CN104392087B - A kind of overhead weapon station performance estimating method - Google Patents
A kind of overhead weapon station performance estimating method Download PDFInfo
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Abstract
The invention discloses a kind of overhead weapon station war performance estimating methods, data acquisition is carried out to overhead weapon station and obtains multiple performance indicators, the overhead weapon station Performance Measuring Indicators being made of overall layer performance indicator, system layer performance indicator, state layer performance indicator and variable layer performance indicator are built, the performance indicator weight sets of four levels is determined by grey relational grade computational methods；Fuzzy overall evaluation collection is obtained by Field Using Fuzzy Comprehensive Assessment and calculates variable layer performance indicator comprehensive evaluation value；Then state layer performance indicator comprehensive evaluation value is calculated according to variable layer performance indicator comprehensive evaluation value；According to state layer performance indicator comprehensive evaluation value computing system layer performance indicator comprehensive evaluation value；Overall layer performance indicator comprehensive evaluation value is finally calculated according to system layer performance indicator integrated value.This method establishes grey relational grade analysis model and model of fuzzy synthetic evaluation, overhead weapon station can be carried out it is objective, quantify, quick, effective performance evaluation and assessment.
Description
Technical field
The present invention relates to a kind of overhead weapon station performance estimating methods.
Background technology
At present, the external automatic weapon of armored vehicle is mainly machine gun, small-bore automatic gun or the howitzer hair of different bores
It is important to ensure that armored vehicle plays in Tactical Applications fields such as amphibious landing, ground assault, motor-driven, the city anti-terrorisms in mountainous region for emitter
Strength.But there are two defects for traditional external automatic weapon steer mode：First, observation, aiming and shooting use original hand
Dynamic operation, Weapon Combat efficiency are relatively low；Second is that manipulator must lean out upper body operates weapon outside vehicle, there is no armor facing shape
The safety of personnel cannot be guaranteed under condition.If manipulator, which interior can be remotely controlled, completes external automatic weapon operation, target is realized
Observation, the automation for aiming at and shooting, then while precision strike enemy, also ensure the safety of personnel.Overhead weapon
It stands and comes into being under this operational need, changed to adapt to modern war, each military power of the world all is putting forth effort to grind
Overhead weapon station processed.
As a kind of novel on-vehicle weapon system, overhead weapon station at home and abroad causes extensive attention, is increasingly becoming
One research hotspot of weapon field, military power one after another expand it correlative study, and Countries, which have been already equipped with, to be suitble to
The overhead weapon station that Home Force uses.Although there has been no molding overhead weapon station, relevant department is organizing respectively for the country
Fang Liliang steps up to develop, and qualification test will be carried out during " 12th Five-Year Plan ", in the near future by trial assembly army.
Overhead weapon station is to can configure the fire control system of a variety of weapons and various combination, possess target search, identification,
The remotely controlling functionals such as tracking, aiming and marching fire can be mounted on module relatively independent on a variety of military vehicle platforms
Change weapon system.The weapon that overhead weapon station is equipped with includes various small medium caliber machine guns, automatic grenade launcher, 30~40mm machines
Close big gun and guided missile etc..The application prospect of overhead weapon station is boundless.It except can on ground attack platform in addition to use,
Also there is application demand on the platforms such as carrier, naval vessels, armed helicopter.
System performance (System Performance) generally refers to property possessed by system and function.It is filled for weapon
For standby, system performance is primarily referred to as operational exertion performance, it is weaponry performance characterisitic and Synthetic technological guarantee
The function of energy.Performance characterisitic is made of tactical qualities and technical performance, is the main ginseng for describing weapon system fight capability
Number.Synthetic technological guarantee performance is made of a series of Supportability parameters, mainly includes Supportability design parameter, Support Resource parameter
With protection comprehensive parameters, with use reliability, maintainability and availability isometry.
Overhead weapon station is complicated, integrated level is high, being related to technical field, wide and Performance Evaluation is difficult, based on above reality,
Overhead weapon station makes examination in technical indicator demonstration, scheme evaluation, performance prediction, qualification test, prison and input army used
Cheng Zhong be unable to do without and science, real-time, system, objective assay is carried out to its performance.At present, the country is to overhead weapon station
Evaluating Models research seldom, it is necessary to when its performance is analyzed and evaluated, substantially with the national army of traditional conventional Weapon
It is foundation with standard, lacks the performance evaluation software systems of complete, ripe Evaluating Models and high integration, this is very
The prison that overhead weapon station from now on is influenced in big degree is made and is used, and limits the development and development of overhead weapon station.
The content of the invention
For overcome the deficiencies in the prior art, the purpose of the present invention is to propose to a kind of overhead weapon station with a high credibility
Energy evaluation method with the evaluation method of science, carries out all types of overhead weapon station objective, quantization, quick, effective property
It can analyze and assess.
