CN108647414A - Operation plan adaptability analysis method based on emulation experiment and storage medium - Google Patents
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Abstract
Operation plan adaptability analysis method based on emulation experiment and its storage medium, the method includes, Military Scenario, both sides at war's battle plan and the battlefield event provided according to outside, form the Math scenario of analogue system identification, simulation scenario element is obtained, the extraction experiment factor in simulation scenario element extracts experimental point for each experiment factor, simulation scenario space is run, analyzes and excavates emulation experiment.Therefore, the present invention utilizes exploratory simulation experiment, the dynamic interaction between confrontation both sides' system inside and the confrontation between system are fully considered, pass through the emulation experiment of large sample, constantly screening, adjustment and amendment experimental program, and various possible results are verified, deeply understand various key elements comprehensively, the various abilities and strategy of corresponding task demand can be completed by exploring, seek satisfactory solution and follow-up Adjusted Option, to hold influence of the various uncertain factors for system combat plan comprehensively.
Description
Technical field
The present invention relates to simulation analysis fields, specifically, relate to the use of emulation experiment carries out adaptability point to operation plan
The method and storage medium of analysis.
Background technology
Operation under Information Condition, especially system combat, for example, maritime formation system combat, exist it is a large amount of not
Certainty factor, such as information, naval battle field environment, enemy's action, interrelated between these factors, each factor and war knot
Relationship between fruit is also unclear, and traditional method is difficult to meet the needs of all kinds of system combat planning analysis researchs.
For the scope of exploratory analysis, exploratory analysis can be divided into exploration according to the difference of used means
Property analytical analysis, exploratory simulation analysis；For the scope of emulation experiment, emulation experiment according to experiment purpose, using method
Difference, randomness emulation mode, deterministic simulation method, exploratory emulation mode can be divided into.Come from the angle of methodology
It says, exploratory simulation experiment method is both a kind of Exploratory analysis methodology, while being also a kind of emulation experiment method, and being will be not true
Exploratory analysis methodology under fixed condition is combined with computer simulation experiment method, seeks and find the one of complication system rule
The new analysis experimental method of kind.
Therefore, how to be divided there are a large amount of probabilistic system combats using the simulation analysis of exploration
Analysis, obtains the key factor for influencing war overall goals, and assurance holds various uncertain factors for system combat comprehensively
The technical issues of influencing, becoming prior art urgent need to resolve.
Invention content
The purpose of the present invention is obtaining the method for carrying out Adaptability Analysis to system combat based on exploratory simulation experiment, from
And all kinds of key elements in system combat can be investigated comprehensively, the various abilities and strategy for completing corresponding task demand are explored,
Seek satisfactory solution and follow-up Adjusted Option.
For this purpose, the present invention uses following technical scheme：
A kind of operation plan adaptability analysis method based on emulation experiment, includes the following steps：
Math scenario generation step S110：According to outside provide Military Scenario, both sides at war's battle plan and
Battlefield event forms the Math scenario of analogue system identification, and the Military Scenario includes battlefield Initial situation, red blue party soldier
Power, belligerent action and battlefield surroundings；
Simulation scenario element obtaining step S120:After Math scenario generates and is stored in database according to format, from
Environment, task, ability and actionable space four directions are analyzed in face of Math scenario, extract simulation scenario element, and determine
Its value；
Test the factor and experimental point selection step S130:The extraction experiment factor in simulation scenario element, for each reality
Test factor extraction experimental point so that experimental point is evenly distributed in as possible in entire multi-dimensional data space；
Simulation scenario space motion step S140：Permutation and combination and sieve are carried out to the experiment factor and experimental point extracted
Choosing forms simulation scenario space, and runs simulation scenario based on the numerical value in simulation scenario space；
Analysis of simulation experiment step S150:Including simulation result statistical analysis sub-step：
It is for statistical analysis to the simulation experiment result from different perspectives by various statistical analysis means, it analyzes emulation and thinks
Various simulation scenario elements refer to experiment the sensitivity of different experiments index and the simulation scenario element value in fixed
Target influence degree.
