CN117690330A

CN117690330A - Intelligent military operation strategy simulation training system and method

Info

Publication number: CN117690330A
Application number: CN202410153243.2A
Authority: CN
Inventors: 宇欢锋; 吝学军; 彭巧龙; 李荣辉
Original assignee: Xianyang Huajing Electronic Technology Co ltd
Current assignee: Xianyang Huajing Electronic Technology Co ltd
Priority date: 2024-02-04
Filing date: 2024-02-04
Publication date: 2024-03-12
Anticipated expiration: 2044-02-04
Also published as: CN117690330B

Abstract

The invention belongs to the technical field of simulation training, and discloses an intelligent military operation strategy simulation training system and method; wearing the head-mounted equipment by a user, and constructing a corresponding virtual battlefield environment according to the tactical mode selected by the user and the mode level corresponding to the tactical mode; the user establishes a corresponding military operation strategy according to the constructed virtual battlefield environment and carries out military operation simulation training; dividing the military operation simulation training process into n time points, and collecting strategy analysis data corresponding to the n time points after the military operation simulation training is finished; analyzing strategy analysis data corresponding to the n time points, and judging the simulation grade of the military operation simulation training; forward direction guidance is given according to the simulation grade of the military operation simulation training; the method can promote the user to comprehensively and systematically improve the military tactics skills, and obtain better learning and training effects in simulation training.

Description

Intelligent military operation strategy simulation training system and method

Technical Field

The invention relates to the technical field of simulation training, in particular to an intelligent military operation strategy simulation training system and method.

Background

In modern military environments, the form and complexity of the battlefield evolves continuously, and the army needs to continuously adapt and improve the ability to address various challenges; traditional exercises are often limited by geographic location, resources and time, and it is difficult to provide diverse and complex battlefield simulations, which also results in military personnel that may encounter new challenges and difficulties in facing a real battlefield;

of course, there are also intelligent methods capable of simulating diversity and complicating battlefield, for example, chinese patent with grant bulletin number CN110751869B discloses a simulated environment and battlefield situation policy transfer technique based on the challenge identification type migration method; the invention adopts a countermeasure identification method for regression migration, evaluates the effectiveness of tactical strategies from a mimicry environment to a real environment, records real combat scenes, such as mountain, river, military base and the like information by using a real RGB camera through domain randomization, and has strong robustness for the strategies learned in simulation, so that the learned strategies can be directly migrated to the real combat scenes; the dependence cost of the mimicry migration on the real world is greatly reduced by a simulation method;

Although the technology can simulate the real battlefield environment, the inventor researches and practical application prove that the method and the prior art have at least the following partial defects:

(1) The application limitation is large, and the simulation method is only used for simulating a battlefield environment, and can not simulate armies, equipment and the like;

(2) In the simulation process, real-time feedback cannot be provided, so that military personnel cannot know own decision-making effect in real time;

(3) In the simulation process, forward direction of decision making cannot be provided for military personnel, so that decision making difficulty and strategic adjustment are hindered;

in view of the above, the present invention provides an intelligent military operation strategy simulation training system and method to solve the above-mentioned problems.

Disclosure of Invention

In order to overcome the defects in the prior art, the invention provides the following technical scheme for achieving the purposes: an intelligent military operation strategy simulation training method comprises the following steps:

wearing the head-mounted equipment by a user, and constructing a corresponding virtual battlefield environment according to the tactical mode selected by the user and the mode level corresponding to the tactical mode;

the user establishes a corresponding military operation strategy according to the constructed virtual battlefield environment and carries out military operation simulation training;

Dividing the military operation simulation training process into n time points, and collecting strategy analysis data corresponding to the n time points after the military operation simulation training is finished;

analyzing strategy analysis data corresponding to the n time points, and judging the simulation grade of the military operation simulation training;

and giving forward direction guidance according to the simulation grade of the military operation simulation training.

Further, tactical modes include a tapping mode, a voltaic mode, an assault mode, and a battle mode; each of the tactical modes corresponds to three mode levels, the mode levels including a first level, a second level, and a third level, wherein the third level is more difficult than the second level, and the second level is more difficult than the first level.

Further, the virtual battlefield environment comprises terrain, weather, roles, objects and effects; terrain includes plains, mountains, deserts, forests, and cities, where each terrain includes terrain details and terrain features; weather includes sunny days, cloudy days, rainy days, and snowy days; roles include friend army, enemy army and civilian; the objects are entities and materials used in military operations, and include military equipment, personnel supplies and auxiliary facilities; the auxiliary facilities comprise defending work, information equipment and energy supply equipment; effects include visual effects, sound effects, and physical effects.

Further, the policy analysis data includes character analysis data and object analysis data; the character analysis data comprises friend army data, enemy army data and civilian data; the friend army data comprises friend battlefield injury data, friend battlefield apoptosis data, friend accident injury data and friend accident apoptosis data; the enemy army data comprises enemy battlefield injury data, enemy battlefield apoptosis data, enemy accident injury data and enemy accident apoptosis data; the civilian data comprises civilian injury data and civilian matrix death data;

the object analysis data includes friend object data and enemy object data; the friend object data includes friend equipment damage data, friend replenishment consumption data, and friend facility damage data, and the enemy object data includes enemy equipment damage data, enemy replenishment consumption data, and enemy facility damage data.

Further, the method for analyzing the policy analysis data corresponding to the n time points comprises the following steps:

calculating character coefficients and object coefficients corresponding to the n time point strategy analysis data, and calculating analysis coefficients corresponding to the n time points according to the character coefficients and the object coefficients;

the role coefficient calculating method comprises the following steps:

；

In the method, in the process of the invention,for the role factor->For friends Fang Jiaose coefficient, < >>For the number of friends of the army, the ++>For data of battlefield apoptosis of friend, +.>For friend battlefield injury data, +.>For data of accidental matrix death of friend formula +.>For data of accidental injury of friends, < > for>Is the enemy character coefficient, ++>For the number of friends of the army, the ++>Is the data of enemy battlefield matrix death, +.>For enemy battlefield injury data, +.>For data of unexpected paroxysmal death of enemy, ++>For adversary accident injury data, +.>Is a coefficient of the people who are in the plain,for civilian quantity, add->For civilian gust data, < ->For civilian injury data, i is the firsti time points and，/>、/>、/>、/>、/>、/>、/>the weight is preset and is larger than 0; the number of armies, the number of enemy armies, and the number of civilians are each determined by the tactical mode selected by the user and the level corresponding to the tactical mode, and are each the number corresponding to the military operation simulation training not started.

