A one-button switching method for training environments with different training contents

Abstract

The present invention discloses a one-click switching method for training environments with different training contents, comprising: step 1, course optimization and arrangement, according to the training task requirements, based on preset training course knowledge rules, constructing a training course switching time matrix to optimize course arrangement; step 2, background resource reorganization, according to the course sequence and content, the background relies on application clusters, container scheduling and data source switching technologies to quickly establish and arrange background services and dynamically reorganize data resources; step 3, foreground application arrangement, according to the relationship between users, permissions and software, using lightweight client integration technology to integrate and arrange foreground applications. This method realizes one-click rapid switching of training content and dynamic reorganization of training resources, reduces the time for setting up and deploying the training environment and the waiting time of personnel during the conversion of different training courses, and greatly improves training efficiency and effectiveness.

Description

Technical Field

[0001] The present invention belongs to the technical field of military training, and in particular relates to a one-key switching method for training environments with different training contents. Background Art

[0002] Currently, different training content requires switching system deployment methods and configurations. Traditional manual deployment and configuration switching methods are time-consuming, cumbersome, inefficient, and prone to errors. This hinders users from flexibly organizing training for different training subjects and multiple training modes, and fails to meet current training needs. Summary of the Invention

[0003] Purpose of the invention: The technical problem to be solved by the present invention is to provide a one-key switching method for training environments with different training contents in response to the shortcomings of the existing technology.

[0004] In order to solve the above technical problems, the present invention discloses a one-key switching method for training environments with different training contents, comprising the following steps:

[0005] Step 1: Optimize the course arrangement. According to the training task requirements and based on the preset training course knowledge rules, establish the training course switching time matrix, calculate the optimal course sequence, and achieve course arrangement optimization;

[0006] Step 2: Backend resource reorganization: Based on the course sequence and content, the backend relies on application clusters, container scheduling, and data source switching technologies to quickly build and orchestrate backend services and dynamically reorganize data resources.

[0007] Step 3: Front-end application orchestration: Based on the relationship between users, permissions, and software, lightweight client integration technology is used to quickly integrate and orchestrate front-end applications.

[0008] Furthermore, the step 1 includes:

[0009] Step 1.1: Obtain the application resources, service resources, and data resources required for each training course based on the preset training course knowledge rules and training content;

[0010] Step 1.2: Based on the switching time from one training course to another, a switching time matrix is established, and the training courses with high resource similarity are arranged to obtain the optimal course sequence with the shortest waiting time for training environment switching as the constraint.

[0011] Furthermore, the training courses in step 1.1 include individual personnel training courses and overall personnel training courses. The switching time matrix in step 1.2 reflects that different switching times are generated in different course sequences, and the length of the switching time is closely related to the seat resources, service resources and data resources required for the training courses.

[0012] Furthermore, in step 1.2, the training courses with high resource similarity are arranged as follows:

[0013] Step 1.2.1: Format the description of training subject resources. Training subject resources are described in a formatted manner and consist of application resources, service resources, and data resource feature areas. Application resources include training planning, command and control, process monitoring, data collection, and assessment and evaluation application software. Service resources include data transmission, geographic information, knowledge extraction, scenario simulation, and special situation handling services. Data resources include basic training data for our side, enemy, battlefield environment, and models; situation, command, action, and support training process data; and training command and evaluation data for training scenarios, command and control, and evaluation results.

[0014] Step 1.2.2: Generate the training resource feature matrix. The training resource feature matrix generation means assigning a value to each element of the resource feature area obtained in step 1.2.1 according to the actual training task requirements. The value assigned to the corresponding subject resource is 1, and the value assigned to the non-existent subject resource is 0. The training resource feature matrix is expressed as

[0015] Step 1.2.3: Optimal sorting of training courses based on the training resource feature matrix. First, use the norm formula to calculate the deviation between the resource feature matrix of the current training course and the next training course. Then, traverse the training courses and sort all the deviation values after traversal. Rearrange the training courses with the smallest deviation value, that is, the highest resource similarity. The deviation value calculation formula is as follows:

[0016] D ij =‖A i -B j ‖ 2 (i=1,2,…,S; j=1,2,…,S)

[0017] Among them, D ij is the deviation value of the resource feature matrix between the current training course and the next training course, A i is the resource feature matrix of the current training course, B j is the resource feature matrix of the next training course, S is the complete set of training courses, i is the current training course number, and j is the next training course number.