Optionally, in the Math scenario generation step S110, can single run Math scenario, according to
Single operation as a result, found out present in Math scenario by military specialist and object of experiment content there are deviations, or
The problem not being inconsistent etc. with object of experiment level, and Math scenario is adjusted.
Optionally, in the simulation scenario element obtaining step, simulation scenario element includes：Operational environment class, entity
Task class, physical capabilities class and entity action classes element include more seed elements again per class simulation scenario element：
(1) operational environment class element includes：Geographical environment, marine environment, atmospheric environment and electromagnetic environment；
(2) entity task class element includes：The combat duty of various entities and aggregate entities；
(3) physical capabilities class element includes：Entity self-ability element and carrying equipment capability element, self-ability element
Including entity controllable velocity, combat radius, RCS characteristics, it includes carrying guided missile maximum effective range, taking to carry equipment capability element
Carry radar coverage；
(4) entity action classes element includes：Entity plan of maneuver, standby area and beat.
Optionally, in the experiment factor and experimental point selection step, the design selection of experimental point should balance required reality
The time complexity for testing information and control experiment finds in experimental design stage and experiment operation phase and gives up nothing as far as possible
Or the experimental point that information content is less.
Optionally, the common experiment factor includes the operation entity for participating in emulation, operation physical quantities, operation entity carry
Weapon type, quantity and range detection sensor.
Optionally, in simulation scenario space motion step, the numerical value operation emulation in the space based on simulation scenario
Scenario is to adjust the relevant parameter of Math scenario based on the numerical value in simulation scenario space, and run the Math and think
It is fixed.
Optionally, the analysis of simulation experiment step further includes that simulation result excavates sub-step：
On the basis of simulation result statistical analysis, data mining is carried out to experimental data, according to the result of data mining
It returns to the experiment factor and experimental point selects step, if failing to obtain the interested laws of war, feed back to single emulation and think
Surely it generates ring and further adjusts the content and level of simulation scenario and pass through if having analyzed the laws of war of interest
Analysis is further amplified or reduced to crucial subspace.
Optionally, for simulation result statistical analysis sub-step, the experiment factor can also be returned according to statistic analysis result
And experimental point select step S130, in simulation scenario space motion ring simulation scenario element and its value be adjusted, weight
It is new to choose simulation scenario element and determine its value, operation simulation scenario space.
Optionally, the analysis of simulation experiment step further includes that simulation result excavates sub-step：
According to emulation experiment process, by experiment purpose, experiment scenario, experimental design, experiment statistics analysis result, experiment number
Laboratory report is formed according to certain format according to mining analysis result, and/or the decision information of people is attached to as experiment conclusion
In laboratory report.
The invention also discloses a kind of storage mediums, and for storing computer executable instructions, the computer is executable
Instruction executes the operation plan adaptability analysis method based on emulation experiment when being executed by processor.
Therefore, the present invention utilizes exploratory simulation experiment, has fully considered that the dynamic between confrontation both sides' system inside is handed over
Confrontation between mutual and system, analyzes system combat plan using exploratory simulation experiment technology, passes through large sample
Emulation experiment, constantly screening, adjustment and amendment experimental program, and various possible results are verified, deeply understand comprehensively
Various key elements explore the various abilities and strategy that can complete corresponding task demand, seek satisfactory solution and follow-up adjustment
Scheme, operation process and final result under the conditions of investigation is various, gos deep into cognitive system law of operation, various not true to hold comprehensively
Influence of the qualitative factor for system combat plan.
Description of the drawings
Fig. 1 is the theoretical frame figure of the exploratory simulation experiment of system combat according to the present invention；
Fig. 2 is the stream of the operation plan adaptability analysis method based on emulation experiment according to a particular embodiment of the invention
Cheng Tu；
Fig. 3 is the element relationship figure of the operation plan Adaptability Analysis of another specific embodiment according to the present invention.
Specific implementation mode
The present invention is described in further detail with reference to the accompanying drawings and examples.It is understood that this place is retouched
The specific embodiment stated is used only for explaining the present invention rather than limitation of the invention.It also should be noted that in order to just
Only the parts related to the present invention are shown in description, attached drawing rather than entire infrastructure.