Further, the method for calculating the object coefficients comprises the following steps:

；

in the method, in the process of the invention,for object coefficients +.>For friend object coefficient, < >>Equip friend with quantity->Equipping friends with damage data->Supplementing the friends with quantity->Supplying consumption data for friends>For the number of friendly auxiliary facilities, < > for>For friendly facility damage data, < > >Is the enemy object coefficient ++>The number of equipment for the adversary,equipping enemy with damage data, < > for>Supplementing enemy personnel with quantity->The consumption data is supplied to the enemy,for the number of enemy auxiliary facilities, <' > for the number of enemy auxiliary facilities>Damage data for enemy facilities, < >>、/>、/>、/>、/>、/>、/>、/>The weight is preset and is larger than 0; the number of friend equipment, the number of friend personnel supplements, the number of friend auxiliary facilities, the number of adversary equipment, the number of adversary personnel supplements and the number of adversary auxiliary facilities are determined by the tactical mode selected by the user and the corresponding grade of the tactical mode, and are all corresponding numbers when the military operation simulation training is not started.

Further, the calculation method of the analysis coefficient includes:

；

in the method, in the process of the invention,for analysis of coefficients +.>、/>Is a preset proportionality coefficient and is larger than 0.

Further, the method for judging the simulation grade of the military operation simulation training comprises the following steps:

the method comprises the steps of presetting a coefficient threshold value and a simulation grade table, and comparing a total analysis coefficient corresponding to the military operation simulation training with the preset coefficient threshold value according to the simulation grade table to obtain a simulation grade of the military operation simulation training;

the calculation method of the total analysis coefficient corresponding to the military operation simulation training comprises the following steps:

；

In the method, in the process of the invention,is the total analysis coefficient;

the simulation grade includes excellent, good, acceptable and unacceptable;

when the tactical mode is the attack mode, ifThe corresponding simulation grade is excellent; if it isThe corresponding simulation grade is good; if->The corresponding simulation grade is qualified; if->The corresponding simulation grade is unqualified;

when the tactical mode is the voltaic mode, ifThe corresponding simulation grade is excellent; if it isThe corresponding simulation grade is good; if->The corresponding simulation grade is qualified; if->The corresponding simulation grade is unqualified;

when the tactical mode is the battle array mode, ifThe corresponding simulation grade is excellent; if it isThe corresponding simulation grade is good; if->The corresponding simulation grade is qualified; if it isThe corresponding simulation grade is disqualified.

Further, if the simulation level of the military operation simulation training of the user is excellent, forward direction guidance is not needed to be given, and analysis coefficients corresponding to n time points in the process of the military operation simulation training are fed back to the user;

If the simulation grade of the military operation simulation training of the user is good or qualified, analyzing analysis coefficients corresponding to n time points in the military operation simulation training process, and providing forward direction for the user;

the method for analyzing the analysis coefficients corresponding to n time points in the military operation simulation training process comprises the following steps:

calculating the average value of analysis coefficients corresponding to n time points in the military operation simulation training process, and marking the average value as a judgment average valueAnalysis coefficient corresponding to n time points +.>Respectively comparing with the judgment mean value, if +.>Marking the time point corresponding to the analysis coefficient as an abnormal time point, if +.>Marking the time point corresponding to the analysis coefficient as a normal time point; identifying an abnormal time point from the n time points, playing back the virtual battlefield environmental video corresponding to the abnormal time point to the user, and simultaneously providing forward direction for the user;

if the simulation grade of the military operation simulation training of the user is unqualified, playing back the virtual battlefield environment videos of all time points in the military operation simulation training of the user to the user, and providing forward guidance for the whole military operation simulation training of the user.

Further, the method for providing forward direction to the user comprises:

forward direction includes anomaly analysis and policy suggestions; the anomaly analysis is to analyze the reasons of strategy defects of users at the anomaly time points; the policy suggestion is a policy suggestion for providing a user at an abnormal time;

acquiring a virtual battlefield environmental video corresponding to an abnormal time point, acquiring each video frame in the virtual battlefield environment, and marking the video frame as an abnormal image; using a trained battlefield analysis model to identify a plurality of abnormal images, and outputting an identification result, wherein the identification result comprises improper deployment of forces, improper logistics deployment and insufficient air defense force;

the battlefield analysis model training process comprises:

the method comprises the steps of collecting a plurality of abnormal images in advance, marking each abnormal image as a training image, and marking each training image, wherein marking comprises improper deployment of forces, improper logistics and insufficient air defense force; converting inappropriate deployment of forces, inappropriate deployment of logistics and insufficient air defense into digital labels respectively, and dividing the labeled training images into a training set and a testing set; training by using a training set battlefield analysis model, and testing by using a testing set battlefield analysis model; presetting an error threshold, and outputting a battlefield analysis model when the average value of the prediction errors of all training images in the test set is smaller than the error threshold; the battlefield analysis model is a convolutional neural network model;

Counting the identification results of each abnormal image, counting the number of each identification result in three identification results, marking the number of identification results corresponding to improper allocation of forces as a first number, marking the number of identification results corresponding to improper allocation of logistics as a second number, marking the number of identification results corresponding to insufficient air defense as a third number, adding the first number, the second number and the third number, and dividing by three to obtain a number average value; taking the identification results corresponding to the number greater than or equal to the number average value in the first number, the second number and the third number as policy defect reasons;

providing corresponding strategy suggestions according to the strategy defect reasons;

dividing the virtual battlefield environment into m areas, wherein m is an integer larger than 1, acquiring a friend object coefficient and a friend Fang Jiaose coefficient corresponding to each area, calculating a friend object coefficient mean value and a friend character coefficient mean value corresponding to the m areas, and marking the areas with the friend object coefficient of Yu Youfang and the friend character coefficient larger than the friend character coefficient mean value as abnormal areas; sequencing the friend object coefficients corresponding to the m areas from large to small, and sequencing the friend Fang Jiaose coefficients corresponding to the m areas from large to small;

If the strategy defect is that the force allocation is improper, according to the number of the abnormal areas, partial friend troops in the areas corresponding to the last Q friend character coefficients in the friend character coefficient sequencing are respectively allocated to the abnormal areas, wherein Q is the number of the abnormal areas;

if the strategy defect is caused by improper logistics allocation, according to the number of the abnormal areas, respectively allocating partial objects in the areas corresponding to the last Q friend object coefficients in the friend object coefficient sequencing to the abnormal areas;

if the strategy defect is that the air defense force is insufficient, according to the number of the abnormal areas, partial air defense equipment of the areas corresponding to the last Q friend character coefficients in the friend character coefficient sequencing are respectively adjusted to the abnormal areas.