Technical solution provided by the invention is：
A kind of overhead weapon station performance estimating method, comprises the following steps：
Step 1 carries out overhead weapon station data acquisition and obtains multiple performances for being used to weigh the overhead weapon station performance
Index, and one is built by overall layer performance indicator U, system layer according to the performance indicator of the multiple overhead weapon station of acquisition
Performance indicator Ui, state layer performance indicator UijWith variable layer performance indicator UijkThe overhead weapon station Performance Evaluating Indexes body of composition
System, wherein i represent there be i system layer performance indicator U below overall layer performance indicator Ui, j expression system layer performance indicators UiBelow
There is j state layer performance indicator Uij, k expression state layer performance indicators UijThere is k variable layer performance indicator U belowijk, pass through ash
Color calculation of relationship degree method determines the performance indicator weight sets A of this four levels；
Step 2 calculates variable layer performance indicator UijkComprehensive evaluation value Mijk, computational methods are：Mijk=BijkC,
Wherein, BijkFor the fuzzy overall evaluation collection obtained by Field Using Fuzzy Comprehensive Assessment, C is scoring vector；
Step 3 calculates state layer performance indicator UijComprehensive evaluation value Mij, computational methods are：Mij=(Aij1,Aij2,
L,Aijk)(Mij1,Mij2,L,Mijk)T, AijkRepresent variable layer performance indicator UijkWeighted value；
Step 4, computing system layer performance indicator UiComprehensive evaluation value be Mi, computational methods are：Mi=(Ai1,Ai2,
L,Aij)(Mi1,Mi2,L,Mij)T；AijRepresent state layer performance indicator UijWeighted value；
Step 5, the comprehensive evaluation value M for calculating overall layer performance indicator U obtain the final evaluation of the overhead weapon station
As a result, its computational methods is：M=(A1,A2,...Ai)(M1,M2,...Mi)T, AiRepresent system layer performance indicator UiWeighted value.
Preferably, the overhead weapon station performance estimating method, the fuzzy overall evaluation collection B described in step 2ijk
=Rijk, Rijk=(rijk1,rijk2,rijk3,...,rijkq) represent the variable layer performance indicator UijkMembership vector, then
Mijk=BijkC=(rijk1,rijk2,rijk3,...,rijkq)(S1,S2,S3,...,Sq)T, wherein q represent opinion rating in have q
Kind opinion rating, SqRepresent the tax score value of q grades in scoring vector C.
Preferably, the overhead weapon station performance estimating method, in step 2, the overhead weapon station performance indicator
Opinion rating in have 5 kinds of opinion ratings i.e. q values for 5, and use hundred-mark system quantitative assessment, i.e. evaluate collection V is expressed as V=
(V1,V2,V3,V4,V5)=(1,2,3,4,5), the vectorial value that scores is C=(30,65,75,85,95), then the variable layer
It can index UijkComprehensive evaluation value be：
Mijk=BijkC=(rijk1,rijk2,rijk3,rijk4,rijk5)(30,65,75,85,95)T。
Preferably, the overhead weapon station performance estimating method, the totality layer performance indicator U is by overall performance
Index U1, subsystem performance indicator U2With the performance indicator U based on overhead weapon station sample3This 3 system layer performance indicator compositions
I.e. the value of i is 3, then the comprehensive evaluation value of overall layer performance indicator U is expressed as M=(A1,A2,A3)(M1,M2,M3)T。
Preferably, the overhead weapon station performance estimating method, passes through grey relational grade meter described in step 1
Calculation method determines concretely comprising the following steps for the performance indicator weight sets A of four levels：
Step 1 is rule of thumb previously obtained state layer performance indicator UijEvaluation result matrix (Whi)e×k, for each
A performance indicator obtains multiple weighted values, and e represents the number of the weighted value of each performance indicator, and k represents that variable layer performance refers to
Target quantity, WhiRepresent h-th of the weighted value drawn to the assessment of i-th performance indicator, i is equal to 1,2 ... k；
Step 2 passes through irrelevance calculation formulaDraw similar matrix
(Rhg)e×e, RhgFor h-th of the weighted value and the similarity of g-th of weighted value assessed i-th of performance indicator, by deviateing
Spend calculation formula Ph=Σ Rhg, obtain：
P=(p1,p2,...,pe)T, by irrelevance coefficientObtain D=(D1,D2,...,
De), then set irrelevance limitation D0, weighted value irrelevance coefficient in result of calculation is more than D0Remove, by remaining weight
Value determines weight；
Step 3, calculates grey relational grade coefficient, and calculation formula is：
Wherein, t is abscissa, represents the number of the weighted value after each screening, x0(t) to be female because of series of prime numbers x0(t)=
(x0(1),x0(2),L,x0(n)) element in, xi(t) it is comparison sequence xi(t)=(xi(1),xi(2),L,xi(n)) member in
Element, μ are resolution ratio, in (0,1) value,For two-stage maximum difference,
For two-stage lowest difference；
Step 4, calculates the grey relational grade of every curve, and calculation formula is：(i=1,2, L,
N), state layer performance indicator U is obtained after grey relational grade is normalizedijWeight matrix Aijk=(Aij1,Aij2,...,Aijk)；
Step 5 establishes weight sets A.
Overhead weapon station performance estimating method of the present invention, compared with prior art, first, being commented using fuzzy synthesis
Valency method constructs evaluations matrix, determines performance index weights collection using the method that grey relational grade calculates, establishes overhead weapon
Stand grey fuzzy Evaluating Models, with the evaluation method of science, overhead weapon station performance can be carried out it is objective, quantify,
Fast, effective performance evaluation and assessment.And this method is easy, practical, workable.Second is that the overhead weapon station performance
Evaluation method can objectively evaluate the good and bad degree of overhead weapon station, and the deficiency of system is found in evaluation procedure, for top
The performance evaluation offer theory support that weapon station makes the stage in demonstration, development and production prison is provided.
