherein m is the number of climatic effect factor X)；
The weight matrix A is：
A=(ω1, ω2, ω3, ω4, ωm), wherein m is climatic effect factor number.
4. a kind of method for establishing oil tea weather quality ratings based on fuzzy mathematics method according to claim 3, feature
It is, the S4 steps are established in climatic factor evaluate collection, are specifically comprised the following steps：
S4-1, tea seed weather quality single pollution assessment index is established：When oil tea weather quality grade is classified, using it is general,
Good, excellent, special excellent four grades, are indicated, specially with the vector of the degree of membership (i.e. similarity degree) relative to four grades：
Generally [0,0.25) it is, good [0.25,0.5), it is excellent [0.5,0.75), special excellent [0.75,1]；
S4-2, it establishes climatic effect factor evaluation collection R and determines table：
According to the evaluation index of the single factor, the critical value in evaluate collection section is respectively：A1=0.25, a2=0.5, a3=
0.75；
For degree of membership for 1, the degree of membership of remaining rank is 0 when being located at intermediate quantity (i.e. section is hit exactly) of two boundaries with factor X；Work as X
When leaving midpoint in section and being moved to the left or right, the degree of membership of region is reduced since 1, while other regions
Degree of membership increases since 0, and the climatic effect factor evaluation collection R of foundation determines that table is as follows：
Factor evaluation collection R determines table
(wherein, Y is the data that climatic effect factor X carries out that (0,1) changes dimensionless processing, a1、a2、a3Respectively oil tea weather product
The critical value in matter grade evaluate collection section, respectively：a1=0.25, a2=0.5, a3=0.75)；
The R Matrix Calculatings calculation of S4-3, each climatic effect factor X：
Table is determined using climatic effect factor evaluation collection R, calculates the R matrixes of each climatic effect factor X, respectively：R1(R11, R12,
R13, R14)、R2(R21, R22, R23, R24)、R3(R31, R32, R33, R34)、······、Rm(Rm1, Rm2, Rm3, Rm4), wherein m
For climatic effect factor number；
S4-4, summarize climatic factor evaluate collection R：The R matrixes of each climatic effect factor X of comprehensive previous step, summarize weather
Factor evaluation collection R, specially：
Wherein m is climatic effect factor number.
5. a kind of method for establishing oil tea weather quality ratings based on fuzzy mathematics method according to claim 4, feature
It is, in S5 steps, the fuzzy row matrix
R22+ω3*R32+······+ωm*Rm2, ω1*R13+ω2*R23+ω3*R33+······+ωm*Rm3,
ω1*R14+ω2*R24+ω3*R34+······+ωm*Rm4)；
The grading of oil tea weather quality is judged to obscure the maximum value of four numbers in row matrix B, if maximum value is first number,
It is then rated general；If maximum value is second number, it is rated good；If maximum value is third number, it is rated excellent；If most
Big value is the 4th number, then is rated special excellent.
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| CN113111311A (en) * | 2021-04-09 | 2021-07-13 | 安徽农业大学 | Screening method for wheat yield influence factors in region along Huaihe river |
| CN116152006A (en) * | 2022-12-08 | 2023-05-23 | 福建省气象科学研究所 | Sweet potato climate quality assessment method and system |
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