The intelligent military operation strategy simulation training system implements the intelligent military operation strategy simulation training method, which comprises the following steps:

the virtual environment construction module is used for enabling a user to wear the head-mounted equipment and constructing a corresponding virtual battlefield environment according to the tactical mode selected by the user and the mode level corresponding to the tactical mode;

the strategy execution module is used for making a corresponding military operation strategy according to the constructed virtual battlefield environment by a user and performing military operation simulation training;

the data collection module is used for dividing the military operation simulation training process into n time points, and collecting strategy analysis data corresponding to the n time points after the military operation simulation training is finished;

The data analysis module is used for analyzing strategy analysis data corresponding to the n time points and judging the simulation grade of the military operation simulation training;

and the guiding module is used for giving forward guidance according to the simulation grade of the military operation simulation training.

An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the intelligent military operation strategy simulation training method when executing the computer program.

A computer readable storage medium having stored thereon a computer program which when executed by a processor implements the intelligent military operation strategy simulation training method.

The intelligent military operation strategy simulation training system and method have the technical effects and advantages that:

according to the embodiment, by constructing the virtual battlefield environment, a user can personally participate in tactical decision and actions in real-time simulation, so that the feeling of being personally on the scene is enhanced; the collected strategy analysis data enables the system to accurately evaluate the performance of the user, provides targeted forward direction for the user, emphasizes the advantages and points out the improvement direction, is helpful for the user to understand the performance of the user in simulation training in depth, and promotes the cognition and application capability improvement of the tactics strategy; the method can promote the user to comprehensively and systematically improve the military tactics skills, and obtain better learning and training effects in simulation training.

Drawings

FIG. 1 is a schematic diagram of an intelligent military operation strategy simulation training system according to embodiment 1 of the present invention;

FIG. 2 is a flowchart of an intelligent military operation strategy simulation training method according to embodiment 2 of the present invention;

fig. 3 is a schematic diagram of an electronic device according to embodiment 3 of the present invention;

fig. 4 is a schematic diagram of a storage medium according to embodiment 4 of the present invention.

Detailed Description

The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

Example 1:

referring to fig. 1, the intelligent military operation strategy simulation training system of the embodiment includes a virtual environment construction module, a strategy execution module, a data collection module, a data analysis module and a guidance module; each module is connected in a wired and/or wireless mode, so that data transmission among the modules is realized;

The head-mounted equipment is VR equipment, and the virtual battlefield environment at least comprises terrain, weather, characters, objects and effects;

the method for constructing the corresponding virtual battlefield by the head-mounted device comprises the following steps:

digitally reconstructing the actual terrain and environment using 3D modeling software (e.g., 3Ds Max, maya, etc.); firstly, collecting relevant scene ball mapping data, and restoring three-dimensional relief topography through point cloud modeling; secondly, building a building model of real details by referring to image materials to realize correct appearance and material rendering; finally, importing virtual reality rendering platforms such as Unreal or Unity and the like to perform unified light source rendering and animation setting;

establishing an AI behavior tree and an action logic script according to the task type; shooting and injury logic of the complex weapon model is realized by utilizing C++ or C# programming; utilizing a network library to write a multicast transmission protocol, and supporting online concurrent access of more than 100 persons; developing a pluggable system module in a component-oriented architecture mode;

ensuring low-delay transmission by using UDP or TCP protocol; decoupling the virtual world synchronization state by adopting an independent operating system architecture; optimizing network overhead by utilizing a general multi-thread and asynchronous I/O technology; the streaming and Delta coding technology is adopted to reduce the data volume of real-time state update; depth customization is carried out on the virtual environment engine, so that correct perspective butt joint, dynamic repositioning and the like are realized; utilizing the OpenVR/OpenXR standard to perform cross-platform adaptation; restoring a real rendering effect by adopting a 3D space audio technology;

The terrain is the terrain of a virtual battlefield environment, and at least comprises plains, mountains, deserts, forests and cities so as to simulate various battlefield environments; wherein each terrain further includes terrain details, such as ground level variations, vegetation coverage, waters, buildings, etc., and terrain features to increase the fidelity of the virtual battlefield environment; terrain features such as rivers, mountains, roads, bridges, etc. to influence the selection and formulation of military operation strategies by users;

weather is the weather of a virtual battlefield environment, the weather at least comprises sunny days, overcast days, rainy days and snowy days, the weather change can influence visibility and combat conditions (such as weapon performance, troops moving speed and the like), and a user is required to adopt different military operation strategies;

the characters are virtual characters in the virtual battlefield environment, and at least comprise friend army, enemy army and civilian, so that a user can simulate actual combat between the virtual friend army and the enemy army, the actual combat coping capability of the user is improved, and the user is helped to formulate diversified military operation strategies; meanwhile, the existence of civilian roles is considered, and the importance and protection consciousness of a user on civilian safety in a battlefield are cultivated;

