CN108629511A - A kind of satellite synthetic effectiveness evaluation method based on multifactor fuzzy theory reasoning and Analytic hierarchy process - Google Patents
A kind of satellite synthetic effectiveness evaluation method based on multifactor fuzzy theory reasoning and Analytic hierarchy process Download PDFInfo
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Abstract
The satellite synthetic effectiveness evaluation method based on multifactor fuzzy theory reasoning and Analytic hierarchy process that this application involves a kind of, including level divide；Obtain evaluation index system set；Level is divided with respectively different weighted values；Possible evaluation result is chosen for a certain specific indexes；The single factor test index carried out from bottom to up is judged；Establish multifactor fuzzy membership sets；Establish multifactor fuzzy membership Weighted Guidelines；Comprehensive level is judged；Comprehensive Evaluation result confirms；With Efficacy Results iteration.
Description
Technical field
This application involves a kind of Effectiveness Evaluation Model, in particular to one kind based on multifactor fuzzy theory reasoning and
The satellite synthetic effectiveness evaluation model of Analytic hierarchy process.The application further relates to a kind of based on multifactor fuzzy theory reasoning and level
The satellite synthetic effectiveness evaluation flow of analytic approach.The application further relates to a kind of based on multifactor fuzzy theory reasoning and analytic hierarchy process
The satellite synthetic effectiveness evaluation algorithm of method.
Background technology
With the fast development of satellite system, all kinds of satellites quickly occur.Each state all quickly establishes satellite network covering, nothing
By from military or business perspective, the power of satellite strength is largely relevant to the prosperity and decline of national strength.So numerous
Satellite construction demand under, the synthetic effectiveness evaluation of satellite is also become more and more important.Compared with single task before, Dan Wei
Star, unification satellite task realize, the warp-wise multitask of present development trend, flexible, more satellites, clustering
Satellite task demand is changed.Therefore original performance method of exhaustion and single performance Evaluation Method to satellite synthetic effectiveness evaluation is all
It can not comply with and meet satellite task background instantly.
The prior art is to establish evaluation index for satellite complex large system to the synthetic effectiveness evaluation general flow of satellite
System；Analytic hierarchy process is used to establish the weight of evaluation index afterwards；Define the alternative collection of evaluation result；Afterwards according to fuzzy theory meter
Calculate single factor judgment matrix；Last Comprehensive Evaluation determines system comprehensive effectiveness.Its particular flow sheet is as shown in Figure 2.
It faces the reality demand, needs to carry out original synthetic effectiveness evaluation method carried out for satellite complication system
Update appropriate adapts to nowadays flexible, motor-driven, variable, multitask complicated satellite demand with this.
Satellite system synthetic effectiveness evaluation index system needs commonly used in intuitive, hierarchical reaction satellite actual task
It asks, function realization method and built-in function divide relationship.Its level dividing mode can be generally divided into：Satellite system comprehensive effectiveness
Layer, satellite task indicator layer and satellite capacity realize layer.
Satellite comprehensive effectiveness layer usually defines satellite overall synthetic efficiency, satellite actual attribute and waits for that comprehensive assessment satellite is real
Border state, such as remote sensing class, navigation type, communication class satellite comprehensive effectiveness, micro-nano cluster satellite comprehensive effectiveness or navigation constellation satellite
Comprehensive effectiveness etc..
Satellite task indicator layer is then divided by the task sport carried out after being defined to satellite integrated system, with micro-nano
For cluster satellite, as shown in Figure 1, it includes navigation task, communication task, remote sensing task dispatchings.
In order to meet above-mentioned task index, need to refine the index.Specifically, being still with micro-nano cluster satellite
Example, for navigation task, its ability realizes that layer should include：Navigation and positioning accuracy, navigation Service time, navigation coverage, space
The abilities such as signal transmission；And remote sensing task ability layer includes then：Optical imagery investigation ability, radar imagery investigation ability, electronics
Information investigation ability etc.；Communication task ability realizes that layer includes：The capacity indexes number such as user capacity, traffic rate, anti-interference
According to.
