CN110069815A - Index system construction method, system and terminal device - Google Patents
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Abstract
The present invention is suitable for big data analysis technical field, discloses a kind of index system construction method, system and terminal device, comprising: obtains the emulation data emulated to Weapon Equipment System, and carries out data prediction to emulation data；Based on pretreated emulation data, the super pessimistic concurrency control of weighting of Weapon Equipment System is constructed；Based on the measures of effectiveness target of weighting super pessimistic concurrency control and preset Weapon Equipment System, the index system that measures of effectiveness is carried out to Weapon Equipment System is constructed.The present invention can solve the problem of traditional " tree-shaped " weaponry evaluation index system can not be suitable for modern weapons equipment architecture, networking index system can be constructed, it more can be suitably used for modern weapons equipment architecture, measures of effectiveness more rationally and effectively can be carried out to Weapon Equipment System.
Description
Technical field
The invention belongs to big data analysis technical field more particularly to a kind of index system construction methods, system and terminal
Equipment.
Background technique
Index system establishment is basis and the foundation for carrying out Weapon Equipment System measures of effectiveness, therefore, reasonable construction index
System can provide more structurally sound theoretical foundation for Weapon Equipment System measures of effectiveness.
Traditional index system establishment is building " tree-shaped " weaponry evaluation index system, still, due to modern weapons
Equipment architecture shows networked characteristics, and traditional " tree-shaped " weaponry evaluation index system can not be suitable for modern weapons
Equipment architecture.
Summary of the invention
In view of this, the embodiment of the invention provides a kind of index system construction method, system and terminal device, to solve
In the prior art, traditional " tree-shaped " weaponry evaluation index system can not be suitable for asking for modern weapons equipment architecture
Topic.
The first aspect of the embodiment of the present invention provides a kind of index system construction method, comprising:
The emulation data emulated to Weapon Equipment System are obtained, and data prediction is carried out to emulation data；
Based on pretreated emulation data, the super pessimistic concurrency control of weighting of Weapon Equipment System is constructed；
Based on the measures of effectiveness target of weighting super pessimistic concurrency control and preset Weapon Equipment System, construct to Weapon Equipment System
Carry out the index system of measures of effectiveness.
The second aspect of the embodiment of the present invention provides a kind of index system establishment system, comprising:
Data acquisition module is emulated, for obtaining the emulation data emulated to Weapon Equipment System, and to imitative
True data carries out data prediction；
Model construction module constructs the super net mould of weighting of Weapon Equipment System for being based on pretreated emulation data
Type；
Index system establishment module, for the measures of effectiveness mesh based on weighting super pessimistic concurrency control and preset Weapon Equipment System
Mark constructs the index system that measures of effectiveness is carried out to Weapon Equipment System.
The third aspect of the embodiment of the present invention provides a kind of terminal device, including memory, processor and is stored in
In memory and the computer program that can run on a processor, processor are realized when executing computer program such as first aspect institute
The step of stating index system construction method.
The fourth aspect of the embodiment of the present invention provides a kind of computer readable storage medium, computer readable storage medium
It is stored with computer program, index system as described in relation to the first aspect is realized when computer program is executed by one or more processors
The step of construction method.
Existing beneficial effect is the embodiment of the present invention compared with prior art: the embodiment of the present invention is obtained to weapon first
The emulation data that equipment architecture is emulated, and data prediction is carried out to emulation data, it is then based on pretreated
Data are emulated, the super pessimistic concurrency control of weighting of Weapon Equipment System is constructed, finally based on the super pessimistic concurrency control of weighting and preset weaponry
The measures of effectiveness target of system constructs the index system for carrying out measures of effectiveness to Weapon Equipment System, can construct networking and refer to
Mark system more can be suitably used for modern weapons equipment architecture, more rationally and effectively can carry out efficiency to Weapon Equipment System and comment
Estimate.
Detailed description of the invention
It to describe the technical solutions in the embodiments of the present invention more clearly, below will be to embodiment or description of the prior art
Needed in attached drawing be briefly described, it should be apparent that, the accompanying drawings in the following description is only of the invention some
Embodiment for those of ordinary skill in the art without any creative labor, can also be according to these
Attached drawing obtains other attached drawings.