Description of the drawings
Fig. 1 is overhead weapon station Evaluating Models of the present invention；
Fig. 2 is the work flow diagram of overhead weapon station performance estimating method of the present invention.
Fig. 3 is the level and block diagram of prefabricated weapon station Performance Measuring Indicators.
Specific embodiment
The present invention is described in further detail below in conjunction with the accompanying drawings, to make those skilled in the art with reference to specification text
Word can be implemented according to this.
For different types of overhead weapon station, by testing the obtained performance indicator for being used for weighing its performance
Number is different, as a specific embodiment in the present invention, for the overhead weapon station of one of which type, is obtained
87 performance indicators, and index based on this 87 performance indicators is built one by overall layer performance indicator, system layer
The overhead weapon station Performance Measuring Indicators of performance indicator, state layer performance indicator and variable layer performance indicator composition, variable
Layer performance indicator represents 87 base values, such as weapon type, bullet kind, allowance of ammunition, fight firing rate, firing density, ammunition feed
Mode, effective range etc.；State layer performance indicator represents that two-level index, such as tank fire system performance indicator, sight take aim at system performance
Index, fire control system performance indicator etc.；System layer performance indicator represents first class index, such as indicators of overall performance, subsystem
Energy index, the index obtained based on simulation model.
For data character, performance indicator can be divided into two kinds of quantitative target and qualitative index.The letter of quantitative target
Breath has specific numerical value, such as firing area, hit probability, firewire height, Smoke Grenade Discharger quantity, fight firing rate, firing density
Index is known as quantitative target；The connotation and extension of qualitative index is not that very clearly, concept has ambiguity, it is difficult to directly carry out
Quantitative description, information are cannot to provide exact numerical value, can only qualitatively be judged by Linguistic Values such as " excellent, good, poor ".
Qualitative index value is mainly the method acquisition given qualitative evaluation by experience and markedly quantified afterwards, and quantitative target value can pass through examination
The methods of testing statistics, field survey, report analysis obtains.
The evaluating data of train diagram adjusting can not only be tested from overhead weapon station and obtained, can also be from overhead weapon station
Test sample obtains, and overhead weapon station sample is classified as data source and is had the advantage that：First, overhead weapon station test tested person is made
The reasons such as valency is big, be inconvenient to be embodied, condition limitation, it is impossible to by the whole tests of the dynamic characteristic achievement data of overhead weapon station
Out.The shortcomings that testing overhead weapon station is then compensated for the test of overhead weapon station sample, from the limitation of test condition,
More comprehensive dynamic characteristic can be obtained.2nd, since objective factor influences, the data volume of overhead weapon station test cannot be reached
Evaluation requirement.The data volume obtained to the test of overhead weapon station sample is big, improves the credibility of evaluation.The portion of index system
Divide achievement data that can only be obtained by testing overhead weapon station, part index number data can only be surveyed by overhead weapon station sample
Examination obtains, and also some index (such as firing density) data can be tested respectively by two ways and obtained.With overhead weapon
Sample of standing is primarily present in for the performance indicator of data source in firepower subsystem and fire control subsystem performance indicator.
Fig. 1 is two evaluation models constructed in overhead weapon station performance estimating method provided by the present invention, and Fig. 2 is hair
The work flow diagram of bright provided overhead weapon station performance estimating method, the appraisal procedure of the present embodiment comprise the following steps：
S1 determines the performance indicator weight sets A of four levels by grey relational grade computational methods；
The weight sets of performance indicator is determined by grey relational grade computational methods, is first had to overhead weapon station performance evaluation
Index system is analyzed, and establishes grey relational grade analysis model, since there are many performance indicator, specifically with state layer performance
The tank fire system performance U of index21And its research of single-stage performance evaluation is carried out exemplified by the variable layer performance indicator of subordinate, then with this
Based on establish overhead weapon station multistage Evaluating Models, as shown in figure 3, tank fire system performance U21The index of subordinate has weapon
Type U211, bullet kind U212, bullet kind radix U213, fight firing rate U214, firing density U215, ammunition feed mode U216And effective range
U217, tank fire system subordinate's index is as shown in Figure 2.Wherein, weapon type U211, bullet kind U212, ammunition feed mode U216For qualitative index,
Bullet kind radix U213, fight firing rate U214, firing density U215, effective range U217For quantitative target, Dan Yin is carried out as example
Plain performance evaluation is representative.