The object is entity and material used in military operation, the object at least comprises military equipment, personnel supply and auxiliary facilities; military equipment such as infantry weapons (e.g., rifle, submachine gun, machine gun, etc.), armored vehicles (e.g., tank, armored car, armored transport car, etc.), airplanes (e.g., fighter plane, bomber, armed helicopter, etc.), naval vessels (e.g., aircraft carrier, expulsion vessel, cruiser, etc.), air defense equipment (e.g., air defense cannon, air defense rocket cannon, etc.); personnel supplies such as food, drinking water, medical supplies, camping facilities, etc.; the auxiliary facilities at least comprise defending work, information equipment and energy supply equipment, wherein the defending work comprises a trench, a fort, an anti-trench and the like, the information equipment comprises an unmanned plane, a reconnaissance satellite, a reconnaissance robot and the like, and the energy supply equipment comprises a generator, a battery and the like; through simulation of military equipment and auxiliary facilities, more accurate deployment planning can be performed, army force and resource allocation are optimized, and more accurate military operation strategies are formulated; through simulation of personnel replenishment, a more effective replenishment allocation strategy can be formulated;

the effects include at least visual effects, sound effects, and physical effects; visual effects such as special effects (e.g., explosion, fire, smoke, ballistic trajectories, etc.), light shadows (e.g., sunrise, sunset, light changes, etc.); sound effects such as military weapon sounds (e.g., military weapon impact sounds, bomb explosion sounds, etc.), traffic sounds (e.g., armored car travel sounds, aircraft engine sounds, etc.), communication sounds (e.g., command transfer, dialogue, etc. between a user and a soldier of a troop or between soldiers of a troop); physical effects are physical laws of the real world, such as gravity simulation (e.g., falling track, movement track, etc.), collision simulation (e.g., rebound, deformation, friction, etc. after collision), damage simulation (e.g., collapse of building after explosion, deformation of vehicle housing, etc.);

The user can select tactical modes for experience, the tactical modes at least comprise a surrounding mode, a volt mode, an assault mode and an battle mode, different tactical modes have different task requirements, and the comprehensive military coping ability of the user is cultivated through rich tactical modes;

for example, in the tapping mode, the mission requirement is that the user is required to surround the enemy troops in a battlefield environment, and gradually compress to limit the enemy troops to act, finally attack is implemented to fight the enemy troops, and the tapping mode is required to prevent the enemy troops from withdrawing or initiating counterattack, and ensure that the enemy troops cannot acquire personnel replenishment; in the voltaic mode, the task requirement is that a user is required to conceal the army of the friend to wait for the army of the enemy to approach, when the army of the enemy approaches, a sudden attack is initiated to cause confusion or serious injury to the army of the enemy, and the voltaic mode depends on concealment and strategies and requires accurate pre-judgment on the action of the army of the enemy so as to ensure the effectiveness of voltaic; in the sudden attack mode, the task requirement is that a user is required to organize the position of the army of the friend to quickly and accidentally attack the position of the enemy, quickly occupy or destroy the position of the enemy and control the enemy, and the sudden attack mode focuses on speed and resolution, and needs quick action and accurate coordination to achieve the goal in the shortest time; in battle mode, the task is to require the user to organize the friend's army to fight against the enemy's army in a fixed battle or defence work, through firm defending and orderly attack, the battle mode of battle in battle field depends on defending work and strategy, and needs firm intention and stable execution to make long-term battle on battle field;

Each tactical mode corresponds to three mode levels, the mode levels comprise a first level, a second level and a third level, the different mode levels correspond to different difficulties, the difficulty of the third level is greater than that of the second level, and the difficulty of the second level is greater than that of the first level; the mode grades in the same tactical mode are different, and the corresponding topography, weather, roles and objects are different; illustratively, in the battle mode, the secondary corresponds to a worse weather (e.g., strong winds, heavy rain, etc.), the number of friend armies is smaller, the number of enemy armies is larger, the terrain is more complex (e.g., fewer friend armies masks, more enemy armies masks), and fewer personnel replenishment and fewer defence works are performed after fewer military equipment in possession of the friend armies are located; thus, the higher the level, the greater the challenge to the user, requiring the user to have higher tactical skills and better strain capacity to formulate a more complex and efficient military operation strategy;

it should be noted that, the virtual battlefield environments corresponding to the same mode level in the same tactical mode are the same;

The user makes corresponding military operation strategies according to specific terrains, weather, roles and objects in the virtual battlefield scene, and effectively organizes and distributes the army, military equipment, personnel supply and auxiliary facilities of the military, so as to ensure the optimal battlefield performance and successfully execute task requirements in a tactical mode;

the data collection module is used for dividing the military operation simulation training process into n time points, and collecting strategy analysis data corresponding to the n time points after the military operation simulation training is finished, wherein n is an integer greater than 1;

the policy analysis data comprises role analysis data and object analysis data; the character analysis data comprises friend army data, enemy army data and civilian data; the object analysis data includes friend object data and enemy object data; the strategy analysis data is acquired through data records in the virtual battlefield environment, such as through simulation programs, event logs and the like;

the friend army data comprises friend battlefield injury data, friend battlefield apoptosis data, friend accident injury data and friend accident apoptosis data;

the friend battlefield injury data is the injury quantity of the friend army in the battlefield, and the friend battlefield apoptosis data is the apoptosis quantity of the friend army in the battlefield; the injury and the array death on the battlefield are the injury and the array death caused when the army of the friend performs military fight with the army of the enemy on the battlefield; the friend side accidental injury data is the number of casualties caused by accidents of the friend side army in the marching process, and the friend side accidental casualties data is the number of injuries caused by accidents of the friend side army in the marching process; the injuries and the matrix deaths caused by accidents in the marching process are injuries and matrix deaths caused by accidents in the marching process of the army, and the accidents comprise diseases, falls, bad weather, poisoning and the like;

The larger the data of the army of the friend party is, the more the number of injuries and fatalities of the army of the friend party is, the more unreasonable the military operation strategy formulated by the user is, the worse the battlefield performance is, and the more difficult the task requirements under the tactical mode are completed;

the enemy army data comprises enemy battlefield injury data, enemy battlefield apoptosis data, enemy accident injury data and enemy accident apoptosis data; the enemy battlefield injury data is the injury quantity of the enemy army on the battlefield, and the enemy battlefield array death data is the array death quantity of the enemy army on the battlefield; the enemy accidental injury data is the number of casualties caused by the enemy army in the marching process, and the enemy accidental casualties data is the number of injuries caused by the enemy army in the marching process;

the larger the data of the enemy army is, the more the number of injuries and fatalities of the enemy army is, the more reasonable the military operation strategy formulated by the user is, the better the battlefield performance is, and the task requirements under the tactical mode are easier to finish;

the civilian data comprises civilian injury data and civilian matrix death data; the civilian injury data and civilian matrix death data are the number of injuries and matrix deaths of civilians when military combat is carried out on the friendly army and the enemy army;