Fig. 1 is the implementation process schematic diagram for the index system construction method that one embodiment of the invention provides；
Fig. 2 be another embodiment of the present invention provides index system construction method implementation process schematic diagram；
Fig. 3 is the implementation process schematic diagram for the index system construction method that yet another embodiment of the invention provides；
Fig. 4 is the implementation process schematic diagram for the index system construction method that further embodiment of this invention provides；
Fig. 5 is the schematic block diagram for the index system establishment system that one embodiment of the invention provides；
Fig. 6 is the schematic block diagram for the terminal device that one embodiment of the invention provides.
Specific embodiment
In being described below, for illustration and not for limitation, the tool of such as particular system structure, technology etc is proposed
Body details, so as to provide a thorough understanding of the present application embodiment.However, it will be clear to one skilled in the art that there is no these specific
The application also may be implemented in the other embodiments of details.In other situations, it omits to well-known system, device, electricity
The detailed description of road and method, so as not to obscure the description of the present application with unnecessary details.
In order to illustrate technical solutions according to the invention, the following is a description of specific embodiments.
Fig. 1 is the implementation process schematic diagram for the index system construction method that one embodiment of the invention provides, for the ease of saying
Bright, only parts related to embodiments of the present invention are shown.The executing subject of the embodiment of the present invention can be terminal device.
As shown in Figure 1, this method may comprise steps of:
Step S101: the emulation data emulated to Weapon Equipment System are obtained, and emulation data are counted
Data preprocess.
In embodiments of the present invention, rely on existing large artificial system, to Weapon Equipment System carry out emulation deduce and
Experiment obtains emulation data.Wherein, emulation data are emulation big data, may include daily record data, data reporting and instruction number
According to etc..Weapon Equipment System is by the entities such as ultra-large sensor, command and control, communication or system, by various wired
Or the complication system that wireless mode is formed by connecting.
Data prediction may include data processing and data analysis.Specifically, needed for Weapon Equipment System measures of effectiveness
Data source establish on distributed database (structural data) and Miscellaneous Documents system (unstructured data), according to
The demand of Weapon Equipment System measures of effectiveness, needs to establish these initial data data model, carry out data classification, extraction,
The processing such as storage and management；In data analysis phase, integrated, data quality management, data fusion, data correlation by multi-source
Treated that result is reprocessed to data for analysis, data standard etc., solve the quality of data is not high, data are not complete, data not
The problems such as specification.
Real-time simulation deduction can be carried out to Weapon Equipment System by large artificial system and experiment obtains real-time update
Emulation data, data prediction is carried out to the emulation data of real-time update, according to the emulation number of pretreated real-time update
Super pessimistic concurrency control is weighted according to real-time update.
Step S102: pretreated emulation data are based on, the super pessimistic concurrency control of weighting of Weapon Equipment System is constructed.
Wherein, the super pessimistic concurrency control of weighting of Weapon Equipment System be in order to carry out System Effectiveness analysis and establish one is abstracted
It indicates, it includes that node, functional network and weighting surpass dependence in net.
Super-network is the Non-manifold edges heterogeneous network that a plurality of types of nodes are connected to composition by a variety of connection types,
The network emphasizes allomeric function, and multiple interactive subnets can be divided into according to node or link attribute.
The node weighted in super pessimistic concurrency control corresponds to the various entities on battlefield, such as probe node, information aggregators, accuses
Node, Strike node, communication node and destination node.The functional network weighted in super pessimistic concurrency control describes in system combat
Various basic function networks, such as Sensor Network accuse net and communication network.Weighting the dependence in super pessimistic concurrency control may include: to pass
Feel net, accuse the communication dependence between net and communication network, Sensor Network accuses that the State-dependence between net and enemy's node closes
Information dependence between system and Sensor Network and charge net.
In embodiments of the present invention, pretreated emulation data are based on, the weighting that can construct Weapon Equipment System is super
Pessimistic concurrency control.
Step S103: the measures of effectiveness target based on weighting super pessimistic concurrency control and preset Weapon Equipment System is constructed to force
The index system of device equipment architecture progress measures of effectiveness.
Wherein, index system refer to be made of in assessment activity a series of essential attribute indexs that are mutually related it is organic whole
Body.The measures of effectiveness target of Weapon Equipment System can be preset according to actual needs.
In embodiments of the present invention, according to the super pessimistic concurrency control of weighting of the measures of effectiveness target and building of Weapon Equipment System,
The index system that measures of effectiveness is carried out to Weapon Equipment System can be constructed.