Gray system theory is a kind of using poor information, small sample, uncertain system as research object, by " part "
The definite research method described and recognize to things and action rule is realized in generation, the exploitation of Given information.In grey colour system
In system, the information that is fully apparent from is represented with " white ", and completely ignorant information is represented with " black ", and part is clear and definite, part is indefinite
Information with " ash " expression.In different occasions, the amplification of " ash " concept is also different, as shown in table 1：
The amplification of the different occasion ash concepts of table 1
Correlation analysis method is most widely used method in gray theory.Grey relational grade analysis make use of several where
The mode of thinking of reason, basic thought are the tightness degrees that contact is described according to the similarity degree of sequence curve geometry,
Geometrical curve similarity degree is higher, and the degree of association between corresponding sequence is bigger.Estimate as what relevance between index was measured, refer to
The target degree of association is bigger, represents that the relation of the index and overall performance level is bigger, influence power is bigger.Therefore, the degree of association and power
It is identical for focusing on basic meaning.The maximum feature of grey relational grade is that do not have strict requirements to data volume, no matter performance
The data volume of evaluation is big or small can all be analyzed.In the quantized result for the degree of association do not occur and the inconsistent situation of qualitative analysis
Under, when evaluation condition is unsatisfactory for statistical requirements or data information is less, for the weight of overhead weapon station Performance Evaluating Indexes
It calculates more with practical value.
Weight (weight coefficient of index) is the mathematical quantity for portraying relative importance between evaluation index.To target
During being evaluated, it is first determined object and evaluation index are evaluated, it is then determined that weight coefficient.Weight coefficient it is reasonable
Whether, it is related to the height of the credibility of comprehensive evaluation result.
Weight is rule of thumb to carry out assignment mostly, and the weight sets of things is not only definite, these are uncertain
Property can impact the accuracy of evaluation result.To solve this problem, with the method for calculating irrelevance to investigation result
It is screened, by calculating each investigation result to the departure degree of Positive ideal point, rejects the big investigation result of departure degree, reduce
The randomness that estimator's subjective factor is brought and uncertainty, make result more approaching to reality result.Its detailed process is：
S101, for tank fire system performance U217 variable layer performance indicators of subordinate, each performance indicator obtain 10
Weighted value, the evaluation result matrix (W that weighted value is formedhi)10×7For：
Wherein, WhiIt is h-th of the weighted value drawn to i-th of performance indicator assessment.
S102, irrelevance calculate
The calculation formula of irrelevance is
Similar matrix (R is drawn by similarity factorhg)e×e。
In formula：K be variable layer performance indicator quantity, the number of the weighted value for each performance indicator that e is, RhgFor
H-th of the weighted value assess i-th of performance indicator and
The similarity of g weighted value.
By similar matrix (R is calculatedhg)10×10For：
By irrelevance Ph=Σ Rhg, obtain：
P=(p1,p2,L,p10)T=(9.686,8.589,9.632,9.656,9.643,9.652,9.647,9.541,
9.656,9.642,)T
By irrelevance coefficient：
D=(D1,D2,L,D10)=(0,0.95%, 0.59%, 0.79%, 0.87%, 0.51%, 0.41%, 1.09%,
0.46%, 0.59%)
Set irrelevance limitation D0=0.9%, the 2nd weight assessed value and the 8th weight evaluation result in result of calculation
Irrelevance coefficient is more than D0, investigation result cancels, and weight is determined by remaining 8 weighted values.
S103, the calculating of grey relational grade
Grey relational grade calculating is in order to calculate weight, herein still with tank fire system performance U21The index of subordinate is used as and grinds
Study carefully object, screening visit sample and reject interference result after, to investigation sample carry out grey relational grade calculating.Grey relational grade
The general step of analysis：
(1) determine mother because of series of prime numbers.
Equipped with N number of ordered series of numbers, each data row acquisition m data
x1(t)=(x1(1),x1(2),L,x1(m))
x2(t)=(x2(1),x2(2),L,x2(m))
L L L
xn(t)=(xn(1),xn(2),L,xn(m))
After original data packet, dimensionless processing should be carried out to it, since the target of grey relational grade analysis is first
Weight, identical dimension is 1, therefore dimensionless processing procedure is omitted.
Incidence coefficient is asked to first have to formulate the data row of reference, which is known as mother because of series of prime numbers, is denoted as x0.According to firepower
System performance U21The investigation result of the index weights of subordinate obtains female factor data and is classified as：
x0=(x0(1),x0(2),L,x0(8))=(0.30,0.30,0.30,0.30,0.20,0.25,0.35,0.30)
(2) each factor of evaluation is calculated with female because the sequence of series of prime numbers is poor.
Provide it is female because after series of prime numbers can calculate correlation coefficient, judge tank fire system performance U from expert's result21In other
Performance Evaluating Indexes U21iCompared with the importance x of female factori.Each Performance Evaluating Indexes data and the sequence of female factor data row
Difference is：
Δi(t)=| x0(t)-xi(t) | (i=1,2, L, 7；T=1,2, L, 8)
Wherein maximum difference isMinimal difference is
According to investigation result, tank fire system performance U is calculated21Subordinate's Performance Evaluating Indexes U21iThe sequence of weight and female factor
It is poor as shown in table 3.
Other indexs of table 3 and x0Sequence it is poor
(3) calculation formula of grey incidence coefficient is：
In formula：T is abscissa, represents the number of the expert after each screening,
x0(t) to be female because of series of prime numbers x0(t)=(x0(1),x0(2),L,x0(n)) element in,
xi(t) it is comparison sequence xi(t)=(xi(1),xi(2),L,xi(n)) element in,
μ is resolution ratio, in (0,1) value, generally 0.5.
