CN105894026A - Figure classifying method based on fuzzy theory - Google Patents
Figure classifying method based on fuzzy theory Download PDFInfo
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Abstract
The invention relates to a figure classifying method based on a fuzzy theory. The method comprises the following steps of: determining whether the divided sections of a conventional figure classifying method is continuous and carrying out continuous processing on the divided sections if not; determining the lower limit value s, the upper limit value u, and the maximum likelihood value m of the triangular fuzzy number of each figure; determining the membership function of the triangular fuzzy number of each figure; establishing a fuzzy figure definition expression according to the membership function; substituting the measuring parameter of a user with figure to be measured into the expression in order to determine the figure membership of the user with figure to be measured. The method solves a problem that a conventional figure classifying method is not continuous and not completely accurate in figure classification.
Description
Technical field
The present invention relates to human engineering technical field, particularly relate to a kind of somatotype method based on fuzzy theory.
Background technology
Somatotype has important application in many fields, is the important evidence of garment size exploitation in dress designing field.
Under normal circumstances, Clothing Specialty personnel formulate the standard of size of clothes according to somatotype；Garment development personnel are according to clothes
Standard of size, design is suitable for the clothes of different building shape；Clothing Consuming person selects the clothes of corresponding type according to the build of oneself
Dress.The somatotype of human body all seems extremely important for garment enterprise or consumer itself as can be seen here.
Traditional somatotype method, is based on a certain item of body measurements, or several the modes combined, this
Or combine several and divide different intervals as classification foundation, the interval that buman body type is divided is divided into some points.Such as depend on
According to CNS, the somatotype method of women is divided into tetra-kinds of builds of Y, A, B and C human body.Wherein, chest measurement
Belonging to Y build with waistline difference at 19-24cm, belong to A build at 14-18cm, 9-13cm belongs to B build, 4-8cm
Belong to C build.
The buman body type classification having at present is a kind of method of absolute classification, and with regard to right and wrong, this is the shortcoming of this method maximum
That, say, that anyone build must be classified as a certain class.The disadvantage of sorting technique is exactly some people's at present
Which kind of build build, between two class builds, is attributed to the most suitable.And garment enterprise is the standard of size according to clothes
Producing clothes, the foundation that the standard of size of clothes is formulated is exactly buman body type classification, which results in a lot of people commercially
Select less than suitable clothes.Such as, chest measurement is respectively 18cm's and 19cm with waistline degree of enclosing poor (chest waist is poor)
Two women, if according to the somatotype method of existing CNS, chest waist difference be 18cm be belonging to A body
Type, chest waist difference be 19cm be belonging to Y build.And actually chest waist difference is respectively these two women of 18cm and 19cm
Build be closely.Garment enterprise is envisioned as a certain class build body everyone producing clothes in enormous quantities when
Material, the standard value only according to all kinds of builds produces clothes.This has resulted in current many people and has complained that a direct election is less than suitably
Clothes.
Summary of the invention
The present invention provides a kind of somatotype method based on fuzzy theory, solves present somatotype method discontinuity and right
Buman body type is classified the problem of not entirely accurate.
The technical solution adopted for the present invention to solve the technical problems is: provide a kind of somatotype side based on fuzzy theory
Method, comprises the following steps:
(1) judge that the demarcation interval of existing somatotype method is the most continuous, if discontinuous, demarcation interval is carried out even
Continuousization processes；
(2) value m that lower limit s of Triangular Fuzzy Number of each idiotype, higher limit u and possibility are maximum is determined；
(3) membership function of the Triangular Fuzzy Number of each idiotype is determined；
(4) set up fuzzy build definition expression formula according to membership function, the measurement parameter of build user to be measured is substituted into table
Reach the build degree of membership determining build user to be measured in formula.
Described step (1) chooses the median of two adjacent interval gaps as two after serialization when carrying out continuous treatment
Interval line of demarcation.
The membership function of described Triangular Fuzzy Number isWherein, x is body to be measured
The measurement parameter of type user.
The possibility that lower limit s is the sides adjacent that it the is less maximum of the Triangular Fuzzy Number of each idiotype in described step (2)
Value m, higher limit u is value m of the possibility maximum of the sides adjacent that it is bigger, and value m of possibility maximum is self interval
Center.
Beneficial effect
Owing to have employed above-mentioned technical scheme, the present invention compared with prior art, has the following advantages that and good effect:
The present invention uses the degree of membership of Triangular Fuzzy Number to represent the definite build of people.The method is used can definitely to represent a certain individual
Build for the subjection degree of dissimilar build, be not to fully belong to some classification build.Therefore, this invention
Meaning is to improve Chinese visible human classification GB and supplement, and is easy to enterprise's degree of membership according to consumer's build on this basis
Carry out dress designing, meet the actual products of consumer's build demand.