Seen from the above description, the embodiment of the present invention obtains the emulation number emulated to Weapon Equipment System first
According to, and data prediction is carried out to emulation data, pretreated emulation data are then based on, adding for Weapon Equipment System is constructed
Super pessimistic concurrency control is weighed, the measures of effectiveness target finally based on weighting super pessimistic concurrency control and preset Weapon Equipment System is constructed to weapon
Equipment architecture carries out the index system of measures of effectiveness, and by big data analysis, the magnanimity generated during being deduced using emulation is more
The emulation big data of source isomery constructs networking index system, more can be suitably used for modern weapons equipment architecture, can more rationally
Measures of effectiveness effectively is carried out to Weapon Equipment System.
Fig. 2 be another embodiment of the present invention provides index system construction method implementation process schematic diagram, for the ease of
Illustrate, only parts related to embodiments of the present invention are shown.As shown in Fig. 2, on the basis of the above embodiments, step S102
It may comprise steps of:
Step S201: analyzing pretreated emulation data, establishes corresponding weighting according to the function of military simulation entity
Super net node, and the super net node of the weighting of foundation is included into corresponding node set.
Wherein, weighting super net node is the node in the super pessimistic concurrency control of weighting.Military simulation entity can be combat troop, force
Device platform etc..Node set may include probe node set, information aggregators set, accuse that node set, firepower are beaten
Beat time point set, communication node set and destination node set.
It in embodiments of the present invention, can be according to the function of military simulation entity by analyzing pretreated emulation data
The super net node of the corresponding weighting of each military simulation entity can be established, and the super net node of the weighting of foundation is included into corresponding
In node set.
Step S202: analyzing the information flow of Weapon Equipment System, according to the corresponding super net node of weighting of information flow connection, builds
The functional network side of vertical functional network, and calculate the weight on each functional network side.
Wherein, information flow includes communication stream, sensing stream and accuses stream.Communication network is completed the transmission of various battle field informations, is deposited
It stores up and distributes, the interactive relation between node in communication network is known as communication stream；Sensor Network is completed to implement to divide to the information of collection
It analyses and handles, the interactive relation between node in Sensor Network is known as sensing stream；Accuse that net is formed specifically according to situation of battlefield
Battle plan, not to command and control are implemented, accuses that the interactive relation between the node in net is known as accusing stream to related.In function
In energy network, the line between two nodes is known as functional network side.
In embodiments of the present invention, by analyzing the information flow of Weapon Equipment System, that is, the friendship between each node is analyzed
Mutual relation forms the functional network side of functional network according to the corresponding super net node of weighting of interactive relation connection between node.
In some functional network, give from node viIt is directed toward node vjA directed edge (vi, vj), definitionIt indicates the degree of transitivity for generating information (communication stream, sensing stream or accusing stream) in period T, enablesIndicate the maximum information degree of transitivity generated in all directed edges, then directed edge (vi,
vj) weight Φ (vi, vj) it is calculated by formula (1):
Step S203: the dependence side between functional network is established, and the weight on dependence side is set.
In embodiments of the present invention, dependence when including communication dependence, State-dependence relationship side and information according to
Rely relationship side.If having communication dependence between two nodes, the line between two nodes is known as to communicate dependence
Relationship side；If having State-dependence relationship between two nodes, the line between two nodes is known as State-dependence and is closed
It is side；If having information dependence between two nodes, the line between two nodes is known as information dependence
Side.The weight on dependence side is disposed as 1.
Optionally, on the basis of statistical analysis, in conjunction with the qualitative analysis to practical Weapon Equipment System, conditional
In the case of can be compared with the system according to the building of practical connection relationship, weight super pessimistic concurrency control in order to modify.
In one embodiment of the invention, after step s 103, the above method can also include:
Based on the emulation data obtained in real time, updates and weight super pessimistic concurrency control.
In embodiments of the present invention, emulation deduction and experiment can be carried out to Weapon Equipment System in real time, so as to reality
When obtain emulation data, data prediction is carried out to the emulation data that obtain in real time, according to it is pretreated obtain in real time it is imitative
True data can weight super pessimistic concurrency control with real-time update.Wherein, the emulation data that different moments obtain may be identical, it is also possible to no
It is identical.