The exploratory simulation experiment theory of system combat can be in terms of object of experiment, experiment model and experimental system three
It is described, as shown in Figure 1, the purpose of experiment is for decision, the experiment based on decision is divided into optimizing, seeks and need to and seek rule three
Kind.Optimizing is solution the problem of finding a relatively optimization by the method for emulation experiment；Seeking need to be by emulation experiment
Method finds the target feasible set for meeting demand；It is to find system inherent law, auxiliary by emulation experiment means to seek rule
Commander's assimilated equations solving practical problems.Experiment model refers to experimental design pattern, for both ends type, discrete type and continuous type
2k experiment models, Nk experiment models and Lk experiment models is respectively adopted in three classes experimental subjects.Experimental system is mainly set including model
Count module, scenario editor module, experimental design module, simulation run module, data analysis module.
Based on above-mentioned theory, in conjunction with the characteristics of operation and factor, as shown in Fig. 2, the work based on emulation experiment of the present invention
War plan adaptability analysis method includes the following steps：
Math scenario generation step S110：
The step is the basic steps of exploratory simulation experiment implementation process, is the base for being subsequently generated simulation scenario space
Plinth is the initial setting carried out to initial situation of battlefield, both sides at war's operation etc. according to the requirement of emulation, above-mentioned initial
Setting includes Military Scenario, both sides at war's battle plan and battlefield event.
The content of the step is specially：Military Scenario, both sides at war's battle plan and the battlefield thing provided according to outside
Part, forms the Math scenario of analogue system identification, and the Military Scenario includes battlefield Initial situation, red blue party troops, hands over
The contents such as war action, battlefield surroundings are the follow-up basic scenarios for carrying out exploratory simulation experiment.
Further, in the Math scenario generation step S110, can single run Math scenario, root
According to single operation as a result, found out present in Math scenario by military specialist and object of experiment content there are deviations, or
The problem that person and object of experiment level are not inconsistent etc., and Math scenario is adjusted.
Simulation scenario element obtaining step S120:
Math scenario each element influential on the result of analysis is analyzed to obtain simulation scenario element, is sought to
The all possible variable in exploratory simulation experiment is obtained, for the choice experiment factor in subsequent experiment, for carrying out
Analytical experiment.
This step is specially：After Math scenario generates and is stored in database according to format, from environment, task, energy
Power and actionable space four directions are analyzed in face of Math scenario, extract simulation scenario element, true according to the data grasped
Its fixed value.With in simulation scenario space environment, task, ability and actionable space it is corresponding, simulation scenario element is mainly wrapped
Include four classes：Operational environment class, entity task class, physical capabilities class and entity action classes element are wrapped again per class simulation scenario element
Include more seed elements：
(1) operational environment class element includes：Geographical environment, marine environment, atmospheric environment, electromagnetic environment；
(2) entity task class element includes：The combat duty of various entities and aggregate entities, for example, it is air-defense anti-missile, aerial
Go on patrol, combine it is antisubmarine, to sea strike etc.；
(3) physical capabilities class element includes：Entity self-ability element and carrying equipment capability element, self-ability element
Such as entity controllable velocity, combat radius, RCS characteristics；Equipment capability element is carried as carried guided missile maximum effective range, carrying
Radar coverage etc.；
(4) entity action classes element includes：Entity plan of maneuver, standby area, beat etc..
Therefore, simulation scenario element is extracted, simulation scenario collection is exactly further converted to the number that computer can identify
It is believed that breath, the combat duty undertaken by the weaponry to present, following we and potential fight opponents, operational performance and
The research and prediction of its possible operational mode determine the value of simulation scenario element according to the content of following three aspect：Foundation
Study on Problems needs, and according to simulation scenario element property, had design conditions are tested according to carrying out.
A. " needs according to Study on Problems " seek to surround object of experiment, its number can be controlled to the value of certain elements
Amount, and by technologies such as sensitivity analysis, variance analyses come the preliminary susceptibility for judging element and its value.After analysis,
If it find that some element is not very sensitive, experiment is not also eliminated easily, because war complex system has
There are nonlinear feature, various elements that may all generate certain effect to the result of campaign or fight, " buterfly effect " is fighting
It strives commonplace in history.