[0018] Furthermore, in step 1.2, with the shortest waiting time for training environment switching as the constraint, the optimal course sequence is obtained as follows:

[0019] The training courses in the training course set S are s1, s2, s3, ..., s H-1 ,s H , H represents the number of training subjects; the training sequence of subjects is recorded as: s1, s2, s3,…, s H-1 ,s H .

[0020] The objective function with the shortest waiting time for training environment switching as the constraint is expressed as:

[0021]

[0022] Among them, T represents the total time consumed by switching between all training subjects; and The time required to switch from the current training course to the next training course respectively;

[0023] In order to optimize the objective function, the following constraints are required:

[0024] Each training course must and can only be switched once, i.e. s1, s2, s3, ..., s H-1 ,s H Not the same;

[0025] The last training course does not need to be switched, so the value of a row and column of the matrix is 0, that is,

[0026] The training courses with high similarity in terms of objective function, constraints and resources are arranged together to obtain the optimal course sequence.

[0027] Furthermore, in step 2: for different training contents of individual personnel training and overall personnel training, the background resource reorganization adopts different construction methods to meet the training needs: in the individual personnel training mode, relying on the container cloud on the supporting server, build multiple sets of minimal system operating environments that meet the training needs, and each set of minimal system operating environments can support one training seat to carry out training; in the overall personnel training environment, the actual system technology architecture is adopted, and the core and basic application services of the actual system technology architecture run on the core basic server, hosted by the lightweight service cluster, and the supporting application services run on the container cloud of the supporting server, thereby building a complete training system to support all training seats to carry out training.

[0028] Furthermore, the step 2 includes: the software developer uses a packaging tool to uniformly package the backend service software into two forms: an image and a software installation package, and uploads them to the image warehouse and the software warehouse respectively;

[0029] During training, according to the order of training courses, before the start of each course training, the system automatically stops and withdraws resources that are no longer needed in the previous course's operating environment. According to the training resource configuration plan for each course group, the system automatically identifies the construction method of the operating environment and constructs it.

[0030] Furthermore, the automatic identification and construction method of the operating environment in step 2 includes: when the actual system technical architecture is adopted in the overall personnel training environment, the core basic server automatically downloads the software installation package of the core basic application service from the software warehouse for installation and deployment, and the container cloud automatically creates a supporting application service instance, completes the resource configuration of each application and database service and the injection of hypothetical data, and starts the application service container in the application cluster and the container cloud.

[0031] Furthermore, the automatic identification and construction of the operating environment construction method in step 2 also includes: when using the container cloud to build multiple sets of minimal system operating environments in a single-personnel training mode, automatically extracting the service images required for the training courses, automatically creating the required application service instances and database instances on the container cloud, completing the resource configuration of each application and database service and the injection of hypothetical data, starting the application service container in the container cloud, and building multiple sets of minimal systems that meet the training needs, supporting each trainee to carry out training without interference at the same time.

[0032] Furthermore, the step 3 includes:

[0033] Relying on the functional modules of QT, Poco and Java, a lightweight client integration architecture is constructed, including the basic function layer, the framework extension function layer and the application support function layer. Among them, the basic function layer provides plug-in integration based on the Poco module for the general client software integration architecture; the framework extension function layer provides functional extension for the general client software integration architecture; and the application support function layer provides support capabilities for application plug-ins and application systems.

[0034] The client application software used in different training courses is different, and corresponding client application software is provided to trainees according to the training courses; all client application software of the training environment are deployed in all training seats, and they are managed uniformly, providing a unified startup entrance; according to the user identity, current training course and preset training course knowledge rules, the application resources required for this training course are matched, and the corresponding function menu is switched to complete the rapid loading and operation of the training environment.