Specifically, during emulation is deduced and is tested, if there is increasing or decreasing for military simulation entity, basis
The function renewal of the military simulation entity increased or decreased weights the node set of super pessimistic concurrency control；If the work in some functional network
War relationship changes, and produces new information flow, then updates the functional network side in the functional network, and calculate the function
The weight of network edge；If the dependence between different functional networks changes, update the different functional network it
Between dependence side, and the weight on the dependence side is set as 1.
Seen from the above description, the embodiment of the present invention can weight super pessimistic concurrency control according to Generation of simulating data, and can be real
Shi Gengxin weights super pessimistic concurrency control, so that the characteristics of super pessimistic concurrency control of weighting is more in line with Weapon Equipment System, in order to more preferable twelve Earthly Branches
It holds and measures of effectiveness is carried out to Weapon Equipment System.
Fig. 3 is the implementation process schematic diagram for the index system construction method that yet another embodiment of the invention provides, for the ease of
Illustrate, only parts related to embodiments of the present invention are shown.As shown in figure 3, on the basis of the above embodiments, step S103
It may comprise steps of:
Step S301: it is based on measures of effectiveness target, determines the structure of index system.
In embodiments of the present invention, measures of effectiveness target is analyzed first, carrying out analysis to measures of effectiveness target is
Construct the premise of index system.Measures of effectiveness target is measures of effectiveness purpose to be achieved, i.e. Weapon Equipment System assessment result
Most important not instead of " quality " finds problem of the Weapon Equipment System in structure, ability and efficiency, improves and fill to weapon
The cognition of standby system.
By the analysis to measures of effectiveness target, to determine the structure of index system.Different targets can be brought different
The structure type of index system.The structure type of common index system includes hierarchical index system and network-type index body
System.Since Weapon Equipment System is typical complication system, networked characteristics are showed, so selection network-type index system.
Step S302: according to the structure of index system, reference model is selected.
According to the network-type index system structure of selection, select network analysis (Analytic Network Process,
ANP) model is as reference model.
Step S303: according to reference model, efficacy measure index is determined.
Wherein, the construction achievement of efficacy measure index primary metric and performance Weapon Equipment System, such as to the adaptive of system
It should be able to power, recombination ability, survivability, dispersibility, hidden ability, flexibility, the assessment of the abilities such as high-effect.
Weapon Equipment System is analyzed by using ANP model, determine efficacy measure index may include survivability,
Recombinant, dispersibility, concealment, propinquity, flexibility, adaptability and high efficiency.
Step S304: according to super pessimistic concurrency control is weighted, basal evaluation index is determined.
Basal evaluation index reflects the overall performance of Weapon Equipment System, and the characteristic parameter by weighting super pessimistic concurrency control constructs
Basal evaluation index.Basal evaluation index includes individual behavior evaluation index and system global behavior evaluation index.Individual behavior
The evaluation object of evaluation index is the structure and behavior characteristic that individual and its interbehavior are constituted in Weapon Equipment System；System is whole
The evaluation object of body behavior evaluation index is system global behavior characteristic and integral structure characteristic.Individual behavior evaluation index can
To include active node quantity, degree, level, function center of gravity quantity and distribution and betweenness etc.；System global behavior evaluation index can
To include degree of communication, link nodes ratio, neutral rate and number of clusters and cluster scale etc..
Step S305: analyzing each being associated property of index in efficacy measure index and basal evaluation index, determines
Incidence relation between each index.
In embodiments of the present invention, each being associated property of index can be analyzed by existing method, determines each finger
Incidence relation between mark.By index association analysis, status and influence of the available each index in comprehensive assessment
Degree.
Step S306: referred to according to the incidence relation determination between efficacy measure index, basal evaluation index and each index
Mark system.
Incidence relation between efficacy measure index, basal evaluation index and each index constitutes initial index body
System.
It is alternatively possible to which initial index system is examined in practice, and it is based on actual assessment result, to initial
Index system improves, and obtains final index system.
Fig. 4 is the implementation process schematic diagram for the index system construction method that further embodiment of this invention provides, for the ease of
Illustrate, only parts related to embodiments of the present invention are shown.As shown in figure 4, after step S305, the above method can be with
Include:
Step S401: the weight of each efficacy measure index is calculated.
The empirical data provided according to expert calculates the power between efficacy measure index using Delphi (Delphi) method
Weight, establishes weighting matrix.