B. it seeks to according to element be discrete or continuous variable, there is monotonicity " according to simulation scenario element property "
Or it is non-monotonic, the value of simulation scenario element is determined using suitable strategy.For example, the part in entity action classes element is wanted
Element is continuous, and partial element is discrete, just needs to distinguish when determining value.Such as the position of the standby point of naval vessels be exactly from
Value is dissipated, and aircraft patrol altitude is then successive value or meets the functional expression of certain probability distribution.
C. " had design conditions are tested according to carrying out " and seeks to adaptation to local conditions, to implement exploratory simulation experiment
Based on soft and hardware condition, feasibility, economy that experiment is implemented are considered while pursuing element value density and coverage rate
And the timeliness of experimental result.
Test the factor and experimental point selection step S130:
When studying new warfighting concepts, need to consider that a large amount of factors, each factor need to consider multiple values again, this
It is a higher-dimension, huge space objectively to cause simulation scenario space.Simulation scenario element obtaining step S120 is obtained
The simulation scenario element of operational environment class, entity task class, four classes of physical capabilities class and entity action classes element is emulated per class
Scenario element includes more seed elements again.Since simulation scenario element is the expansion to the experimental point concept in traditional experiment field
Exhibition, therefore, it is necessary to, to design operational experiments analysis, use experimental design techniques pair by the selection to above-mentioned simulation scenario element
It is planned in simulation scenario space.
This step is specially：The extraction experiment factor in simulation scenario element, experimental point is extracted for each experiment factor,
So that experimental point is evenly distributed in as possible in entire multi-dimensional data space.
The time complexity that should balance required experiment information and control experiment is chosen in the design of experimental point, is set in experiment
Meter stage and experiment operation phase find and give up useless or less information content experimental point as far as possible.Traditional experiment
Designing technique has orthogonal, Latin square experimental design, uniform test design etc., and the experimental design techniques occurred recently have
Center Mixed Design, nearly orthogonal super Latin―Square design etc..Above-mentioned experimental design method be mathematically strictly to space into
Row sampling.The applicable data of different experimental design methods are different, such as Latin square method is primarily adapted for use in monotonicity
Data.
The common experiment factor selected in the present invention include the operation entity for participating in emulating, operation physical quantities,
Operation entity carry weapon type, quantity and range detection sensor.
Simulation scenario space motion step S140：
Specially：Permutation and combination and screening are carried out to the experiment factor and experimental point extracted, form simulation scenario space,
And simulation scenario is run based on the numerical value in simulation scenario space.
Simulation scenario space includes empirical factor selected in simulation scenario element, each of simulation scenario space
Point is all a multi-C vector, corresponding one group of variable-value, and each point can be independent in simulation based agent analytic process
Operation.
Further, the numerical value operation simulation scenario in the space based on simulation scenario is based in simulation scenario space
Numerical value, adjust the relevant parameter of Math scenario, and run the Math scenario.
I.e. using Math scenario as the template of simulation scenario, the parameter of Math scenario is adjusted before each run,
Multiple and different simulation scenarios is set to reduce, convenient for rule is found and obtained from simulation scenario, improves the efficiency of emulation
And effect.
Analysis of simulation experiment step S150:
Decision cannot be directly used to for the result of analysis of simulation experiment, in most cases emulation experiment output, need
By data analysis and excavation, the data information for decision can be just obtained.Analysis of simulation experiment includes basic simulation result
Statistical analysis and further emulation data mining, ultimately generate emulation experiment report.
Simulation result statistical analysis sub-step：
It is for statistical analysis to the simulation experiment result from different perspectives by various statistical analysis means, it analyzes emulation and thinks
Various simulation scenario elements refer to experiment the sensitivity of different experiments index and the simulation scenario element value in fixed
Target influence degree.
Further, the experiment factor can also be returned to according to statistic analysis result and experimental point selects step S130, to imitative
Simulation scenario element and its value in true scenario space motion ring are adjusted, and are chosen simulation scenario element again and are determined it
Value, operation simulation scenario space.