[0035] Compared with the existing technology, the present invention has the following significant advantages: it proposes a one-click switching method for training environments with different training contents, constructs a switching time matrix, optimizes the course arrangement, realizes one-click rapid switching of training content and dynamic reorganization of training resources, reduces the time for setting up and deploying the training environment and the waiting time for personnel during the conversion of different training courses, and greatly improves the training efficiency and effectiveness. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments, and the above and / or other advantages of the present invention will become more apparent.

[0037] Figure 1 It is a flow chart of a one-key switching method for training environments with different training contents according to the present invention.

[0038] Figure 2 This is a diagram of the integrated architecture of a lightweight client in a one-click switching method for training environments with different training contents according to the present invention.

[0039] Figure 3 It is a schematic diagram of training course resources in a one-key switching method for training environments with different training contents according to the present invention.

[0040] Figure 4 It is a schematic diagram of the background operation environment construction in the one-key switching method of the training environment for different training contents of the present invention. DETAILED DESCRIPTION

[0041] The embodiments of the present invention will be described below with reference to the accompanying drawings.

[0042] The one-click switching method of training environments for different training contents provided in this application can be applied to training scenarios for military commanders or operators.

[0043] The embodiment of the present application discloses a one-key switching method for training environments with different training contents, such as Figure 1 Shown, including:

[0044] Step 1: Optimize course arrangement

[0045] According to the training task requirements and based on the preset training course knowledge rules, a switching time matrix is established, the optimal course sequence is calculated, and course arrangement optimization is achieved. The specific steps include the following:

[0046] Step 1.1: During normal training, the training environment pre-sets the training course knowledge rules and sets the applications, services, and data resources that each training course relies on. During training planning, the applications, services, and data resources required for each training course are obtained based on the pre-set training course knowledge rules and training content.

[0047] In step 1.2, a switching time matrix is established based on the switching time between each training course. The training resource feature matrix is also calculated, and training courses with high resource similarity are arranged. The optimal course sequence is determined, with the shortest training environment switching wait time as the constraint, to minimize the time spent switching between training environments during training.

[0048] Assume that this training involves both individual training and joint training. Individual training subjects primarily include Subject A, Subject B, Subject C, Subject D, Subject E, and Subject F, while joint training primarily includes Subject X and Subject Y. Table 1 shows the training environment switching time matrix for different subjects.

[0049] Table 1. Time matrix for switching training environments of different subjects (seconds)

[0050] Course Name A B C D E F X Y A 0 20 28 25 22 5 18 30 B 14 0 10 20 40 32 26 19 C 21 16 0 3 23 21 34 42 D 13 19 8 0 9 22 15 30 E 10 27 19 24 0 25 32 29 F 13 18 26 15 22 0 10 27 X 17 27 21 23 40 35 0 6 Y 38 16 19 31 33 29 13 0

[0051] The table above shows a matrix of training environment switching times generated by sequencing eight training courses. This matrix demonstrates that different course sequences produce different switching times, and that the duration of these switching activities is closely related to the seats, services, and data resources required by the training courses. Different training course sequencing results in different training environment switching times. Rescheduling training courses with similar resource requirements can reduce switching activities and effectively shorten training environment switching time.

[0052] In step 1.2, the training courses with high resource similarity are arranged as follows:

[0053] Step 1.2.1: Format description of training subject resources

[0054] Training subject resources are expressed in a formatted manner, such as Figure 3 Training subject resources are primarily composed of application resources, service resources, and data resources. Application resources primarily include application software for training planning, command and control, process monitoring, data collection, and assessment and evaluation. Service resources primarily include services such as data transmission, geographic information, knowledge extraction, scenario simulation, and special situation handling. Data resources primarily include basic training data such as friendly forces, enemy forces, battlefield environments, and models; training process data such as situation, command, action, and support; and training command and evaluation data such as training scenarios, command and control, and evaluation results.