Specifically, the empirical data provided according to expert determines the different degree of each efficacy measure index, and to each effect
The different degree of energy Measure Indexes is normalized, and obtains the weight of each efficacy measure index.Each efficacy measure index
The sum of weight be 1.
Step S402: the simulation parameter of each basal evaluation index of dynamic acquisition.
Being deduced and tested due to emulation is real-time perfoming, it is possible to each basal evaluation at dynamic acquisition each moment
The simulation parameter of index, as parameter needed for constructing initial hypermatrix.
Step S403: if the emulation of the simulation parameter of a certain basal evaluation index and corresponding basal evaluation index is joined
Belong to linear relationship between number, then calculates the weight of corresponding basal evaluation index using least square method, it is corresponding
Basal evaluation index be there are the basal evaluation indexs of incidence relation with a certain basal evaluation index.
Assuming that a certain basal evaluation index y and one group of basal evaluation index A=(a1, a2..., an) there are incidence relations, and
Belong to linear relationship between simulation parameter, wherein aiFor i-th of basal evaluation index, Aj(j=1,2 ..., n) is the jth moment
Simulation parameter value establishes the fit correlation regression model between each index simulation parameter value using least square methodN basal evaluation index is acquired to a certain basal evaluation index y according to simulation parameter value
Influence coefficient vector B=[b1, b2..., bn]T, these influence coefficients are compared two-by-two, it is available by relative Link Importance
Judgment matrix C=(the b of compositioni/bj)n×n=(cij)n×n.By being finely adjusted to judgment matrix, complies with index judgement and want
It asks.The weight of n basal evaluation index can be calculated in judgment matrix by adjusting after, and weight is substituted into initial super square
Battle array.
Step S404: if the emulation of the simulation parameter of a certain basal evaluation index and corresponding basal evaluation index is joined
Belong to non-linear relation between number, then corresponding basal evaluation index is calculated using preset deep neural network model
Weight.
Assuming that a certain basal evaluation index y and one group of basal evaluation index A=(a1, a2..., an) there are incidence relations, and
Belong to non-linear relation between simulation parameter, then calculates n basal evaluation index using preset deep neural network model
Weight.
Seen from the above description, the embodiment of the present invention passes through the simulation parameter of each basal evaluation index of dynamic acquisition, adopts
The weight of each basal evaluation index is calculated with least square method or deep neural network model, can excavate each index with depth
Between relevance.
It should be understood that the size of the serial number of each step is not meant that the order of the execution order in above-described embodiment, each process
Execution sequence should be determined by its function and internal logic, the implementation process without coping with the embodiment of the present invention constitutes any limit
It is fixed.
Fig. 5 is that the schematic block diagram for the index system establishment system that one embodiment of the invention provides only shows for ease of description
Part related to the embodiment of the present invention out.
In embodiments of the present invention, These parameters system construction system 5 may include:
Data acquisition module 51 is emulated, for obtaining the emulation data emulated to Weapon Equipment System, and it is right
It emulates data and carries out data prediction；
Model construction module 52 constructs the super net of weighting of Weapon Equipment System for being based on pretreated emulation data
Model；
Index system establishment module 53, for based on the measures of effectiveness for weighting super pessimistic concurrency control and preset Weapon Equipment System
Target constructs the index system that measures of effectiveness is carried out to Weapon Equipment System.
Optionally, model construction module 52 may include:
Node establishes unit, for analyzing pretreated emulation data, according to the foundation pair of the function of military simulation entity
The super net node of the weighting answered, and the super net node of the weighting of foundation is included into corresponding node set；
Unit is established on functional network side, for analyzing the information flow of Weapon Equipment System, is connected according to information flow corresponding
Super net node is weighted, establishes the functional network side of functional network, and calculate the weight on each functional network side；
Unit is established on dependence side, the dependence side for establishing between functional network, and dependence side is arranged
Weight.
Optionally, These parameters system construction system 5 can also include:
Model modification module, for updating and weighting super pessimistic concurrency control based on the emulation data obtained in real time.
Optionally, index system establishment module 53 may include:
Index system structure determination unit determines the structure of index system for being based on measures of effectiveness target；
Reference model selecting unit selects reference model for the structure according to index system；
First index determination unit, for determining efficacy measure index according to reference model；
Second index determination unit, for determining basal evaluation index according to super pessimistic concurrency control is weighted；
Association analysis unit, for each being associated property of index in efficacy measure index and basal evaluation index
Analysis, determines the incidence relation between each index；
Index system determination unit, for according to the pass between efficacy measure index, basal evaluation index and each index
Connection relationship determines index system.