For two-stage maximum difference
For two-stage lowest difference
(4) grey relational grade of every curve is calculated：
The degree of association being calculated according to size is arranged and has just obtained inteerelated order.The bigger influence of inteerelated order of index
Degree is bigger.Calculate tank fire system performance U21Subordinate's Performance Evaluating Indexes U21iThe grey incidence coefficient of weight and female factor, grey
The degree of association, the results are shown in Table 4.
4 other influences factor of table and x0Grey incidence coefficient and grey relational grade
Tank fire system performance U is obtained after the degree of association is normalized21Weight matrix A21：
Overall performance U, which may be employed, obtains overhead weapon station and overhead weapon station sample two ways data progress performance
Evaluation, mainly passes through overall performance evaluation weight matrix A=(A1,A2,A3)=(x, y, z) difference of value realizes.Evaluate mould
Type, which is divided into, only to be evaluated by overhead weapon station, is only evaluated by overhead weapon station sample and by overhead weapon station
It is evaluated jointly with overhead weapon station sample.According to three kinds of evaluation model situations, pass through experience and grey relational grade analysis phase
With reference to method obtain overall performance evaluation weight matrix, as shown in table 5.
5 overall performance evaluation weight matrix of table
Summarize to obtain overhead weapon station Performance Evaluating Indexes weight sets by calculating as shown in table 6：
The definite each performance indicator weight of table 6
S2 calculates variable layer performance indicator UijkComprehensive evaluation value Mijk, computational methods are：Mijk=BijkC=
(rijk1,rijk2,rijk3,...,rijkq)(S1,S2,S3,...,Sq)T, BijkIt is fuzzy comprehensive to be obtained by Field Using Fuzzy Comprehensive Assessment
Evaluate collection is closed, C is scoring vector, and q indicates q kind opinion ratings, SqRepresent the tax score value of q grades in scoring vector；Pass through
Field Using Fuzzy Comprehensive Assessment obtains fuzzy overall evaluation collection, and concrete implementation process is：
Field Using Fuzzy Comprehensive Assessment is based on fuzzy mathematics, with maximum membership grade principle and blurring mapping principle, is incited somebody to action
Obscure boundary is not easy quantitative factor quantification, and overall merit is carried out to being evaluated target membership from multiple influence factors
Method.The step of fuzzy synthetic appraisement method is：An evaluations matrix R is constructed first (from set of factors U to the mould of evaluate collection V
Paste mapping), then the weight sets A for reflecting the relative importance of each factor is determined to, it is calculated by fuzzy composition, by evaluations matrix
R and weight sets A synthesizes Evaluation by Multi-factor with Fuzzy Weight collection B.
S201 builds set of factors and evaluate collection
(1) set of factors is divided
Set of factors U=(u1,u2,u3,L,um) be to influence to be evaluated the index set of object, for reflect judge from which
Target is evaluated in terms of a little.The overhead weapon station index system of structure is multi-level set of factors.
(2) evaluate collection is established
Evaluate collection is the set that each influence factor forms the opinion rating that may be made by judge object：
V=(V1,V2,V3,L,Vq)
Q indicates q kind opinion ratings in formula, and general evaluation number of degrees is 3-7, if opinion rating number crosses conference to fuzzy
Comprehensive Evaluation brings difficulty, if evaluated, number is too small to reduce evaluation accuracy.Fuzzy overall evaluation matrix R is really set of factors
Mappings of the U to evaluate collection V, final appraisal results are reflected from evaluate collection.If evaluation number is too small to reduce evaluation accurately
Degree, if opinion rating number, which crosses conference, brings fuzzy comprehensive evoluation difficulty, general number of degrees is 3-7.For reflection property directly perceived
The number of degrees of overhead weapon station performance evaluation collection V is determined as five, and uses hundred-mark system quantitative assessment by the quality of energy, i.e.,：
V=(V1,V2,V3,V4,V5)=(1,2,3,4,5)
Therein 1,2,3,4,5 evaluate for grade, and five opinion ratings correspond to continuous, incremental numerical score respectively, this
Sample by quantification of targets, can not only also improve the accuracy of evaluation.Each corresponding comment of opinion rating and corresponding tax score value are such as
Shown in 7 opinion scale table of table：
7 opinion scale table of table
The foundation of S202 Subject Matrix
Subject Matrix R=(rij)m×nIt is each factor uiTo the degree of membership r of evaluate collection VijSet.Degree of membership is used for table
Show some element in set to the subjection degree of fuzzy set, degree of membership can take closed interval (0,1) it is arbitrary, ∞ be worth
Number, use rijRepresent element uiTo the subjection degree of evaluate collection V, and meet 0≤rij≤1。rijThe bigger expression u of valueiTo evaluation
It is bigger to collect the subjection degree of V, it is smaller to be worth smaller expression subjection degree.Work as rijValue when taking 0 and 1, represent u respectivelyiAffirmative does not belong to
Belong in evaluate collection V and certainly evaluate collection V.After definite set of factors and evaluate collection, you can determine single factor test u in set of factorsi
(i=1,2, L, m) is to the choice grade v of a upper subsetjThe degree of membership r of (j=1,2, L, n)ij, can obtain single factor test uiEvaluation
Collect ri=(ri1,ri2,L,rin), by can be obtained by Subject Matrix R to the integration of all factors of evaluation：
The definite of fuzzy overall evaluation degree of membership refers to the process of scalarization, makes to be comparable between each achievement data.