Therefore, this field still needs a kind of satellite comprehensive effectiveness based on multifactor fuzzy theory reasoning and step analysis
Appraisal procedure.
Invention content
Being designed to provide for the application is a kind of based on the satellite of multifactor fuzzy theory reasoning and Analytic hierarchy process synthesis
Efficiency estimation method.
To achieve the goals above, the application provides following technical proposals.
The application provides a kind of satellite synthetic effectiveness evaluation side based on multifactor fuzzy theory reasoning and Analytic hierarchy process
Method comprising following steps：1) it is to be oriented to carry out level division to satellite comprehensive effectiveness index with mission requirements；2) real to meeting
Satellite efficiency index under the mission requirements of border carries out evaluation index system combing by the level divided, and obtains the assessment of the level
Index system set；3) level evaluation index is carried out according to Analytic hierarchy process to the index system by expert or empirical system
System weight vectors matrix is established, and is divided with respectively different weighted values according to level by the index weights after quantization；4)
Result of considering from expert or empirical system is combined by fuzzy theory reasoning with practical language judge class fuzzy concept,
Possible evaluation result is chosen for a certain specific indexes, and establishes the corresponding alternative collection of single factor evaluation result；5) with level
The mode of change carries out single factor test index from bottom to up to the evaluation index system combed and judges, and matrix calculates；6) it establishes more
Factor fuzzy membership sets；7) multifactor fuzzy membership Weighted Guidelines are established；8) comprehensive level is judged；9) Comprehensive Evaluation knot
Fruit confirms：Using fuzzy reasoning theory combination expert or empirical system, lead to by fuzzy indicator quantification, and by the index of quantification
It crosses after the method in above-mentioned steps carries out quantitative values solution and obtains Comprehensive Evaluation result；With 10) Efficacy Results iteration：To different
Mission requirements carry out multifactor assessment fuzzy membership index and weight matrix fine tuning.
Compared with prior art, having the advantage that for the application carries out complicated multifactor satellite measures of effectiveness.
Description of the drawings
Fig. 1 is the stratal diagram of the micro-nano cluster satellite synthetic effectiveness evaluation index system of the prior art.
Fig. 2 is the schematic diagram of the conventional satellite synthetic effectiveness evaluation flow of the prior art.
Fig. 3 is the satellite comprehensive effectiveness model schematic based on multifactor fuzzy reasoning and Analytic hierarchy process of the application.
Fig. 4 is the satellite synthetic effectiveness evaluation model grade classification schematic diagram of the application.
Fig. 5 is the rough schematic view of the navigation satellite comprehensive effectiveness index system of the application.
Specific implementation mode
Below in conjunction with attached drawing and embodiments herein, carries out clear to the technical solution of the application and completely retouch
It states.
This paper presents the realizations that a kind of new computational methods are used for satellite synthetic effectiveness evaluation, by improving fuzzy reasoning
Judge method simultaneously proposes a kind of new solution with the mode that level method is combined to satellite synthetic effectiveness evaluation index.Fuzzy reasoning
Algorithm is the important means for applying to satellite measures of effectiveness instantly.
Due to satellite comprehensive assessment index system judge not right and wrong ' 0 ' be ' 1 ' presence, the index in many cases
System is the appearance in the form of a kind of uncertainty, therefore by being that basic description instrument carries out mathematical logic with general set theory
Extension just seems fuzzy factors introducing evaluation indice reasonable appropriateness.Entire assessment implementation process is referred to single assessment
Based on target assessment result, simultaneously because there is distinct level in the measures of effectiveness of satellite system, it need to be under same level
Each factor between carry out multifactor evaluation index foundation, and combine the adjustment of real satellite mission requirements, increase dynamic mostly because
Plain fuzzy membership Weighted Guidelines amount.The evaluation index of wherein each level be required for by the lower layer of several evaluation indexes Lai
It determines.Entire synthetic effectiveness evaluation flow be one from bottom and on process.