Optionally, index system establishment module 53 can also include:
First weight calculation unit, for calculating the weight of each efficacy measure index；
Simulation parameter acquiring unit, the simulation parameter for each basal evaluation index of dynamic acquisition；
Second weight calculation unit, if simulation parameter and corresponding basal evaluation for a certain basal evaluation index
Belong to linear relationship between the simulation parameter of index, then calculates the power of corresponding basal evaluation index using least square method
Weight, corresponding basal evaluation index are that there are the basal evaluation indexs of incidence relation with a certain basal evaluation index；
Third weight calculation unit, if simulation parameter and corresponding basal evaluation for a certain basal evaluation index
Belong to non-linear relation between the simulation parameter of index, then corresponding base is calculated using preset deep neural network model
The weight of plinth evaluation index.
It is apparent to those skilled in the art that for convenience of description and succinctly, only with above-mentioned each function
Can unit, module division progress for example, in practical application, can according to need and by above-mentioned function distribution by different
Functional unit, module are completed, i.e., the internal structure of the index system establishment system is divided into different functional unit or mould
Block, to complete all or part of the functions described above.Each functional unit in embodiment, module can integrate at one
It manages in unit, is also possible to each unit and physically exists alone, can also be integrated in one unit with two or more units
In, above-mentioned integrated unit both can take the form of hardware realization, can also realize in the form of software functional units.Separately
Outside, each functional unit, module specific name be also only for convenience of distinguishing each other, the protection model being not intended to limit this application
It encloses.The specific work process of unit in above-mentioned apparatus, module, can refer to corresponding processes in the foregoing method embodiment, herein
It repeats no more.
Fig. 6 is the schematic block diagram for the terminal device that one embodiment of the invention provides.As shown in fig. 6, the terminal of the embodiment
Equipment 6 includes: one or more processors 60, memory 61 and is stored in the memory 61 and can be in the processor
The computer program 62 run on 60.The processor 60 realizes above-mentioned each index system when executing the computer program 62
Step in construction method embodiment, such as step S101 to S103 shown in FIG. 1.Alternatively, the processor 60 execute it is described
The function of each module/unit in These parameters system construction system embodiment, such as mould shown in Fig. 5 are realized when computer program 62
The function of block 51 to 53.
Illustratively, the computer program 62 can be divided into one or more module/units, it is one or
Multiple module/units are stored in the memory 61, and are executed by the processor 60, to complete the application.Described one
A or multiple module/units can be the series of computation machine program instruction section that can complete specific function, which is used for
Implementation procedure of the computer program 62 in the terminal device 6 is described.For example, the computer program 62 can be divided
It is as follows to be cut into emulation data acquisition module, model construction module and index system establishment module, the concrete function of modules:
Data acquisition module is emulated, for obtaining the emulation data emulated to Weapon Equipment System, and to imitative
True data carries out data prediction；
Model construction module constructs the super net mould of weighting of Weapon Equipment System for being based on pretreated emulation data
Type；
Index system establishment module, for the measures of effectiveness mesh based on weighting super pessimistic concurrency control and preset Weapon Equipment System
Mark constructs the index system that measures of effectiveness is carried out to Weapon Equipment System.
Other modules or unit can refer to the description in embodiment shown in fig. 5, and details are not described herein.
The terminal device 6 can be mobile phone, tablet computer, notebook etc. and calculate equipment.The terminal device 6 include but
It is not limited only to processor 60, memory 61.It will be understood by those skilled in the art that Fig. 6 is only an example of terminal device,
The restriction to terminal device 6 is not constituted, may include components more more or fewer than diagram, or combine certain components, or
The different component of person, such as the terminal device 6 can also include input equipment, output equipment, network access equipment, bus
Deng.
The processor 60 can be central processing unit (Central Processing Unit, CPU), can also be
Other general processors, digital signal processor (Digital Signal Processor, DSP), specific integrated circuit
(Application Specific Integrated Circuit, ASIC), field programmable gate array (Field-
Programmable Gate Array, FPGA) either other programmable logic device, discrete gate or transistor logic,
Discrete hardware components etc..General processor can be microprocessor or the processor is also possible to any conventional processor
Deng.