Accompanying drawing explanation
Fig. 1 is Triangular Fuzzy Number membership function figure；
Fig. 2 is Chinese women somatotype national standard schematic diagram；
Fig. 3 is the Chinese women somatotype national standard schematic diagram after serialization；
Fig. 4 is build membership function figure.
Detailed description of the invention
Below in conjunction with specific embodiment, the present invention is expanded on further.Should be understood that these embodiments be merely to illustrate the present invention and
It is not used in restriction the scope of the present invention.In addition, it is to be understood that after having read the content that the present invention lectures, people in the art
The present invention can be made various changes or modifications by member, and these equivalent form of values fall within the application appended claims equally and limited
Scope.
Embodiments of the present invention relate to a kind of somatotype method based on fuzzy theory, and the present invention is subordinate to based on Triangular Fuzzy Number
Genus degree function:Wherein: fuzzy number represents with (s, m, u).S and u divides
Not Wei the lower limit of fuzzy number and the upper limit, m is the value that possibility is maximum, and its functional digraph is as shown in Figure 1.
In order to traditional somatotype method is converted into fuzzy somatotype method, need to first determine whether that tradition build divides
The interval that class method divides is the most continuous.If continuously, being directly entered next step, if discontinuous, need to make it continuous.
Being illustrated in figure 2 the women somatotype interval distribution of CNS, these intervals are not connect as can be seen from the figure
Continue, need its serialization for this.
For the loss that the information making discontinuous somatotype interval is the fewest during serialization.Choose two adjacent regions
Between the median of gap as the interval [19,24] in two after serialization interval lines of demarcation, such as build Y and build A
Interval [14,18] are two discontinuous intervals, and the separation that after serialization, the two is interval is 18.5, other several idiotypes
Class interval, carrys out serialization according to same mode, and result is as shown in Figure 3.
Somatotype interval after this serialization is for determining lower limit s and higher limit u of Triangular Fuzzy Number, and possibility
Maximum value m.
Lower limit s of the Triangular Fuzzy Number of 1 build C and higher limit u, and value m that possibility is maximum
Chest waist difference belongs to build C in interval [4,8.5], so the value of Triangular Fuzzy Number possibility maximum is exactly the center in this interval,
I.e. (4+8.5)/2.Owing to the interval at build C place does not has somatotype type in left side, so cannot determine build C's
The lower limit of Triangular Fuzzy Number, and the interval right side at build C place is the class interval of build B, build C Triangle Module
The maximum of the class interval sticking with paste number is i.e. the value of the Triangular Fuzzy Number possibility maximum of build B, is i.e. (8.5+13.5)/2.
Lower limit s of the Triangular Fuzzy Number of 2 build B and higher limit u, and value m that possibility is maximum
Chest waist difference belongs to build B in interval [8.5,13.5], so the value of Triangular Fuzzy Number possibility maximum is exactly this interval
Center, i.e. (8.5+13.5)/2.Owing to the interval left side at build B place is the class interval of build C, build B divides
The lower limit of the Triangular Fuzzy Number of class interval is i.e. the possibility maximum of the Triangular Fuzzy Number of build C, is i.e. (4+8.5)/2.,
And the interval right side at build B place is the class interval of build A, the upper limit of the class interval of build B Triangular Fuzzy Number
Value is i.e. the possibility maximum of the Triangular Fuzzy Number of build A, be i.e. (13.5+18.5)/2. therefore, the s=6.25 of B build,
M=11, u=16.
Lower limit s of the Triangular Fuzzy Number of 3 build A and higher limit u, and value m that possibility is maximum
Chest waist difference belongs to build A in interval [13.5,18.5], so the value of Triangular Fuzzy Number possibility maximum is exactly this interval
Center, i.e. (13.5+18.5)/2.Owing to the interval left side at build A place is the class interval of build B, build A divides
The lower limit of the Triangular Fuzzy Number of class interval is i.e. the possibility maximum of the Triangular Fuzzy Number of build B, is i.e. (8.5+13.5)
/ 2, and the interval right side at build A place is the class interval of build Y, the class interval of build A Triangular Fuzzy Number upper
Limit value is i.e. the possibility maximum of the Triangular Fuzzy Number of build Y, be i.e. (18.5+24)/2. therefore, the s=11 of A build,
M=16, u=21.25.