The basic procedure of multifactor fuzzy reasoning and Analytic hierarchy process is introduced by taking two-stage assessment models as an example：New departure proposes
Overall procedure block diagram it is as shown in Figure 3：
1) assessment models grade classification：It is to be oriented to satellite comprehensive effectiveness indicator layer grade comb to draw with mission requirements
Point, index set L is such as pressed into Attribute decomposition into two-stage assessment models, wherein first order task layer evaluation indice is L1 and the second level
Realize that layer evaluation indice L2, the evaluation indice source divide for satellite system actual attribute.
2) assessment indicator system combs：After completing level division, need to meeting the satellite efficiency under actual task demand
Index carries out evaluation index system combing by level.Herein, for realization layer L2Carry out evaluation index system foundation, the level
The evaluation index system for including down includes：L21、L22、L23……L2n；Level task layer L thereon1It is same to carry out index system point
Solution combs：L11、L12、L13……L1n.The evaluation index system is obtained to integrate as L1={ L11, L12, L13……L1n}；L2={ L21,
L22, L23……L2n, overall objective collection is set, that is, L=L of each point of index set1∪L2, for shown in Fig. 5, L1Expression task
Indicator layer, L2Indicate that system capability realizes that layer, wherein spacing wave, signal anti-interference, spacing wave precision form L21It is right
Answer L1The navigation space signal performance of layer；Test the speed performance, navigation Service time and the navigation of navigation and positioning accuracy therein, navigation is covered
Lid range forms L22Corresponding L1Navigation Service performance in layer.The premise that the indicator evaluation system generates is total according to real satellite
What body function demand and satellite were finally clearly obtained using purpose.
3) evaluation criterion weight collection is established：
In view of the assessment of satellite comprehensive effectiveness index system often needs to be related to multiple evaluation index items, at the same each index item and
Evaluation system hierarchy multiplex, general qualitative or quantitative analysis technology are difficult to carry out weights to evaluation criterion weight to draw
Point.Therefore herein by by Analytic hierarchy process satellite comprehensive effectiveness index system carried out it is qualitative and be quantitatively combined in the way of into
Row network analysis.In conjunction with above-mentioned assessment models grade classification, with each evaluation index relative importance in reflected appraisal system
Difference for the purpose of, need to assign corresponding weights.As for shown in Fig. 5, if the weight vectors of first order evaluation index are
A1={ a1, a2..., an, while with the weight vectors A of second level evaluation index2iWeight matrix is constructed for row, obtains the second layer
The weight vectors matrix of assessment indicator system is then A2={ A21, A22..., A2n, wherein A2i={ ai1, ai2..., ain(i=1,
2,……,n).The weight sets of evaluation index is made of each level, and the acquisition of value is special by analytic hierarchy process (AHP) and to each field
Obtained by the consulting of family.
4) the alternative collection of single factor evaluation result is established：Result and practical language will be considered obtained by the expert or empirical system
Speech is judged class fuzzy concept and is combined, and possible evaluation result is chosen for a certain specific indexes or things item.If evaluation result
Including { fine, good, general, poor, poor } totally 5 as a result, the evaluation result set V then established it is corresponding be V={ a1,
a2, a3, a4, a5, wherein a1, a2, a3, a4, a5It corresponds to respectively fine to poor judgment criteria in evaluation result.
5) single factor test index jdgement matrix calculates：
Simple element evaluation from bottom to up is carried out to the evaluation index system combed in a manner of hierarchical, herein with two
For layer comprehensive effectiveness index system, first from the single factor Y of second level evaluation indice2jIt sets out, determines system phase to be evaluated
For the degree of membership of alternative collection element, i.e. fuzzy vector.To index of different nature, the mould of distinct methods parameter should be taken
Paste vector.By the fuzzy membership functions type of each individual event quantitative target of determination, and the membership function coefficient that seeks advice from experts
Then value calculates fuzzy vector of all quantitative targets relative to alternative collection element, while using above-mentioned fuzzy vector as row structure
Make the single factor judgment matrix R of current layer overall target factor, the acquisition of value from expertise system and combine the 3) in
The evaluation result established is selected collection and is obtained.By taking Fig. 5 as an example：Second level evaluation index Y2j(j=1,2 ..., n) is relative to alternative
Collect the fuzzy membership vector R of element in V2j={ rj1,rj2,……,rjs, and Σ rjk=1, (k=1,2 ..., s)., rjk≧0
(j=1,2 ..., n；K=1,2 ..., p).Then, it is row construction second level evaluation index with the fuzzy vector of all single indexs
The single factor judgment matrix R of collection2(n × p), bottom-up development matrix operation.