Simulation result statistical analysis refers to being counted, being handled to Simulation result data using the method for mathematical statistics, divided
Analysis, such as：Regression analysis, variance analysis, sensitivity analysis, Threshold Analysis, key element analysis, meta-model analysis etc..According to number
Reason counts the different characteristics of various methods, and distinct methods can be used and analyze the following contents：1. single experiment data statistics,
2. many experiments data statistics, multiple more in input simulation scenario space 3. on the basis of many experiments data statistics result
When dimension strong point, statistical disposition is carried out to result data, includes mainly variance analysis, regression analysis etc..
Simulation result excavates sub-step：
Data mining can find to contribute to the knowledge of decision from mass data.It is emulated using the technology investigative analysis real
The process and result data tested, to find the rule implied in war in mass data.Available data digging technology has god
Through network, decision tree, correlation rule, fuzzy clustering, support vector machines, rough set, isolated point, Bayesian network etc., each digging
Pick technology has different purposes.Such as the regression tree analysis in decision tree, it is exactly a kind of to classify to data, it is closed to reduce
Note the better method of range.
The sub-step is specially：On the basis of simulation result statistical analysis, data mining is carried out to experimental data, according to
The result of data mining returns to the experiment factor and experimental point selects step S130, if failing to obtain the interested laws of war,
It then feeds back to single simulation scenario and generates content and level that ring further adjusts simulation scenario, such as the adjustment patterns of warfare or work
War level；If having analyzed the laws of war of interest, by the way that analysis is further amplified or reduced to crucial subspace,
And policymaker is showed to supply its decision by visual form its analysis result.
That is emulation data mining is established on the basis of simulation result statistical analysis, by the preliminary treatment of statistical analysis to reality
It tests data and is formed by the direction that intuitive judgment can be used as data mining so that data mining has better directionality, stronger
Specific aim.
Finally, further include the generation sub-step of laboratory report in analysis of simulation experiment step S150：According to emulation experiment
Process, by experiment purpose, experiment scenario, experimental design, experiment statistics analysis result, experimental data mining analysis result according to one
Fixed format forms laboratory report, or the decision information of people is attached to as experiment conclusion in laboratory report, the experiment report
Announcement is the conclusion and summary to entirely testing.
Referring to Fig. 3, the element relationship figure of operation plan Adaptability Analysis according to the present invention is shown, it is of the invention
Five steps, can be divided into the generation of simulation scenario, scenario space motion, three parts such as analysis of simulation experiment, each section it
Between influence intersected with each other, can be according to the dynamic regulation experiment factor of result and valued space of experimental analysis, being capable of basis
Numerical value after adjustment adjusts simulation scenario model, and operation obtains its concrete outcome, and further carries out the analysis of experimental result,
Until obtaining desired result.
The present invention further discloses a kind of storage mediums, for storing computer executable instructions, it is characterised in that：
The computer executable instructions execute the above-mentioned operation plan based on emulation experiment when being executed by processor
Adaptability analysis method.
Embodiment-system combat case study：
(1) operation problem：
Build the simulated environment of command relation, command flow path, information exchange etc. between each node of naval's XX systems, formed from
The emulation experiment closed loop that modelling, scenario editor, simulation run, synthesis display are assessed to analysis is studied with this in XX operations
Command and control Efficacy Problem based on information system.
(2) Combat scenario
Enemy sends each two framves of A1 and A2, amounts to four sortie opportunities of combat and carries out low latitude surprise attack, wherein A1-1 to our M command posts
Be responsible for shielding, carry the absolutely empty bullet of 2 pieces of Type Bs and 2 pieces of absolutely empty bullets of c-type, A1-2 carry 2 pieces of D types vacant lot bullets attempt to my M command posts into
Row strike.
The operation entity that we is related to has J-type early warning plane, K-type fighter plane, the air-ground transmitting battle array of L-type and p-type surface-to-air ballistic missile to refer to
Wave vehicle, the closely anti-system transmitting battle array of Q types and command car, the centers S.
After detection information is reported to the centers S by our J-type early warning plane by respective communication link, number will be detected by the centers S
According to being distributed to, K-type fighter plane, L-type are air-ground to launch a guided missile and the closely anti-system of Q types.