Obtain the premise that accurate degree of membership is overhead weapon station benchmark problem, the definite method of degree of membership be it is diversified,
It needs to be made choice according to the property of index.Classify according to index property, the evaluation index of weapon station is divided into quantitative target and determines
Two kinds of index of property, the incommensurability and paradox that they show bring appraisal difficulty, for the spy of two kinds of indexs
Property, two class difference degrees of membership is taken to determine method respectively.
(1) the definite method of quantitative target degree of membership
The degree of membership of quantitative target can be acquired with membership function, and membership function can quantitatively reflect first in fuzzy concept
Element is subordinated to the degree of fuzzy set.Since number of people brain thinking has differences, everyone is usually difference to the understanding of same thing
, therefore the membership function in everyone brains is also different, the definite of membership function is inevitably subject to subjectivity in varying degrees
The influence of factor, but since subjectiveness and objectiveness has inevitable relevance, there are definite membership functions to reflect objective reality.
1) degree of membership fuzzy subset's table is constructed
The degree of membership of quantitative target variable can both be represented with the mode of continuous function, input quantity can also be considered as language
Variable, so original continuous membership function can just occur with the hierarchical manner of discretization.With reference to classical membership function and
The experience of expert investigation constructs scoring degree of membership fuzzy subset's table of index, as shown in table 8.Fuzzy subset's table is determining to be subordinate to
It is essentially identical with membership function but more more convenient than membership function in terms of the effect of category degree.
8 degree of membership fuzzy subset's table of table
2) interval division
The present invention carries out interval division using point 5 sections of section obtaining value methods to quantitative assessing index data.It is passed through according to expert
Test and establish the corresponding piecewise function of each quantitative target and segmentation criteria so that the scoring model established can adapt to it is any
When, anyone needs.Piecewise function is shown below：
In formula：DLZBijRepresent the definite value of j-th of quantitative target of the i-th class；
yj1、yj2、yj3、yj4、yj5Represent the 1st, 2,3,4, the numerical value in 5 constant intervals；
xijRepresent the data value of the acquired original of j-th of index of the i-th class；
M1、M2、M3、M4、M5Represent the 1st, 2,3,4, the critical value of 5 sections variation.
Quantitative performance indicator mainly has cost type, profit evaluation model and fixed three classes.Cost type index (such as react by fire control system
Time, power consumption, control panel weight, exposed height etc.) numerical value is the smaller the better, and profit evaluation model index (penetrate by such as effective range, fight
Speed, white light CCD sighting distances etc.) numerical value is the bigger the better, and fixed index value is better closer to some fixed value.According to each quantitative finger
Target piecewise function draws corresponding segmentation criteria, such as table 9 and table 10.
9 fire control system reaction time of table segmentation criteria (/s)
(2) the definite method of qualitative index
Qualitative index can not be expressed directly using this quantitative tool of mathematics, therefore will be to qualitative index before evaluation
Quantified, then also to carry out standardization processing.According to the characteristics of overhead weapon station qualitative index, the present invention is using fuzzy system
Meter method describes the degree of membership of qualitative index.
It is empirically derived the judgement frequency vector r of i-th of indexi=(ri1,ri2,ri3,ri4,ri5), then it is carried out
Standardization processing, i.e., to ri=(ri1,ri2,ri3,ri4,ri5) calculating is normalized, make its satisfaction：
Calculating process is as follows：
ri 0=(ri1 0,ri2 0,ri3 0,ri4 0,ri5 0) be i-th of qualitative index of overhead weapon station membership vector.
(3) open subordinated-degree matrix
Since objective condition limits, during overhead weapon station performance evaluation, whether carried out by overhead weapon station
Performance evaluation still carries out performance evaluation by overhead weapon station sample, is all likely to occur the phenomenon that input data is not complete, presses
It is not easy to obtain evaluation result according to traditional evaluation method.
In order to solve this problem, the present invention devises open subordinated-degree matrix.Regulation is independent in overhead weapon station
During performance evaluation, the index for lacking data is handled according to 3 grades of linguistic variables, that is, provide its degree of membership for (0,0.15,
0.65,0.17,0.03)；When two weapon station performances compare, as long as the data of wherein side's weapon station index lack, in addition
The correspondence index of one side's weapon station is handled also according to shortage of data.The design of open subordinated-degree matrix so that overhead is military
Device station can still be commented in the case where partial data (overhead weapon station data and overhead weapon station sample data) lacks
Valency has stronger objectivity, opening and operability.
S203, fuzzy composition computing
Subject Matrix R=(r described aboveij)m×n, (i=1,2, L, m；J=1,2, L, n) different row, from different lists
Factor angle reflects the subjection degree for being evaluated each evaluate collection of object.R differences row is carried out to respectively commenting by factor by weight sets A
The synthesis of the subjection degree of valency collection, obtains subjection degree of each influence factor from whole angle to evaluate collection, i.e. fuzzy synthesis is commented
Valency result vector B=(b1,b2,L,bn)。
Computing is carried out using weighted mean method, B=AR is calculated according to ordinary channel multiplication, then obtains fuzzy overall evaluation
Matrix：
In formula：biReflect significance level of i-th of evaluation result in totality V is judged.