6) multifactor evaluation fuzzy membership sets are established：Multifactor evaluation fuzzy membership sets are established based on laterally right
Than the fuzzy membership sets mutually established compared with single factor evaluation results set, multifactor evaluation result set is chosen single
As a result it exports, it is that judgment criteria establishes set, but only chooses final high that with two-by-two, mutually more comparison result, which is { excellent, equivalent, bad },
Probability results item, final collection of establishing are combined into D2k={ dk1, dk2... ..., dkn}.The foundation of the index need to consider each list between same level
Correlation between index.Lateral cross compares between multifactor, while being obtained using multifactor evaluation fuzzy membership sets
Multifactor fuzzy membership value is obtained, it is practical to compare because using intersection although the value still comes from expert system, therefore significantly
Reduce subjectivity and monistic disadvantage.Equally by taking the second level as an example, multifactor fuzzy membership index D2={ D21,
D22... ..., D2j(j=1,2 ..., n).The foundation of the index needs first to enumerate each index of level progress topology, it is assumed that the
For two levels have 3 single factor test indexs, topological matrix is enumerated as shown in the table, and the acquisition of the matrix is first with single index
Factor is that row is arranged, and the aforementioned multifactor evaluation fuzzy membership sets for proposing to establish is being utilized, with D21For first run ratio
Compared with data, by it respectively at other two single factor test index of same level D22、D23It is compared, obtains relatively large value.It calculates simultaneously
Its relative probability result compared two-by-two as this under output as a result, by it according to arranging from big to small after result acquisition
Sequence, the multifactor evaluation fuzzy membership sets D for obtaining and establishing2={ D21, D22, D23}(D21＞ D22＞ D23)。
7) multifactor fuzzy membership Weighted Guidelines are established：Current almost all of efficiency index assessment is all based on institute as above
The analytic hierarchy process combination fuzzy theory stated is realized, and is usually only introduced expertise system to single factor test index and carried out fuzzy membership
Degree, which confirms, simultaneously to be calculated for level, but as previously mentioned, carries out fuzzy membership confirmation to single factor test index and by itself and finger
Mark system weight calculates the factor as only the two of measures of effectiveness and is easy excessively to introduce expert's influence and consideration relatively fewer simultaneously
The relationship between each index system under multifactor various dimensions is secondly also more unknown for the iteration feedback effect of later stage measures of effectiveness
It is aobvious.And since Future Satellite actually uses vdiverse in function, and for the specific emergency scene such as wartime is emergent, there are satellite effects
The variation of the practical index of energy, while the division of satellite comprehensive effectiveness index weights being caused to have differences variation.Therefore innovative point is more
Introduce multifactor fuzzy membership Weighted Guidelines Q on the basis of factor evaluation fuzzy membership sets, the Weighted Guidelines be according to
It factually is assessed to obtain under border satellite application or particular task adjustment and wartime particular demands, the addition of the value can be to original
Fixed satellite synthetic effectiveness evaluation index system carry out dynamically changeable adjustment, the quantization meaning of the value is to multifactor evaluation
The quantizations of fuzzy membership sets weights, and will weighting acquired results by satellite synthetic effectiveness evaluation index system it is hierarchical based on
In calculation.Multifactor evaluation fuzzy membership to be combined also needs to establish Weighted Guidelines item after obtaining, by each list of same level
The multifactor evaluation fuzzy membership sets D compared two-by-two after process between factor2Be weighted judgement, since from expert pass through
The quantization weighted comprehensive coefficient of check system is that final opposite weighted size is distributed item by item.As with " 10% ", (value is this example
Acquisition for Weighted Guidelines quantitative values, the multifactor Weighted Guidelines item need to be quantified according to actual task demand or wartime scenario