[0055] Step 1.2.2, training resource feature matrix generation

[0056] The training resource feature matrix generation refers to assigning a value to each element of the resource feature area obtained in step 1.2.1 according to the actual training task requirements. The value assigned to the corresponding subject resource is 1, and the value assigned to the non-existent subject resource is 0. The training resource feature matrix is represented as

[0057] Step 1.2.3: Optimal ranking of training courses based on training resource feature matrix

[0058] First, use the norm formula to calculate the deviation value of the resource feature matrix of the current training course and the next training course. Then traverse the training courses, sort all the deviation values after traversal, and rearrange the training courses with the smallest deviation value, that is, the highest resource similarity. The deviation value calculation formula is as follows:

[0059] D ij =‖A i -B j ‖ 2 (i=1,2,…,S; j=1,2,…,S)

[0060] Among them, D ij is the deviation value of the resource feature matrix between the current training course and the next training course, A i is the resource feature matrix of the current training course, B j is the resource feature matrix of the next training course, S is the complete set of training courses, i is the current training course number, and j is the next training course number.

[0061] Calculations show that while Courses C and D require similar resources, their switching time is shorter, and the switching time between Courses A and F is also shorter. However, due to the different technical architectures used, the switching time required for individual and group training is longer.

[0062] In step 1.2, the optimal course sequence is obtained with the shortest training environment switching waiting time as the constraint:

[0063] The training courses in the training course set S are s1, s2, s3, ..., s H-1 ,s H , H represents the number of training subjects; the training sequence of subjects is recorded as: s1, s2, s3,…, s H-1 ,s H .

[0064] The objective function with the shortest waiting time for training environment switching as the constraint is expressed as:

[0065]

[0066] Among them, T represents the total time consumed by switching between all training subjects; and The time required to switch from the current training course to the next training course respectively;

[0067] In order to optimize the objective function, the following constraints are required:

[0068] Each training course must and can only be switched once, i.e. s1, s2, s3, ..., s H-1 ,s H Not the same;

[0069] The last training course does not need to be switched, so the value of a row and column of the matrix is 0, that is,

[0070] The training courses with high similarity in terms of objective function, constraints and resources are arranged together to obtain the optimal course sequence.

[0071] Taking the 8 types of training subjects in the table above as an example, the objective function is expressed as:

[0072] T=min(T ij +T jk +T kl +T lm +T mn +T no +T op +T pp )

[0073] Where T represents the total time consumed in switching between the eight types of training courses; i, j, k, l, m, n, o, and p are the training course numbers; T ij 、T jk 、T kl 、T lm 、T mn 、T no 、T op The time required to switch from the current training course to the next training course.

[0074] In order to optimize the objective function, the following constraints are required:

[0075] (1) Each training course must and can only be switched once, then:

[0076] i,j,k,l,m,n,o,p∈S and i≠j≠k≠l≠m≠n≠o≠p

[0077] (2) The last training subject does not need to be switched, so the value of a row and column of the matrix is 0, that is, T pp =0.

[0078] Calculate the known objective function

[0079] T=T BC +T CD +T DE +T EA +T AF +T FX +T XY+T YY

[0080] =10+3+9+10+5+10+6+0=53 (seconds)

[0081] The training order of the subjects is rearranged as follows: Subject B, Subject C, Subject D, Subject E, Subject A, Subject F, Subject X and Subject Y.

[0082] Step 2: Backend resource reorganization

[0083] According to the sequence and content of the courses, the backend relies on application clusters, container scheduling and data source switching technologies to quickly build and orchestrate backend services, dynamically reorganize data resources, and provide support for front-end applications.

[0084] For different training content, such as individual training and joint training, backend resource reorganization adopts different construction methods to meet training needs. In the individual training model, relying on the container cloud on the support server, multiple sets of minimal system operating environments that meet training requirements are built. Each minimal system operating environment can support training for one trainee. In the joint training environment, the actual system technology architecture is adopted. The core and basic application services of the actual system technology architecture run on the core basic server, hosted by a lightweight service cluster, and the supporting application services run on the container cloud of the support server. This builds a complete training system to support training for all trainees.