(3) model system
According to troops and weaponry situation between ourselves and the enemy in Combat scenario, Simulation Application model system is built.Main packet
Two class of component model and physical model is included, wherein component model includes motor-driven component, sensor module, communication component, weapon system
System component, anti-warship guided missle component, weapon rule components, behavior component etc., physical model include that troops' physical model and weapon are real
Body Model, physical model are assembled by component model, after design parameter is set, generate the physical model of concrete model
(such as so-and-so type guided missile destroyer).
(4) experimental design and interpretation of result
To available troops J-type early warning plane, K-type fighter plane, p-type surface-to-air ballistic missile and the closely anti-four type troops of system (ABCD) of Q types
Carry out comprehensive analysis design, J-type early warning plane setting two states (just do not guard against in air-borne early warning 1 and in the air 0), K-type fighting
Machine setting two states (air patrol wait for fight 1 and base await orders 0), the closely anti-system of p-type surface-to-air ballistic missile, Q types, XX and base are awaited orders
K-type fighter plane set three kinds of operation grades (level-one, two level, three-level) altogether, obtain 9 battle plan scenarios, respectively indicate be
A0B0ICIDI, A0B0IICIIDII, A0B0IIICIIIDIII, A1B0ICIDI, A1B0IICIIDII,
A1B0IIICIIIDIII, A1B1ICIDI, A1B1ICIIDII, A1B1ICIIIDIII, the results are shown in Table 1.
1 first round of table simulation result statistical form
Therefore, the present invention utilizes exploratory simulation experiment, emphasizes to count rather than just parsing using computer simulation experiment
Calculation carries out exploration solution, the dynamic interaction between confrontation both sides' system inside and the confrontation between system has been fully considered, to body
The whole emergence rule of system has carried out deeper exploration, and can be visited by the operation control strategy of emulation experiment to improve
Rope efficiency.Using exploratory analysis strategy rather than single case analysis or sensibility partial analysis strategy are real to instruct to emulate
It tests, the uncertain factors such as various scenario backgrounds, various ability schemes has been fully considered, by being dug from magnanimity experimental data
It digs rather than simply compares, obtain and the relevant critical capability demand of war overall goals.
System combat plan is analyzed using exploratory simulation experiment technology, by the emulation experiment of large sample, no
Disconnected screening, adjustment and amendment experimental program, and various possible results are verified, various be critical to deeply is understood comprehensively
Element explores the various abilities and strategy that can complete corresponding task demand, seeks satisfactory solution and follow-up Adjusted Option, investigate each
Operation process and final result under the conditions of kind, go deep into cognitive system law of operation, to hold various uncertain factors pair comprehensively
In the influence of system combat plan.
Obviously, it will be understood by those skilled in the art that each unit or each step of the above-mentioned present invention can be with general
Computing device realizes that they can concentrate on single computing device, and optionally, they can be executable with computer installation
Program code realize, be performed by computing device so as to be stored in storage device, or by they point
Be not fabricated to each integrated circuit modules, or by them multiple modules or step be fabricated to single integrated circuit module
It realizes.In this way, the present invention is not limited to the combinations of any specific hardware and software.
The above content is a further detailed description of the present invention in conjunction with specific preferred embodiments, and it cannot be said that
The specific implementation mode of the present invention is only limitted to this, for those of ordinary skill in the art to which the present invention belongs, is not taking off
Under the premise of from present inventive concept, several simple deduction or replace can also be made, all shall be regarded as belonging to the present invention by institute
Claims of submission determine protection domain.
Claims (10)
1. a kind of operation plan adaptability analysis method based on emulation experiment, includes the following steps：
Math scenario generation step S110：
According to Military Scenario, both sides at war's battle plan and battlefield event that outside provides, the imitative of analogue system identification is formed
Very basic scenario, the Military Scenario includes battlefield Initial situation, red blue party troops, belligerent action and battlefield surroundings；
Simulation scenario element obtaining step S120:
After Math scenario generates and is stored in database according to format, in terms of environment, task, ability and actionable space four
Math scenario is analyzed, extracts simulation scenario element, and determine its value；
Test the factor and experimental point selection step S130:
The extraction experiment factor in simulation scenario element, extracts experimental point so that experimental point is equal as possible for each experiment factor
It is distributed in evenly in entire multi-dimensional data space；
Simulation scenario space motion step S140：
Permutation and combination and screening are carried out to the experiment factor and experimental point extracted, form simulation scenario space, and based on emulation
Numerical value in scenario space runs simulation scenario；
Analysis of simulation experiment step S150:
Including simulation result statistical analysis sub-step：
It is for statistical analysis to the simulation experiment result from different perspectives by various statistical analysis means, it analyzes in simulation scenario
Various simulation scenario elements are to the sensitivity of different experiments index and the simulation scenario element value to experimental index
Influence degree.