Adjustment, the index are the adjustable index of dynamic, for meeting real satellite demand and multiple measures of effectiveness iteration effect to greatest extent
Can) as this level quantization weighted comprehensive coefficient, the multifactor mould obtained on the basis of multifactor evaluation fuzzy membership sets
Paste is subordinate to metrization weight quantization index Q2={ Q/2 (D21),0.00(D22) ,-Q/2 (D23) i.e. Q2=0.05,0.00 ,-
0.05}。
8) comprehensive level is judged：Entire comprehensive level Appraisal process operation is bottom-up, by taking system shown in Figure 5 as an example into
Row Decompose operaton describes：Pass through expert system capacitation layer index weights matrix A first2, utilize analytic hierarchy process (AHP) and expert
The fuzzy membership that system combination fuzzy comprehensive evaluation method obtains is selected collection capacitation layer single factor judgment matrix R2, determine and add
Weighting ratio coefficient obtains new multifactor fuzzy membership in combination with multifactor, and using expert system to each Dan Yin
It carries out intersecting between element and compare, finally gather weight ratio and be worth to Weighted Guidelines value Q of each single factor test compared with other elements, and
Multifactor fuzzy membership metrization Weighted Guidelines collection Q is calculated using weighted valuen, recycle formula R1 *=A2×(R2+Qn),
N*=A1×R1, such as task layer jdgement matrix R1From with realize layer weight matrix and simple element evaluation put to the proof by combine mostly because
Quantization Weighted Guidelines Q acquired in plain fuzzy membership metrization Weighted Guidelines value QnIt is optimal to corresponding single factor test index jdgement matrix
Position is weighted, while the result after most bad position subtracts most bad weighted value carries out matrix multiple acquisition, i.e., upper layer level is comprehensive
It closes evaluation result N to judge from current next level multi-factor comprehensive level, final current level evaluation result N=A × (R+
“Qn”).And the weight matrix A that the assessment result N of current level is equally calculated as last layer.Such operation layer by layer is to top
Grade obtains final evaluation result Nfin。
9) Comprehensive Evaluation result confirms：The final result of synthetic effectiveness evaluation, which obtains to depend on, utilizes fuzzy reasoning theory knot
Expertise system is closed, fuzzy indicator is subjected to quantification, and the index of quantification is subjected to quantitative values by the above method and is asked
Solution obtains, and for satellite system, final system to be evaluated is relatively single, therefore can directly use fuzzy distribution, directly
Regard last result as final evaluation result.
10) Efficacy Results iteration：Simple measures of effectiveness value calculating cannot be satisfied fast changing actual demand, while nothing
Method, which meets, responds numerous and complicated mixed and disorderly military actual demand and situation of battlefield.One index is no longer enough to represent a kind of satellite system
System, it is therefore desirable to Efficacy Results iteration be carried out to the satellite system under specific tasks background, different mission requirements are carried out more
The multitask that factors assessment fuzzy membership index and weight matrix fine tuning, fine tuning and interative computation are used to meet present satellites is real
Existing, more scene application model, is realized for particular task under demand and more scene application models, and Weighted Guidelines are adjusted by dynamic
Quantitative values, can meet instantly needed for actual operation demand, obtain adjustment after satellite comprehensive effectiveness index value.Such as to lead
It navigates for micro-nano satellite, under normal condition, multifactor weighting quantitative target Q is 0%, military specific when local operation etc. occurs
When purposes, major demands become the performance supplement to backbone navigation large satellite, therefore for the navigator fix of ability level essence
The weight of the four indices such as degree becomes 10%~15% weight quantization, more focuses on to the theater of war compared under normal condition
The monitoring of local navigator fix, can be played by dynamically adjusting multifactor weighted value and the accurate of present satellites comprehensive effectiveness is commented
Estimate.The dynamic adjustable feature for having benefited from multifactor assessment fuzzy membership and Weighted Guidelines, can adapt to quick Efficacy Results iteration
It calculates, is to be oriented to obtain final Efficacy Results rapidly with task satisfaction.