In the computing of fuzzy overall evaluation, the Mathematical Model of Comprehensive Evaluation of selection is different, and corresponding computing model is not yet
It is identical to the greatest extent.According to different requirements, different fuzzy models is chosen, determines different Fuzzy Arithmetic Operators.It is common fuzzy comprehensive
It closes there are three types of evaluation processing methods：Maximum membership degree method, weighted mean method and fuzzy distribution.Wherein, Weighted Average Algorithm is comprehensive
The effect for considering all influence factors is closed, ensure that evaluation result B includes the comprehensive of each side information.It is military in view of overhead
In the Performance Evaluation System of device station index quantity mostly with Index Influence gradient it is small the characteristics of, it is necessary to by the influence factor in appraisement system
It is all included in calculating, therefore using weighted mean method processing evaluation result more science.With weighted mean method, with fuzzy
Overall merit collection B=(b1,b2,L,bn) as scoring vector in element weight, with scoring multiplication of vectors obtain the knot of computing
Fruit.Scoring vector C=(30,65,75,85,95) is formed with the intermediate value that 5 groups of opinion scales assign score value in table 7, then it is flat by weighting
The comprehensive evaluation value M=BC obtained after equal method processing evaluation result draws the quantitative evaluation result of single-stage index.
Three levels are divided into overhead weapon station Multistage fuzzy comprehensive：Wherein UiFor first class index (system layer), Uij
For two-level index (state layer), UijkFor three-level index (variable layer).Claim UiFor UijUpper level index, UijFor UijkUpper level
Index, UijFor Ui、UijkFor UijNext stage index.
Evaluate collection V=(V are set1,V2,V3,V4,V5), then primary evaluation is variable layer performance indicator UijkTo one of V
It is fuzzy to hint obliquely at：
f:U→V
It is fuzzy to hint obliquely at f and use bottom index UijkTo Comment gathers each element Vm(m=1,2,3,4,5) membership vector in
Rijk=(rijk1,rijk2,rijk3,rijk4,rijk5) represent, since primary evaluation is the result is that represented in the form of evaluation of estimate, because
This needs to substitute into scoring vector, and fuzzy overall evaluation collection Bijk=Rijk。
Vector C=(30,62,75,85,95) score with the membership vector R of each bottom indexijk(the i.e. evaluation of single index
Collect Bijk) it is weight, ask for each bottom index UijkComprehensive evaluation value Mijk, then:
Mijk=BijkC=(rijk1,rijk2,rijk3,rijk4,rijk5)(30,65,75,85,95)T
S3, state layer performance indicator U is calculatedijComprehensive evaluation value Mij, i.e., to two-level index Uij(state layer performance indicator)
The performance evaluation of progress, two-level index UijThere is a k branches index U belowijk.The fuzzy weight vector obtained by table 3- tables 5 is, by three-level evaluation operation result MijkForming evaluation vector is
, then two-level index UijComprehensive evaluation value MijFor：
In formula：I=1,2,3；J=1,2 ..., n1；n1∈(2,5,7)；K=1,2 ..., n2；n2∈(2,3,4,6,7,11,
13,19)
S4, computing system layer performance indicator UiComprehensive evaluation value be Mi, i.e., to first class index Ui(i=1,2,3) (system
Layer performance indicator) performance evaluation that carries out, the fuzzy weight vector obtained by table 3- tables 5 isAccording to
Two-level appraisement computing acquires two-level index UiComprehensive evaluation value MijForming evaluation vector is
Then first class index UiOverall merit score value MiFor：
In formula：I=1,2,3；J=1,2 ..., n1；n1∈(2,5,7)
S5 calculates the comprehensive evaluation value M of overall layer performance indicator U, i.e., final evaluation, 3 branches of indicators of overall performance U
The weight vectors of index are A=(A1,A2,A3)=(x, y, z), computing is evaluated according to level-one, acquires 3 first class index UiIt is comprehensive
Close evaluation of estimate MiThe evaluation vector formed is M=(M1,M2,M3), then overhead weapon station performance synthesis evaluation of estimate M is：
M=(A1,A2,A3)(M1,M2,M3)T
The evaluation of overhead weapon station performance synthesis should be divided into level Four, and evaluation model is as follows：
Although the embodiments of the present invention have been disclosed as above, but its be not restricted in specification and embodiment it is listed
With it can be fully applied to various fields suitable for the present invention, for those skilled in the art, can be easily
Realize other modification, therefore without departing from the general concept defined in the claims and the equivalent scope, it is of the invention and unlimited
In specific details and shown here as the legend with description.