The memory 61 can be the internal storage unit of the terminal device, such as the hard disk or interior of terminal device
It deposits.What the memory 61 was also possible to be equipped on the External memory equipment of the terminal device, such as the terminal device inserts
Connect formula hard disk, intelligent memory card (Smart Media Card, SMC), secure digital (Secure Digital, SD) card, flash memory
Block (Flash Card) etc..Further, the memory 61 can also both include the internal storage unit of terminal device or wrap
Include External memory equipment.The memory 61 is for storing needed for the computer program 62 and the terminal device other
Program and data.The memory 61 can be also used for temporarily storing the data that has exported or will export.
In the above-described embodiments, it all emphasizes particularly on different fields to the description of each embodiment, is not described in detail or remembers in some embodiment
The part of load may refer to the associated description of other embodiments.
Those of ordinary skill in the art may be aware that list described in conjunction with the examples disclosed in the embodiments of the present disclosure
Member and algorithm steps can be realized with the combination of electronic hardware or computer software and electronic hardware.These functions are actually
It is implemented in hardware or software, the specific application and design constraint depending on technical solution.Professional technician
Each specific application can be used different methods to achieve the described function, but this realization is it is not considered that exceed
Scope of the present application.
In embodiment provided herein, it should be understood that disclosed index system establishment system and method, it can
To realize by another way.For example, index system establishment system embodiment described above is only schematical, example
Such as, the division of the module or unit, only a kind of logical function partition, can there is other division side in actual implementation
Formula, such as multiple units or components can be combined or can be integrated into another system, or some features can be ignored, or not
It executes.Another point, shown or discussed mutual coupling or direct-coupling or communication connection can be to be connect by some
Mouthful, the INDIRECT COUPLING or communication connection of device or unit can be electrical property, mechanical or other forms.
The unit as illustrated by the separation member may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, it can and it is in one place, or may be distributed over multiple
In network unit.It can select some or all of unit therein according to the actual needs to realize the mesh of this embodiment scheme
's.
It, can also be in addition, each functional unit in each embodiment of the application can integrate in one processing unit
It is that each unit physically exists alone, can also be integrated in one unit with two or more units.Above-mentioned integrated list
Member both can take the form of hardware realization, can also realize in the form of software functional units.
If the integrated module/unit be realized in the form of SFU software functional unit and as independent product sale or
In use, can store in a computer readable storage medium.Based on this understanding, the application realizes above-mentioned implementation
All or part of the process in example method, can also instruct relevant hardware to complete, the meter by computer program
Calculation machine program can be stored in a computer readable storage medium, the computer program when being executed by processor, it can be achieved that on
The step of stating each embodiment of the method.Wherein, the computer program includes computer program code, the computer program generation
Code can be source code form, object identification code form, executable file or certain intermediate forms etc..The computer-readable medium
It may include: any entity or device, recording medium, USB flash disk, mobile hard disk, magnetic that can carry the computer program code
Dish, CD, computer storage, read-only memory (ROM, Read-Only Memory), random access memory (RAM,
Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium etc..It should be noted that described
The content that computer-readable medium includes can carry out increasing appropriate according to the requirement made laws in jurisdiction with patent practice
Subtract, such as in certain jurisdictions, according to legislation and patent practice, computer-readable medium do not include be electric carrier signal and
Telecommunication signal.
Embodiment described above is only to illustrate the technical solution of the application, rather than its limitations；Although referring to aforementioned reality
Example is applied the application is described in detail, those skilled in the art should understand that: it still can be to aforementioned each
Technical solution documented by embodiment is modified or equivalent replacement of some of the technical features；And these are modified
Or replacement, the spirit and scope of each embodiment technical solution of the application that it does not separate the essence of the corresponding technical solution should all
Comprising within the scope of protection of this application.
Claims (10)
1. a kind of index system construction method characterized by comprising
The emulation data emulated to Weapon Equipment System are obtained, and data prediction is carried out to the emulation data；
Based on pretreated emulation data, the super pessimistic concurrency control of weighting of the Weapon Equipment System is constructed；
Based on the measures of effectiveness target of the weighting super pessimistic concurrency control and the preset Weapon Equipment System, construct to the weapon
The index system of equipment architecture progress measures of effectiveness.