To sum up, herein with regard to multifactor fuzzy reasoning and Analytic hierarchy process be applied to satellite synthetic effectiveness evaluation technology it
On, it is now target according to aforementioned progress example realization using practical navigation satellite synthetic effectiveness evaluation.
Navigation actual task demand carries out navigation satellite synthetic effectiveness evaluation model foundation, establishes satellite simplification
Effectiveness evaluation index system model is as shown in Figure 5.
For established navigation satellite effectiveness evaluation index system model, using Analytic hierarchy process, and expert's warp is introduced
Check system carries out quantifying to define, and the weight vectors of each level index of gained correspond to task layer index weights matrix A1And it realizes
Layer index weights matrix A2.Its occurrence is shown in as shown in the table respectively.
1 task index layer weight vectors of table divide
| A1 | 0.44 | 0.56 |
2 system capability layer weight vectors of table divide
| A21 | 0.35 | 0.40 | 0.25 | 0.00 | 0.00 | 0.00 | 0.00 |
| A22 | 0.00 | 0.00 | 0.00 | 0.45 | 0.15 | 0.25 | 0.15 |
It is fuzzy comprehensive evoluation content to choose { fine, good, general, poor, poor }, corresponding to establish single factor evaluation result set
Close V={ a1, a2, a3, a4, a5, wherein a1, a2, a3, a4, a5It corresponds to respectively fine to poor judgment criteria in evaluation result.So
Single factor test index jdgement matrix, which is established, afterwards needs to carry out from bottom to up the evaluation index system combed in a manner of hierarchical
Simple element evaluation, the single factor test in all levels realizes that quantizating index is required for after expertise system carries out consulting confirmation
It obtains, single factor judgment matrix vector R of this example to system capability layer fuzzy vector2As shown in the table.
3 single factor judgment matrix R of table2
| R21 | 0.20 | 0.80 | 0.00 | 0.00 | 0.00 |
| R22 | 0.70 | 0.30 | 0.00 | 0.00 | 0.00 |
| R23 | 0.00 | 0.50 | 0.50 | 0.00 | 0.00 |
| R24 | 0.80 | 0.20 | 0.00 | 0.00 | 0.00 |
| R25 | 0.00 | 0.60 | 0.40 | 0.00 | 0.00 |
| R26 | 0.00 | 0.40 | 0.60 | 0.00 | 0.00 |
| R27 | 0.50 | 0.50 | 0.00 | 0.00 | 0.00 |
It is simultaneously row construction upper level evaluation index jdgement matrix R with current layer fuzzy vector degree of membership1 *=R2×A2.Together
When, on the basis of having carried out related single factor test Index Establishment fuzzy membership, multifactor fuzzy membership Weighted Guidelines are added
Q, comparing two-by-two after process also according to expertise system carrying out carrying out each index after topology is enumerated between each index of the level
System is obtained to multifactor evaluation fuzzy membership sets D2={ R24, R22, R27, R21, R25, R23, R26, since from expertise system
The quantization weighted comprehensive coefficient of system is that final opposite weighted size is distributed item by item.It is comprehensive using 10% as the quantization weighting of this level
Collaboration number, the multifactor fuzzy membership metrization Weighted Guidelines Q2=obtained on the basis of multifactor evaluation fuzzy membership sets
{0.03(R24), 0.02(R22), 0.01(R27), 0.00(R21), -0.01(R25), -0.02(R23), -0.03(R26)}.Current level judges knot
Fruit N*=A × (R+ " Qn ").And the weight matrix A that the assessment result N of current level is equally calculated as last layer.As shown above
N is calculated1(R1) as shown in the table, it obtains obtaining final N also according to realization layer calculation1 *=R1×A1.By such as
This operation layer by layer to highest level obtains final evaluation result Nfin={ 0.201,0.411,0.138,0,0 }.
4 task index layer single factor test matrix of table
| N11(R11) | 0.358 | 0.512 | 0.130 | 0.000 | 0.000 |
| N12(R12) | 0.077 | 0.331 | 0.144 | 0.000 | 0.000 |
The characteristics of according to satellite system, uses fuzzy distribution to evaluation result, and the maximum value chosen in final result is seen
Do final evaluation result.Example as above analyzes final evaluation result：Its final judgment criteria judges degree of membership according to be maximum
Expert's result of calculation that item is 41.1% thinks that the efficiency evaluation result of calculation is " good ".