The larger the civilian data is, namely the larger the civilian injury data and the civilian apoptosis data are, the more the civilian injury and the more the number of the civilian apoptosis are, the less reasonable the military operation strategy formulated by the user is, the more harm is caused to the civilian, and the task requirements in the tactical mode are not easy to complete;

the friend object data comprises friend equipment damage data, friend replenishment consumption data and friend facility damage data, wherein the friend equipment damage data is the damage quantity of friend military equipment, the friend replenishment consumption data is the consumption quantity of friend personnel replenishment, and the friend facility damage data is the damage quantity of friend auxiliary facilities; the enemy object data comprises enemy equipment damage data, enemy replenishment consumption data and enemy facility damage data, wherein the enemy equipment damage data is the damage quantity of enemy military equipment, the enemy replenishment consumption data is the consumption quantity of enemy personnel replenishment, and the enemy facility damage data is the damage quantity of enemy auxiliary facilities;

the larger the data of the object of the friend is, the larger the damage and consumption of military equipment, personnel supply and auxiliary facilities of the friend are, the more unreasonable the military operation strategy formulated by the user is, and the more difficult the task requirements under tactical mode are completed; the larger the object data of the opposite enemy is, the larger damage and consumption of military equipment, personnel replenishment and auxiliary facilities of the enemy are, the more reasonable the military operation strategy formulated by the user is, the better the battlefield performance is, and the task requirements under the tactical mode are more easily completed;

The strategy analysis data is used for analyzing the casualties and material loss conditions of friends and enemies in the military operation simulation training so as to judge the rationality and effect of the military operation strategy formulated by the user, and can provide intelligent guidance for the user according to the strategy analysis data;

the method for analyzing the strategy analysis data corresponding to the n time points comprises the following steps:

the role coefficient calculating method comprises the following steps:

；

in the method, in the process of the invention,for the role factor->For friends Fang Jiaose coefficient, < >>For the number of friends of the army, the ++>For data of battlefield apoptosis of friend, +.>For friend battlefield injury data, +.>For data of accidental matrix death of friend formula +.>For data of accidental injury of friends, < > for>Is the enemy character coefficient, ++>For the number of enemy army->Is the data of enemy battlefield matrix death, +.>For enemy battlefield injury data, +.>For data of unexpected paroxysmal death of enemy, ++>For adversary accident injury data, +. >Is a coefficient of the people who are in the plain,for civilian quantity, add->For civilian gust data, < ->For civilian injury data, i is the ith time point and，/>、/>、/>、/>、/>、/>、/>are preset weight coefficients and are all larger than 0;

the specific value of the weight coefficient in the formula can be set according to the actual situation, the weight coefficient reflects the importance of each role analysis data, and a person skilled in the art can adjust the corresponding weight coefficient according to the importance of each role analysis data so as to accurately evaluate the battlefield performance situation of the user;

the number of the armies of the friends, the number of the enemy and the number of the citizens are determined by the tactical mode selected by the user and the grade corresponding to the tactical mode, and are the corresponding numbers when the military operation simulation training is not started;

it should be appreciated that the friend Fang Jiaose coefficient, the enemy character coefficient, the civilian coefficient and the character coefficient are all quantized indexes for evaluating the effect of the present military operation simulation; the larger the data of the battlefield injury, the data of the battlefield apoptosis, the data of the unexpected battlefield apoptosis and the data of the unexpected injury of the friend are, the larger the corresponding role coefficient of the friend is, which means that the more the number of casualties of the army of the friend is, the more unreasonable the strategy formulated by the user is, so the larger the role coefficient is, and vice versa; the larger the enemy battlefield injury data, the enemy battlefield apoptosis data, the enemy accident battlefield apoptosis data and the enemy accident injury data are, the larger the corresponding enemy character coefficients are, which means that the more the number of casualties of the enemy army is, the more reasonable the strategy formulated by the user is, so the smaller the character coefficients are, and the opposite is the contrary; the larger the civilian matrix death data and the civilian injury data are, the larger the civilian coefficient is, which means that the more the civilian number of casualties is, the more unreasonable the strategy formulated by the user is, so the larger the role coefficient is, and vice versa;

The calculation method of the object coefficients comprises the following steps:

；

in the method, in the process of the invention,for object coefficients +.>For friend object coefficient, < >>Equip friend with quantity->Equipping friends with damage data->Supplementing the friends with quantity->Supplying consumption data for friends>For the number of friendly auxiliary facilities, < > for>For friendly facility damage data, < >>Is the enemy object coefficient ++>The number of equipment for the adversary,equipping enemy with damage data, < > for>Supplementing enemy personnel with quantity->The consumption data is supplied to the enemy,for the number of enemy auxiliary facilities, <' > for the number of enemy auxiliary facilities>Damage data for enemy facilities, < >>、/>、/>、/>、/>、/>、/>、/>Is a preset proportionality coefficient and is larger than 0;

the specific value of the proportionality coefficient in the formula can be set according to the actual situation, the proportionality coefficient reflects the importance of each object analysis coefficient, and a person skilled in the art can adjust the corresponding proportionality coefficient according to the importance of each object analysis coefficient so as to accurately evaluate the battlefield performance situation of the user;

the number of the friend equipment, the number of the friend auxiliary facilities, the number of the enemy equipment, the number of the enemy personnel and the number of the enemy auxiliary facilities are determined by the tactical mode selected by the user and the corresponding grade of the tactical mode, and are all corresponding numbers when the military operation simulation training is not started;