[0085] Normally, software developers use packaging tools to uniformly package the training environment backend service software into two forms: images and software installation packages, and upload them to the image repository and software repository respectively.

[0086] During training, according to the sequence of training courses, before the start of each course training, the resources that are no longer needed in the operating environment of the previous course are automatically stopped and withdrawn. According to the training resource configuration plan of each course group, the construction method of the operating environment is automatically identified. When the actual system technical architecture is used in the overall personnel training environment, the core basic server automatically downloads the software installation package of the core basic application service from the software warehouse for installation and deployment, and the container cloud automatically creates supporting application service instances, completes the configuration of service resources such as various applications and databases, and injects hypothetical data, and starts the application cluster and application service containers in the container cloud; when the container cloud is used to build multiple sets of minimal system operating environments in the single-personnel training mode, the service images required for the training courses are automatically extracted, and the required application service instances and database instances are automatically created on the container cloud. The configuration of service resources such as various applications and databases, and the injection of hypothetical data are completed, and the application service containers in the container cloud are started, so as to quickly build multiple sets of minimal systems that meet the training needs, support each trainee to carry out training without interference at the same time, and quickly build such as Figure 4 shown.

[0087] Step 3: Front-end application orchestration

[0088] Based on the relationship between users, permissions and software, lightweight client integration technology is used to quickly integrate and orchestrate front-end applications to meet the training requirements of different users.

[0089] Relying on the functional modules of QT (QtCore, QtGui, QStyle and QtNetwork, etc.), Poco (Foundation and Util, etc.) and Java (net, io and util, etc.), a lightweight client integration architecture is built, including the basic function layer, the framework extension function layer and the application support function layer, such as Figure 2 As shown. Among them, the basic function layer mainly provides various plug-in integrations based on the Poco module for the general client software integration architecture, such as executable program plug-ins, dynamic library plug-ins, web page plug-ins, etc. At the same time, it has functions such as full life cycle management, attribute management and process keep-alive of executable program plug-ins and dynamic library plug-ins; the framework extension function layer mainly provides functional extensions for the general client software integration architecture, such as plug-in message management, plug-in status monitoring, display layout customization, shortcut buttons and menu arrangement, display resolution adaptation, interface style management and one-key switching, etc., and provides network transmission interfaces and data access interfaces to support secondary development; the application support function layer mainly provides support capabilities for application plug-ins and application systems, such as traffic lights and user login management, which can be expanded according to application needs in the future.

[0090] Different training courses utilize different client applications (application resources), and participants are provided with corresponding client applications based on the training course. All client applications for the training environment are deployed at each training seat and centrally managed, providing a unified launch portal. The application resources required for the training course are matched based on user identity, the current training course, and pre-set training course knowledge rules. Based on a lightweight interface integration architecture, the corresponding function menu is switched to quickly load and run the training environment.

[0091] As can be seen from the above, the method of this embodiment constructs a switching time matrix, optimizes the course arrangement, realizes one-click rapid switching of training content and dynamic reorganization of training resources, and solves the long-standing problem that traditional manual deployment and configuration switching are inefficient and prone to errors, making it difficult to flexibly organize training. The training environment switching time only takes about 1 minute, greatly improving training efficiency and effectiveness.

[0092] In a specific implementation, the present application provides a computer storage medium and a corresponding data processing unit, wherein the computer storage medium is capable of storing a computer program, and when the computer program is executed by the data processing unit, it can run the invention content of the method for one-click switching of training environments for different training contents provided by the present invention and some or all steps of each embodiment. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0093] Those skilled in the art can clearly understand that the technical solutions in the embodiments of the present invention can be implemented by means of computer programs and their corresponding general hardware platforms. Based on this understanding, the technical solutions in the embodiments of the present invention, in essence or in other words, the part that contributes to the prior art, can be embodied in the form of a computer program, i.e., a software product. The computer program software product can be stored in a storage medium and includes a number of instructions for enabling a device including a data processing unit (which can be a personal computer, server, single-chip microcomputer, MUU or network device, etc.) to execute the methods described in various embodiments of the present invention or certain parts of the embodiments.