2. index system construction method according to claim 1, which is characterized in that described to be based on pretreated emulation number
According to constructing the super pessimistic concurrency control of weighting of the Weapon Equipment System, comprising:
The pretreated emulation data are analyzed, the corresponding super net node of weighting is established according to the function of military simulation entity,
And the super net node of the weighting of foundation is included into corresponding node set；
The information flow for analyzing the Weapon Equipment System establishes function according to the corresponding super net node of weighting of information flow connection
The functional network side of energy network, and calculate the weight on each functional network side；
The dependence side between functional network is established, and the weight on the dependence side is set.
3. index system construction method according to claim 1, which is characterized in that be based on pretreated emulation described
Data, after the super pessimistic concurrency control of weighting for constructing the Weapon Equipment System, the method also includes:
Based on the emulation data obtained in real time, the super pessimistic concurrency control of weighting is updated.
4. index system construction method according to claim 1, which is characterized in that described based on the super pessimistic concurrency control of weighting
With the measures of effectiveness target of the preset Weapon Equipment System, the finger that measures of effectiveness is carried out to the Weapon Equipment System is constructed
Mark system, comprising:
Based on the measures of effectiveness target, the structure of the index system is determined；
According to the structure of the index system, reference model is selected；
According to the reference model, efficacy measure index is determined；
According to the super pessimistic concurrency control of weighting, basal evaluation index is determined；
To each being associated property of index analysis in the efficacy measure index and the basal evaluation index, determine described each
Incidence relation between a index；
According to the incidence relation determination between the efficacy measure index, the basal evaluation index and each index
Index system.
5. index system construction method according to claim 4, which is characterized in that described to the efficacy measure index
With each being associated property of index analysis in the basal evaluation index, determine incidence relation between each index it
Afterwards, the method also includes:
Calculate the weight of each efficacy measure index；
The simulation parameter of each basal evaluation index of dynamic acquisition；
If belonging to line between the simulation parameter of a certain basal evaluation index and the simulation parameter of corresponding basal evaluation index
Sexual intercourse then calculates the weight of the corresponding basal evaluation index, the corresponding base using least square method
Plinth evaluation index is that there are the basal evaluation indexs of incidence relation with a certain basal evaluation index；
If belonging between the simulation parameter of a certain basal evaluation index and the simulation parameter of corresponding basal evaluation index non-
Linear relationship then calculates the weight of the corresponding basal evaluation index using preset deep neural network model.
6. a kind of index system establishment system characterized by comprising
Data acquisition module is emulated, for obtaining the emulation data emulated to Weapon Equipment System, and to described imitative
True data carries out data prediction；
Model construction module constructs the super net mould of weighting of the Weapon Equipment System for being based on pretreated emulation data
Type；
Index system establishment module is commented for the efficiency based on the super pessimistic concurrency control of the weighting and the preset Weapon Equipment System
Estimate target, constructs the index system for carrying out measures of effectiveness to the Weapon Equipment System.
7. index system establishment system according to claim 6, which is characterized in that the model construction module includes:
Node establishes unit, for analyzing the pretreated emulation data, according to the foundation pair of the function of military simulation entity
The super net node of the weighting answered, and the super net node of the weighting of foundation is included into corresponding node set；
Unit is established on functional network side, for analyzing the information flow of the Weapon Equipment System, according to information flow connection pair
The super net node of the weighting answered, establishes the functional network side of functional network, and calculates the weight on each functional network side；
Unit is established on dependence side, the dependence side for establishing between functional network, and the dependence side is arranged
Weight.
8. index system establishment system according to claim 6, which is characterized in that the system also includes:
Model modification module, for updating the super pessimistic concurrency control of weighting based on the emulation data obtained in real time.
9. a kind of terminal device, including memory, processor and storage are in the memory and can be on the processor
The computer program of operation, which is characterized in that the processor realizes such as claim 1 to 5 when executing the computer program
The step of any one index system construction method.
10. a kind of computer readable storage medium, which is characterized in that the computer-readable recording medium storage has computer journey
Sequence realizes the index system as described in any one of claim 1 to 5 when the computer program is executed by one or more processors
The step of construction method.
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| CN110705873A (en) * | 2019-09-30 | 2020-01-17 | 国网福建省电力有限公司 | Novel power distribution network operation state portrait analysis method |
| CN111047178A (en) * | 2019-12-06 | 2020-04-21 | 上海机电工程研究所 | Weapon system performance index screening method and system based on grey correlation |
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Application publication date: 20190730 |