It should be appreciated that the object coefficients, friend object coefficients, and enemy object coefficients are all quantized metrics for evaluating the effect of the present military operation simulation; the more the damage data of the friend equipment and the consumption data of the friend replenishment are, the larger the damage data of the friend facility are, the larger the corresponding friend object coefficients are, the more the damage quantity of military equipment and auxiliary facilities of the friend is, the more the consumption quantity of personnel replenishment of the friend is, the more unreasonable the strategy formulated by the user is, so that the object coefficients are larger, and vice versa; the larger the damage data of the enemy equipment and the enemy replenishment consumption data are, the larger the corresponding enemy object coefficients are, so that the larger the damage quantity of the military equipment and the auxiliary facilities of the enemy is, the larger the enemy replenishment consumption quantity of the personnel of the enemy is, the more reasonable the strategy formulated by the user is, and therefore the object coefficients are smaller, and conversely, the opposite is true;

the calculation method of the analysis coefficient comprises the following steps:

；

in the method, in the process of the invention,for analysis of coefficients +.>、/>Is a preset proportionality coefficient and is larger than 0;

the specific value of the proportionality coefficient in the formula can be set according to the actual situation, the importance of the object coefficient and the role coefficient is reflected by the proportionality coefficient, and a person skilled in the art can adjust the corresponding proportionality coefficient according to the importance of the object coefficient and the role coefficient so as to accurately evaluate the battlefield performance situation of the user;

It should be noted that, the analysis coefficient is a quantized index, and is used for evaluating the effect of the present military operation simulation; the larger the role coefficient and the object coefficient, the larger the corresponding analysis coefficient, which indicates that the strategy formulated by the user is unreasonable, otherwise, the opposite is true;

the method for judging the simulation grade of the military operation simulation training comprises the following steps:

；

because of different tactical modes, the requirements on analysis coefficients are different, for example, in the voltaic mode, the army of the friend initiates sudden attack to the army of the enemy through concealment, the army of the enemy is easy to be overwhelmed, the organization defense cannot be quickly and effectively realized, the number of injuries and deaths of the army of the friend is small, and the corresponding analysis coefficients are small; in the battle array mode, the army of the friend needs to be positively resisted by the army of the enemy, so that the number of injuries and deaths of the army of the friend is larger, and the corresponding analysis coefficient is also larger; therefore, under different tactical modes, the method for judging the simulation grade is different, the simulation grade comprises excellent, good, qualified and unqualified, and the simulation grade table is shown in table 1;

TABLE 1 analog class table

In the table of the present invention,for the corresponding total analysis coefficient in the attack mode, +.>For the corresponding total analysis coefficient in voltaic mode, +.>For the corresponding total analysis coefficient in the attack mode, +.>For the corresponding total analysis coefficient in battle array mode, +.>A preset coefficient threshold value is set; the coefficient threshold is set by a person skilled in the art according to the task requirements of the military operation simulation training;

the guiding module is used for giving forward guidance according to the simulation grade of the military operation simulation training;

if the simulation level of the military operation simulation training of the user is excellent, forward direction is not required to be given, and analysis coefficients corresponding to n time points in the military operation simulation training process are fed back to the user, so that the user performs strategy optimization in the next military operation, and the fact that the user has higher completion degree of the military operation simulation training and better battlefield performance is shown;

if the simulation grade of the military operation simulation training of the user is good or qualified, analyzing analysis coefficients corresponding to n time points in the military operation simulation training process, and providing forward direction for the user; the user is lower in simulation training completion degree of the military operation, and the battlefield performance is poor;

the method for providing forward direction to the user comprises the following steps:

forward direction includes anomaly analysis and policy suggestions; the anomaly analysis is to analyze the reasons of strategy defects of the user at the anomaly time points so as to help the user to determine the defects of the strategy in the simulation training of the military operation; the strategy proposal is used for providing strategy proposal of a user at abnormal time so as to help the user acquire a corresponding improved method when the explicit strategy has defects, so that the user can better develop a more intelligent and effective strategy under similar conditions;

Acquiring a virtual battlefield environmental video corresponding to an abnormal time point, acquiring each video frame in the virtual battlefield environment, and marking the video frame as an abnormal image; using a trained battlefield analysis model to identify a plurality of abnormal images, and outputting an identification result, wherein the identification result comprises improper deployment of forces, improper logistics deployment and insufficient air defense force; the improper deployment of forces is insufficient in quantity of the army of the friend in certain areas or time, the improper deployment of logistics is insufficient in personnel supply and weapon ammunition supply in the army of the friend, the insufficient air defense force is insufficient in use area of the air defense weapon in the army of the friend, and the air strike of the army of the enemy cannot be effectively prevented;

the specific training process of the battlefield analysis model comprises the following steps:

the method comprises the steps of collecting a plurality of abnormal images in advance, marking each abnormal image as a training image, and marking each training image, wherein marking comprises improper deployment of forces, improper logistics and insufficient air defense force; converting the weapons misallocation, the logistics misallocation and the air defense force shortage into digital labels respectively, and converting the weapons misallocation into 1, the logistics misallocation into 2 and the air defense force shortage into 3 by way of example; dividing the marked training images into a training set and a testing set, taking 70% of the training images as the training set and 30% of the training images as the testing set; training by using a training set battlefield analysis model, and testing by using a testing set battlefield analysis model; presetting an error threshold, and outputting a battlefield analysis model when the average value of the prediction errors of all training images in the test set is smaller than the error threshold; wherein, the calculation formula of the prediction error mean value is that Wherein->For prediction error +.>For the number of training images, +.>Is->Predictive annotation corresponding to group training image, +.>Is->The actual labels corresponding to the training images are set, and U is the number of the training images in the test setThe method comprises the steps of carrying out a first treatment on the surface of the The error threshold is preset according to the precision required by the battlefield analysis model;

the battlefield analysis model is specifically a convolutional neural network model;

If the policy defect is that the army force is improperly allocated, according to the number of abnormal areas, partial army of the last Q areas corresponding to the friend character coefficients in the friend character coefficient sequence are respectively allocated to the abnormal areas, Q is the number of the abnormal areas, andthe method comprises the steps of carrying out a first treatment on the surface of the The method has the advantages that the number of the armies of the friends in the abnormal area is insufficient to fight against the armies of the enemy, so that larger casualties are caused, and the armies of the friends are required to be augmented from the area with the small number of the casualties of the armies of the friends to better cope with the threat of the armies of the enemy;

if the strategy defect is caused by improper logistics allocation, according to the number of the abnormal areas, respectively allocating partial objects in the areas corresponding to the last Q friend object coefficients in the friend object coefficient sequencing to the abnormal areas; the method has the advantages that the excessive consumption of the object quantity in the abnormal area is described, and the objects are required to be transported from the area with less consumption of the object quantity in time so as to ensure the logistic normal;

if the strategy defect is that the air defense force is insufficient, according to the number of the abnormal areas, adjusting partial air defense equipment of the areas corresponding to the last Q friend character coefficients in the friend character coefficient sequencing to the abnormal areas respectively; indicating that the number of the air defense devices in the abnormal area is insufficient to resist the air attack of the enemy, thereby causing larger casualties and object damage of the army, the air defense devices need to be augmented from the area with less casualties of the army to better cope with the air attack of the enemy, and the area with less casualties of the army indicates that the number of the air defense devices is relatively large;