Lower limit s of the Triangular Fuzzy Number of 4 build Y and higher limit u, and value m that possibility is maximum
Chest waist difference belongs to Y build in interval [18.5,24], so the value of Triangular Fuzzy Number possibility maximum is exactly this interval
Center, i.e. (18.5+24)/2.Owing to the interval left side at build Y place is the class interval of build A, build Y divides
The lower limit of the Triangular Fuzzy Number of class interval is i.e. the possibility maximum of the Triangular Fuzzy Number of build B, is i.e. (13.5+18.5)
/ 2, and the interval right side at build A place does not has somatotype interval, the upper limit of the class interval of build Y Triangular Fuzzy Number
Value cannot determine.
The membership function of 5 build C
Owing to there is no class interval on the left of build C, it is desirable to unknown build is 1 to the degree of membership summation of build YABC, so
The membership function of design build C is as follows:
Its functional digraph is as shown in Figure 4.
The membership function of 6 build B
Its functional digraph is as shown in Figure 4.
The membership function of 7 build A
Its functional digraph is as shown in Figure 4.
The membership function of 8 build Y
Its functional digraph is as shown in Figure 4.
Fuzzy build definition method is as follows: (MSC(x),MSB(x),MSA(x),MSY(x))
Wherein: MSCX () represents the build needing the to represent degree of membership to build C；MSBX () represents the build needing to represent
Degree of membership to build B；MSAX () represents the build needing the to represent degree of membership to build A.MSYX () represents needs table
The build the shown degree of membership to build Y.
Such as, the difference of women 1 and the chest measurement of women 2 and waistline is 18cm and 19cm respectively, according to formula (1) this female
Gonosome type respectively can be according to formula (1) to the degree of membership of country classification build CBAY, formula (2), formula (3) and public affairs
Formula (4) is tried to achieve, and the fuzzy build method for expressing of these two women is as follows: (0,0,0.62,0.38), (0,0,0.43,
0.57)。
Here, (0,0,0.62,0.38) refers to the build of women 1 is 0 to the degree of membership of country classification build C and B,
Degree of membership to country classification build A is 0.62, and the degree of membership to country classification build Y is 0.38.(0,0,0.43,0.57)
Be the build of women 2 be 0 to the degree of membership of country classification build C and B, to the degree of membership of country classification build A be
0.43, the degree of membership to country classification build Y is 0.57.
It is seen that, the present invention uses the degree of membership of Triangular Fuzzy Number to represent the definite build of people.Use the method can be true
Cut the build representing a certain individual for the subjection degree of dissimilar build, be not to fully belong to some classification build.
Therefore, the meaning of this invention is to improve Chinese visible human classification GB and supplement, and is easy to enterprise on this basis according to consumption
The degree of membership of person's build carries out dress designing, meets the actual products of consumer's build demand.
Claims (4)
1. a somatotype method based on fuzzy theory, it is characterised in that comprise the following steps:
(1) judge that the demarcation interval of existing somatotype method is the most continuous, if discontinuous, demarcation interval is carried out serialization
Process；
(2) value m that lower limit s of Triangular Fuzzy Number of each idiotype, higher limit u and possibility are maximum is determined；
(3) membership function of the Triangular Fuzzy Number of each idiotype is determined；
(4) set up fuzzy build definition expression formula according to membership function, the measurement parameter of build user to be measured is substituted into expression formula
The middle build degree of membership determining build user to be measured.
Somatotype method based on fuzzy theory the most according to claim 1, it is characterised in that described step (1) exists
Carry out the median the choosing two adjacent interval gaps during continuous treatment line of demarcation as two intervals after serialization.
Somatotype method based on fuzzy theory the most according to claim 1, it is characterised in that described Triangular Fuzzy Number
Membership function beWherein, x is the measurement parameter of build user to be measured.
Somatotype method based on fuzzy theory the most according to claim 1, it is characterised in that in described step (2)
Lower limit s of the Triangular Fuzzy Number of each idiotype is value m of the possibility maximum of the sides adjacent that it is less, and higher limit u is
Value m that the possibility of its bigger sides adjacent is maximum, the center that value m is self interval that possibility is maximum.
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| CN107093005A (en) * | 2017-03-24 | 2017-08-25 | 北明软件有限公司 | The method that tax handling service hall's automatic classification is realized based on big data mining algorithm |
| CN111126432A (en) * | 2019-11-14 | 2020-05-08 | 武汉纺织大学 | Human body type classification method for clothing design |
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| CN101034460A (en) * | 2007-04-13 | 2007-09-12 | 东华大学 | Method for online selling optimized size of clothes |
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| CN107093005A (en) * | 2017-03-24 | 2017-08-25 | 北明软件有限公司 | The method that tax handling service hall's automatic classification is realized based on big data mining algorithm |
| CN111126432A (en) * | 2019-11-14 | 2020-05-08 | 武汉纺织大学 | Human body type classification method for clothing design |
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