In view of used example is the navigation satellite synthetic effectiveness evaluation after simplifying, result of calculation can only be used as one
A investigation reference point, accurately reference point still needs by setting out to navigation satellite task satisfaction in more detail, takes into account simultaneously
The aspect such as the elements such as economic cost, risk and combination actual use scene, task actual support is set out, to evaluation index
System is finely adjusted while carrying out expertise amount to single factor test index jdgement matrix and multifactor fuzzy membership Weighted Guidelines
Change output and mathematical computations obtain final satisfaction reality, close to true satellite synthetic effectiveness evaluation value so that it can really do
It is reacted to entire the satellite system even true assessment of the comprehensive effectiveness of more satellite clusters or even constellation, realizes to be formed for satellite
Certain guarantee estimated value.
The above-mentioned description to embodiment is that this Shen can be understood and applied for the ease of those skilled in the art
Please.Person skilled in the art obviously easily can make various modifications to these embodiments, and described herein
General Principle is applied in other embodiments without paying performing creative labour.Therefore, the application is not limited to implementation here
Example, those skilled in the art make according to herein disclosed content in the case where not departing from the application scope and spirit
It improves and changes within all scope of the present application.
Claims (6)
1. a kind of satellite synthetic effectiveness evaluation method based on multifactor fuzzy theory reasoning and Analytic hierarchy process, feature exist
In including the following steps：
1) it is to be oriented to carry out level division to satellite comprehensive effectiveness index with mission requirements；
2) evaluation index system combing is carried out by the level of division to meeting the satellite efficiency index under actual task demand, and obtained
To the evaluation index system set of the level；
3) level assessment indicator system weight is carried out according to Analytic hierarchy process to the index system by expert or empirical system
Vector matrix is established, and is divided with respectively different weighted values according to level by the index weights after quantization；
4) result of considering from expert or empirical system is judged into class fuzzy concept by fuzzy theory reasoning and practical language
It is combined, chooses possible evaluation result for a certain specific indexes, and establish the corresponding alternative collection of single factor evaluation result；
5) it carries out single factor test index from bottom to up to the evaluation index system combed in a manner of hierarchical to judge, matrix meter
It calculates；
6) multifactor fuzzy membership sets are established；
7) multifactor fuzzy membership Weighted Guidelines are established；
8) comprehensive level is judged；
9) Comprehensive Evaluation result confirms：Using fuzzy reasoning theory combination expert or empirical system, by fuzzy indicator quantification, and
By the index of quantification through the above steps in method carry out quantitative values solution after obtain Comprehensive Evaluation result；
10) Efficacy Results iteration：Multifactor assessment fuzzy membership index is carried out to different mission requirements and weight matrix is micro-
It adjusts.
2. the method as described in claim 1, which is characterized in that the simple element evaluation in the step 5) includes the following steps：
First from the single factor Y of second level evaluation indice2jIt sets out, determines degree of membership of the system to be evaluated relative to alternative collection element,
That is fuzzy vector；Secondly it is the simple element evaluation square gone and construct second level evaluation indice with the fuzzy vector of all single indexs
Battle array R2(n × p), bottom-up development matrix operation.
3. the method as described in claim 1, which is characterized in that the multifactor evaluation fuzzy membership sets in the step 6)
Establish mode pass through using two-by-two mutually more comparison result be judgment criteria establish set, choose final high probability result items, most
Set is established eventually.
4. the method as described in claim 1, which is characterized in that the multifactor fuzzy membership Weighted Guidelines in the step 7)
Q according to real satellite apply or particular task adjustment and wartime particular demands under assessed to obtain.
5. the method as described in claim 1, which is characterized in that the synthesis level Appraisal process of the step 8) is bottom-up
Operation.