Claims (1)
1. a kind of overhead weapon station performance estimating method, which is characterized in that comprise the following steps：
Step 1 obtains multiple performances for being used to weigh the overhead weapon station performance to the progress data acquisition of overhead weapon station and refers to
Mark, and build one according to the performance indicator of multiple overhead weapon station of acquisition and referred to by overall layer performance indicator U, system layer performance
Mark Ui, state layer performance indicator UijWith variable layer performance indicator UijkThe overhead weapon station Performance Measuring Indicators of composition, wherein
I represents there be i system layer performance indicator U below overall layer performance indicator Ui, j expression system layer performance indicators UiThere is j shape below
State layer performance indicator Uij, k expression state layer performance indicators UijThere is k variable layer performance indicator U belowijk, pass through grey correlation
Degree computational methods determine the performance indicator weight sets A of this four levels；
Step 2 calculates variable layer performance indicator UijkComprehensive evaluation value Mijk, computational methods are：Mijk=BijkC,
In, BijkFor the fuzzy overall evaluation collection obtained by Field Using Fuzzy Comprehensive Assessment, C is scoring vector；
Step 3 calculates state layer performance indicator UijComprehensive evaluation value Mij, computational methods are：Mij=(Aij1,Aij2,L,
Aijk)(Mij1,Mij2,L,Mijk)T, AijkRepresent variable layer performance indicator UijkWeighted value；
Step 4, computing system layer performance indicator UiComprehensive evaluation value be Mi, computational methods are：Mi=(Ai1,Ai2,L,Aij)
(Mi1,Mi2,L,Mij)T；AijRepresent state layer performance indicator UijWeighted value；
Step 5, the comprehensive evaluation value M for calculating overall layer performance indicator U are to obtain the final evaluation knot of the overhead weapon station
Fruit, computational methods are：M=(A1,A2,...Ai)(M1,M2,...Mi)T, AiRepresent system layer performance indicator UiWeighted value；
The totality layer performance indicator U is by indicators of overall performance U1, subsystem performance indicator U2With based on overhead weapon station sample
Performance indicator U3This 3 system layer performance indicator compositions are that the value of i is 3, then the comprehensive evaluation value of overall layer performance indicator U
It is expressed as M=(A1,A2,A3)(M1,M2,M3)T；
Wherein, the fuzzy overall evaluation collection B described in step 2ijk=Rijk, Rijk=(rijk1,rijk2,rijk3,...,rijkq) table
Show the variable layer performance indicator UijkMembership vector, then Mijk=BijkC=(rijk1,rijk2,rijk3,...,rijkq)
(S1,S2,S3,...,Sq)T, wherein q represent opinion rating in have q kind opinion ratings, SqRepresent q grades in scoring vector C
Assign score value；
In step 2, it is 5 to have 5 kinds of opinion ratings i.e. q values in the opinion rating of the overhead weapon station performance indicator, and is used
Hundred-mark system quantitative assessment, i.e. evaluate collection V are expressed as V=(V1,V2,V3,V4,V5)=(1,2,3,4,5), the vectorial value that scores is C
=(30,65,75,85,95), then the variable layer performance indicator UijkComprehensive evaluation value be：
Mijk=BijkC=(rijk1,rijk2,rijk3,rijk4,rijk5)(30,65,75,85,95)T；
The specific step of the performance indicator weight sets A that four levels are determined by grey relational grade computational methods described in step 1
Suddenly it is：
Step 1.1, rule of thumb it is previously obtained state layer performance indicator UijEvaluation result matrix (Whi)e×k, for each
Performance indicator obtains multiple weighted values, and e represents the number of the weighted value of each performance indicator, and k represents variable layer performance indicator
Quantity, WhiRepresent h-th of the weighted value drawn to the assessment of i-th performance indicator, i is equal to 1,2 ... k；
Step 1.2, irrelevance calculation formula is passed throughDraw similar matrix (Rhg)e×e, Rhg
For h-th of the weighted value and the similarity of g-th of weighted value assessed i-th of performance indicator, by irrelevance calculation formula
Ph=∑ Rhg, obtain：P=(p1,p2,...,pe)T, by irrelevance coefficientObtain D=(D1,
D2,...,De), then set irrelevance limitation D0, weighted value irrelevance coefficient in result of calculation is more than D0Remove, by remaining
Under weighted value determine weight；
Step 1.3, grey relational grade coefficient is calculated, calculation formula is：
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Wherein, t is abscissa, represents the number of the weighted value after each screening, x0(t) to be female because of series of prime numbers x0(t)=(x0
(1),x0(2),L,x0(n)) element in, xi(t) it is comparison sequence xi(t)=(xi(1),xi(2),L,xi(n)) element in,
μ is resolution ratio, in (0,1) value,For two-stage maximum difference,For two
Grade lowest difference；
Step 1.4, the grey relational grade of every curve is calculated, calculation formula is：
State layer performance indicator U is obtained after grey relational grade is normalizedijWeight matrix Aijk=(Aij1,Aij2,...,Aijk)；
Step 1.5, weight sets A is established.
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| CN106125549B (en) * | 2016-06-27 | 2018-12-28 | 中国人民解放军装甲兵工程学院 | Burst-firing gun muzzle vibrates substep suppressing method between a kind of overhead weapon station is advanced |
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| CN107300907B (en) * | 2017-06-14 | 2019-03-19 | 中国人民解放军91550部队 | In conjunction with the flight control system Reliable Evaluating Methods of Their Performance of comprehensive assessment and hypothesis testing |
| CN107944216B (en) * | 2017-11-29 | 2021-06-18 | 南京理工大学 | Method for determining destruction probability of weapon system configured in hierarchical manner |
| CN108256761A (en) * | 2018-01-15 | 2018-07-06 | 中国人民解放军陆军装甲兵学院 | Overhead weapon station grey fuzzy comprehensive evaluation method |
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