The military operation simulation training is an array battle mode, at an abnormal time point, the casualties of the friendly army are larger, the virtual battle field environment is played back, the condition that the number of the friendly army at one place of the array is smaller, the friendly army cannot be blocked, and larger casualties are caused is found, and therefore the given strategy proposal is that the deployment of the friendly army in each area of the array is regulated, and part of the friendly army in the area with the smaller casualties is regulated to the place with larger casualties so as to better cope with the threat of the friendly army and cause powerful blocking to the friendly army;

if the simulation grade of the military operation simulation training of the user is unqualified, playing back the virtual battlefield environment videos of all time points in the military operation simulation training to the user, providing forward guidance for the whole military operation simulation training of the user, and simultaneously encouraging the user to perform the military operation simulation training again; the user is proved to have serious problems in the military operation simulation training, and task requirements under corresponding tactical modes are not completed, so that the military operation simulation training is finished in advance;

Example 2:

referring to fig. 2, this embodiment is not described in detail in embodiments 1 and 2, and provides an intelligent military operation strategy simulation training method, which includes:

the role coefficient calculating method comprises the following steps:

；

in the method, in the process of the invention,for the role factor->For friends Fang Jiaose coefficient, < >>For the number of friends of the army, the ++>For data of battlefield apoptosis of friend, +.>For friend battlefield injury data, +.>For data of accidental matrix death of friend formula +.>For data of accidental injury of friends, < > for>Is the enemy character coefficient, ++>For the number of friends of the army, the ++>Is the data of enemy battlefield matrix death, +.>For enemy battlefield injury data, +.>For data of unexpected paroxysmal death of enemy, ++>For adversary accident injury data, +.>Is a coefficient of the people who are in the plain,for civilian quantity, add->For civilian gust data, < ->For civilian injury data, i is the ith time point and ，/>、/>、/>、/>、/>、/>、/>The weight is preset and is larger than 0; the number of armies, the number of enemy armies, and the number of civilians are each determined by the tactical mode selected by the user and the level corresponding to the tactical mode, and are each the number corresponding to the military operation simulation training not started.

；

in the method, in the process of the invention,for object coefficients +.>For friend object coefficient, < >>Equip friend with quantity->Equipping friends with damage data->Supplementing the friends with quantity->Supplying consumption data for friends>For the number of friendly auxiliary facilities, < > for>For friendly facility damage data, < >>Is the enemy object coefficient ++>The number of equipment for the adversary,equipping enemy with damage data, < > for>Supplementing enemy personnel with quantity->The consumption data is supplied to the enemy,for the number of enemy auxiliary facilities, <' > for the number of enemy auxiliary facilities>Damage data for enemy facilities, < >>、/>、/>、/>、/>、/>、/>、/>The weight is preset and is larger than 0; the number of friend equipment, the number of friend personnel supplements, the number of friend auxiliary facilities, the number of adversary equipment, the number of adversary personnel supplements and the number of adversary auxiliary facilities are determined by the tactical mode selected by the user and the corresponding grade of the tactical mode, and are all corresponding numbers when the military operation simulation training is not started.

Further, the calculation method of the analysis coefficient includes:

；

the simulation grade includes excellent, good, acceptable and unacceptable;

when the tactical mode is the attack mode, if The corresponding simulation grade is excellent; if it isThe corresponding simulation grade is good; if->The corresponding simulation grade is qualified; if->The corresponding simulation grade is unqualified;

calculating the average value of analysis coefficients corresponding to n time points in the military operation simulation training process, and marking the average value as a judgment average valueAnalysis coefficient corresponding to n time points +. >Respectively comparing with the judgment mean value, if +.>Marking the time point corresponding to the analysis coefficient as an abnormal time point, if +.>Marking the time point corresponding to the analysis coefficient as a normal time point; identifying an abnormal time point from the n time points, playing back the virtual battlefield environmental video corresponding to the abnormal time point to the user, and simultaneously providing forward direction for the user;

Further, the method for providing forward direction to the user comprises:

The battlefield analysis model training process comprises:

Example 3:

referring to fig. 3, an electronic device 500 is also provided according to yet another aspect of the present application. The electronic device 500 may include one or more processors and one or more memories. Wherein the memory has stored therein computer readable code which, when executed by the one or more processors, can perform the intelligent military operation strategy simulation training method as described above.

The method or system according to embodiments of the present application may also be implemented by means of the architecture of the electronic device shown in fig. 3. As shown in fig. 3, the electronic device 500 may include a bus 501, one or more CPUs 502, a Read Only Memory (ROM) 503, a Random Access Memory (RAM) 504, a communication port 505 connected to a network, an input/output 506, a hard disk 507, and the like. A storage device in electronic device 500, such as ROM503 or hard disk 507, may store the intelligent military operation policy simulation training method provided herein. Further, the electronic device 500 may also include a user interface 508. Of course, the architecture shown in fig. 3 is merely exemplary, and one or more components of the electronic device shown in fig. 3 may be omitted as may be practical in implementing different devices.

Example 4:

referring to FIG. 4, a computer readable storage medium 600 according to one embodiment of the present application is shown. Computer readable storage medium 600 has stored thereon computer readable instructions. The intelligent military operation strategy simulation training method according to the embodiments of the present application described with reference to the above figures may be performed when the computer readable instructions are executed by the processor. Storage medium 600 includes, but is not limited to, for example, volatile memory and/or nonvolatile memory. Volatile memory can include, for example, random Access Memory (RAM), cache memory (cache), and the like. The non-volatile memory may include, for example, read Only Memory (ROM), hard disk, flash memory, and the like.