6. method as claimed in claim 5, which is characterized in that the synthesis level of the step 8) is judged, and is included the following steps：
Pass through expert system capacitation layer index weights matrix A first2, utilize analytic hierarchy process (AHP) and expert system combination fuzzy synthesis
The fuzzy membership that judge method obtains is selected collection capacitation layer single factor judgment matrix R2, determine weighted value proportionality coefficient, together
When in conjunction with multifactor obtain new multifactor fuzzy membership, and intersection phase is carried out between each single factor test using expert system
Compared with finally set weight ratio is worth to Weighted Guidelines value Q of each single factor test compared with other elements, and is calculated using weighted value
To multifactor fuzzy membership metrization Weighted Guidelines collection Qn, recycle formula R1 *=A2×(R2+Qn), N*=A1×R1, such as task
Layer jdgement matrix R1Multifactor fuzzy membership metrization is combined from putting to the proof to pass through with simple element evaluation with realization layer weight matrix
Quantization Weighted Guidelines Q acquired in Weighted Guidelines value QnThe optimal position of corresponding single factor test index jdgement matrix is weighted, simultaneously
Result after most bad position subtracts most bad weighted value carries out matrix multiple acquisition, i.e. the Comprehensive Evaluation result N of upper layer level comes from
Current next level multi-factor comprehensive level is judged, final current level evaluation result N*=A × (R+ " Qn”).And current layer
The weight matrix A that the assessment result N of grade is equally calculated as last layer.Such operation layer by layer to highest level obtains final judge
As a result Nfin。
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| CN110108282A (en) * | 2019-05-09 | 2019-08-09 | 仲恺农业工程学院 | Multi-source information obstacle avoidance apparatus and obstacle avoidance system |
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103439716A (en) * | 2013-08-21 | 2013-12-11 | 电子科技大学 | Method for constructing GNSS receiver anti-interference evaluation index system |
| CN104834987A (en) * | 2015-03-09 | 2015-08-12 | 中国人民解放军装甲兵工程学院 | Quantitative decision-making method based on layer analysis, and quantitative decision-making system |
| CN104850901A (en) * | 2015-04-27 | 2015-08-19 | 辽宁工程技术大学 | Soft measurement method and soft measurement system for predicting gas concentration based on multiple models |
| CN107371256A (en) * | 2016-05-12 | 2017-11-21 | 华硕电脑股份有限公司 | The detection of control channel with different Transmission Time Intervals in wireless communication system |
| CN107576920A (en) * | 2017-08-02 | 2018-01-12 | 北京空间飞行器总体设计部 | A kind of satellite power supply health degree computational methods based on fuzzy multi-attribute evaluation |
-
2018
- 2018-05-04 CN CN201810418991.3A patent/CN108629511A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103439716A (en) * | 2013-08-21 | 2013-12-11 | 电子科技大学 | Method for constructing GNSS receiver anti-interference evaluation index system |
| CN104834987A (en) * | 2015-03-09 | 2015-08-12 | 中国人民解放军装甲兵工程学院 | Quantitative decision-making method based on layer analysis, and quantitative decision-making system |
| CN104850901A (en) * | 2015-04-27 | 2015-08-19 | 辽宁工程技术大学 | Soft measurement method and soft measurement system for predicting gas concentration based on multiple models |
| CN107371256A (en) * | 2016-05-12 | 2017-11-21 | 华硕电脑股份有限公司 | The detection of control channel with different Transmission Time Intervals in wireless communication system |
| CN107576920A (en) * | 2017-08-02 | 2018-01-12 | 北京空间飞行器总体设计部 | A kind of satellite power supply health degree computational methods based on fuzzy multi-attribute evaluation |
Non-Patent Citations (2)
| Title |
|---|
| 安雪滢 等: "基于模糊理论的卫星系统效能评估仿真研究", 《系统仿真学报》 * |
| 项磊 等: "基于层次分析法与模糊理论的卫星效能评估", 《计算机仿真》 * |
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| CN113743811A (en) * | 2021-09-10 | 2021-12-03 | 上海卫星工程研究所 | Comprehensive efficiency evaluation method and system adopting coefficient weighting calculation |
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