2. the operation plan adaptability analysis method according to claim 1 based on emulation experiment, it is characterised in that：
In the Math scenario generation step S110, can single run Math scenario, according to single operation
As a result, found out present in Math scenario by military specialist and object of experiment content there are deviations, or and object of experiment
The problem that level is not inconsistent etc., and Math scenario is adjusted.
3. the operation plan adaptability analysis method according to claim 1 based on emulation experiment, it is characterised in that：
In the simulation scenario element obtaining step, simulation scenario element includes：Operational environment class, entity task class, entity
Ability class and entity action classes element include more seed elements again per class simulation scenario element：
(1) operational environment class element includes：Geographical environment, marine environment, atmospheric environment and electromagnetic environment；
(2) entity task class element includes：The combat duty of various entities and aggregate entities；
(3) physical capabilities class element includes：Entity self-ability element and carrying equipment capability element, self-ability element include
Entity controllable velocity, combat radius, RCS characteristics, it includes carrying guided missile maximum effective range, carrying thunder to carry equipment capability element
Up to investigative range；
(4) entity action classes element includes：Entity plan of maneuver, standby area and beat.
4. the operation plan adaptability analysis method according to claim 1 based on emulation experiment, it is characterised in that：
In the experiment factor and experimental point selection step, the design selection of experimental point should balance required experiment information and control
The time complexity of experiment finds in experimental design stage and experiment operation phase and gives up useless or information to contain as far as possible
Measure less experimental point.
5. the operation plan adaptability analysis method according to claim 4 based on emulation experiment, it is characterised in that：
The common experiment factor includes the operation entity for participating in emulation, operation physical quantities, operation entity carry weapon type, number
Amount and range detection sensor.
6. the operation plan adaptability analysis method according to claim 1 based on emulation experiment, it is characterised in that：
In simulation scenario space motion step, the numerical value operation simulation scenario in the space based on simulation scenario is based on imitative
Numerical value in true scenario space, adjusts the relevant parameter of Math scenario, and runs the Math scenario.
7. the operation plan adaptability analysis method according to claim 1 based on emulation experiment, it is characterised in that：
The analysis of simulation experiment step further includes that simulation result excavates sub-step：
On the basis of simulation result statistical analysis, data mining is carried out to experimental data, is returned according to the result of data mining
It tests the factor and experimental point selects step, if failing to obtain the interested laws of war, feed back to single simulation scenario life
The content and level of cyclic further adjustment simulation scenario, if having analyzed the laws of war of interest, by closing
Key subspace is further amplified or reduces analysis.
8. the operation plan adaptability analysis method according to claim 1 based on emulation experiment, it is characterised in that：
For simulation result statistical analysis sub-step, the experiment factor can also be returned to according to statistic analysis result and experimental point selects
Step S130, in simulation scenario space motion ring simulation scenario element and its value be adjusted, again choose emulation think
Determine element and determines its value, operation simulation scenario space.
9. the operation plan adaptability analysis method according to claim 1 based on emulation experiment, it is characterised in that：
The analysis of simulation experiment step further includes that simulation result excavates sub-step：
According to emulation experiment process, experiment purpose, experiment scenario, experimental design, experiment statistics analysis result, experimental data are dug
It digs analysis result and forms laboratory report according to certain format, and/or experiment is attached to using the decision information of people as experiment conclusion
In report.
10. a kind of storage medium, for storing computer executable instructions, it is characterised in that：
Computer executable instructions perform claim when being executed by processor require described in any one of 1-9 based on imitative
The operation plan adaptability analysis method of true experiment.
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