In addition, according to embodiments of the present application, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, the present application provides a non-transitory machine-readable storage medium storing machine-readable instructions executable by a processor to perform instructions corresponding to the method steps provided herein, such as: an intelligent military operation strategy simulation training method. The above-described functions defined in the method of the present application are performed when the computer program is executed by a Central Processing Unit (CPU).

The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the processes or functions described in accordance with embodiments of the present invention are produced in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center over a wired network or a wireless network. The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains one or more sets of available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium may be a solid state disk.

Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.

In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely one, and there may be additional divisions in actual implementation, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.

The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Finally: the foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.

Claims

1. The intelligent military operation strategy simulation training method is characterized by comprising the following steps of:

2. The intelligent military operation strategy simulation training method of claim 1, wherein said tactical patterns include a girth pattern, a voltaic pattern, an assault pattern, and an battle array pattern; each of the tactical modes corresponds to three mode levels, the mode levels including a first level, a second level, and a third level, wherein the third level is more difficult than the second level, and the second level is more difficult than the first level.

3. The intelligent military operation strategy simulation training method of claim 2, wherein said virtual battlefield environment comprises terrain, weather, characters, objects and effects; the terrains include plain, mountain, desert, forest, and city, where each terrain includes terrain details and terrain features; weather includes sunny days, cloudy days, rainy days, and snowy days; the roles include friend army, enemy army and civilian; the object is an entity and a material used in military operations, and the object comprises military equipment, personnel supply and auxiliary facilities; the auxiliary facilities comprise defending work, information equipment and energy supply equipment; the effects include visual effects, sound effects, and physical effects.

4. The intelligent military operation strategy simulation training method of claim 3, wherein said strategy analysis data comprises character analysis data and object analysis data; the role analysis data comprises friend army data, enemy army data and civilian data; the friend army data comprises friend battlefield injury data, friend battlefield apoptosis data, friend accidental injury data and friend accidental apoptosis data; the enemy army data comprises enemy battlefield injury data, enemy battlefield apoptosis data, enemy accidental injury data and enemy accidental apoptosis data; the civilian data comprises civilian injury data and civilian matrix death data;

5. The intelligent military operation strategy simulation training method of claim 4, wherein said method for analyzing strategy analysis data corresponding to n time points comprises:

the role coefficient calculating method comprises the following steps:

；

in the method, in the process of the invention,for the role factor->For friends Fang Jiaose coefficient, < >>For the number of friends of the army, the ++>For data of battlefield apoptosis of friend, +.>For friend battlefield injury data, +.>For data of accidental matrix death of friend formula +.>For data of accidental injuries of the friends,is the enemy character coefficient, ++>For the number of enemy army->Is the data of enemy battlefield matrix death, +.>For enemy battlefield injury data, +.>For data of unexpected paroxysmal death of enemy, ++ >For adversary accident injury data, +.>Is a civilian factor, is->For civilian quantity, add->For civilian gust data, < ->For civilian injury data, i is the i-th time point and +.>，、/>、/>、/>、/>、/>、/>The weight is preset and is larger than 0; the number of armies, the number of enemy armies, and the number of civilians are each determined by the tactical mode selected by the user and the level corresponding to the tactical mode, and are each the number corresponding to the military operation simulation training not started.

6. The intelligent military operation strategy simulation training method of claim 5, wherein the object coefficient calculation method comprises:

；

in the method, in the process of the invention,for object coefficients +.>For friend object coefficient, < >>Equip friend with quantity->Equipping friends with damage data->Supplementing the friends with quantity->Supplying consumption data for friends>For the number of friendly auxiliary facilities, < > for>For friendly facility damage data, < >>Is the enemy object coefficient ++>Equipping enemy with number->Equipping enemy with damage data, < > for>Supplementing enemy personnel with quantity->Supplementing consumption data for enemy, < - > for>For the number of enemy auxiliary facilities, <' > for the number of enemy auxiliary facilities>Damage data for enemy facilities, < >>、/>、/>、/>、/>、/>、/>、/>The weight is preset and is larger than 0; the number of friend equipment, the number of friend personnel supplements, the number of friend auxiliary facilities, the number of adversary equipment, the number of adversary personnel supplements and the number of adversary auxiliary facilities are determined by the tactical mode selected by the user and the corresponding grade of the tactical mode, and are all corresponding numbers when the military operation simulation training is not started.

7. The intelligent military operation strategy simulation training method of claim 6, wherein the calculation method of the analysis coefficients comprises:

；

8. The method for intelligent simulation training of military operation strategy according to claim 7, wherein the method for judging the simulation level of the simulation training of the present military operation comprises:

preset coefficient thresholdComparing the total analysis coefficient corresponding to the military operation simulation training with a preset coefficient threshold according to the simulation grade table to obtain the military operationSimulation grade of simulation training;

；

the simulation grade includes excellent, good, acceptable and unacceptable;

when the tactical mode is the attack mode, ifThe corresponding simulation grade is excellent; if->The corresponding simulation grade is good; if->The corresponding simulation grade is qualified; if->The corresponding simulation grade is unqualified;

when the tactical mode is the voltaic mode, ifThe corresponding simulation grade is excellent; if it is The corresponding simulation grade is good; if->The corresponding simulation grade is qualified; if->The corresponding simulation grade is unqualified;

9. The intelligent military operation strategy simulation training method according to claim 8, wherein if the simulation level of the military operation simulation training of the user is excellent, no forward direction is required to be given, and the analysis coefficients corresponding to n time points in the process of the military operation simulation training are fed back to the user;

10. The intelligent military operation strategy simulation training method of claim 9, wherein the method of providing forward direction to the user comprises:

the battlefield analysis model training process comprises:

11. An intelligent military operation strategy simulation training system for implementing the intelligent military operation strategy simulation training method as set forth in any one of claims 1-10, comprising:

12. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the intelligent military operation strategy simulation training method of claims 1-10 when the computer program is executed by the processor.

13. A computer readable storage medium, wherein a computer program is stored on the computer readable storage medium, which when executed by a processor, implements the intelligent military operation strategy simulation training method of claims 1-10.