[0094] The present invention provides a one-touch switching method for training environments with different training contents. There are many methods and approaches to implement this technical solution. The above is only a specific embodiment of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and such improvements and modifications should also be considered within the scope of protection of the present invention. Any components not specified in this embodiment may be implemented using existing technologies.

Claims

1. A one-touch switching method for training environments with different training contents, characterized in that: The following steps are involved: Step 1: Optimize the arrangement of courses. According to the training task requirements and based on the preset training course knowledge rules, establish a training course switching time matrix and calculate the optimal course sequence; Step 2: Backend resource reorganization: Based on the course sequence and content, the backend relies on application clusters, container scheduling, and data source switching technologies to quickly build and orchestrate backend services and dynamically reorganize data resources. Step 3: Orchestrate front-end applications. Based on the relationship between users, permissions, and software, lightweight client integration technology is used to integrate and orchestrate front-end applications. The step 1 includes: step 1.1, according to the preset training course knowledge rules and training content, obtaining the application resources, service resources and data resources required for each training course; Step 1.2: Based on the switching time between each training course and another, a switching time matrix is established. Training courses with high resource similarity are arranged, and the optimal course sequence is obtained with the shortest training environment switching waiting time as the constraint. In step 1.2, the training courses with high resource similarity are arranged as follows: Step 1.2.1: Format the description of training course resources. Training course resources are described in a formatted manner and consist of application resources, service resources, and data resource feature areas. Application resources include training planning, command and control, process monitoring, data collection, and assessment and evaluation application software. Service resources include data transmission, geographic information, knowledge extraction, scenario simulation, and special situation handling services. Data resources include basic training data for our side, enemy, battlefield environment, and models; situation, command, action, and support training process data; and training scenario, command and control, and evaluation results training command and evaluation data. Step 1.2.2: Generate the training resource feature matrix. The training resource feature matrix generation means assigning a value to each element of the resource feature area obtained in step 1.2.1 according to the actual training task requirements. The value assigned to the corresponding subject resource is 1, and the value assigned to the non-existent subject resource is 0. The training resource feature matrix is expressed as Step 1.2.3: Optimal sorting of training courses based on the training resource feature matrix. First, use the norm formula to calculate the deviation between the resource feature matrix of the current training course and the next training course. Then, traverse the training courses and sort all the deviation values after traversal. Rearrange the training courses with the smallest deviation value, that is, the highest resource similarity. The deviation calculation formula is as follows: D ij =‖A i -B j || 2 (i=1,2,…,S;j=1,2,…,S) Among them, D ij is the deviation value of the resource feature matrix between the current training course and the next training course, A i is the resource feature matrix of the current training course, B j is the resource feature matrix of the next training course, S is the complete set of training courses, i is the current training course number, and j is the next training course number.

2. The one-key switching method for training environments with different training contents according to claim 1, characterized in that: The training courses in step 1.1 include individual personnel training courses and overall personnel training courses. The switching time matrix described in step 1.2 reflects that different switching times are generated in different course sequences, and the length of the switching time is closely related to the seat resources, service resources and data resources required for the training courses.

3. The one-touch switching method for training environments with different training contents according to claim 2, characterized in that: In step 1.2, the optimal course sequence is obtained with the shortest training environment switching waiting time as the constraint: The training courses in the training course set S are s1, s2, s3, ..., s H-1 ,s h , H represents the number of training subjects; the training sequence of subjects is recorded as: s1, s2, s3,…, s H-1 ,s H ; The objective function with the shortest waiting time for training environment switching as the constraint is expressed as: Among them, T represents the total time consumed by switching between all training subjects; and The time required to switch from the current training course to the next training course respectively; In order to optimize the objective function, the following constraints are required: Each training course must and can only be switched once, i.e. s1, s2, s3, ..., s H-1 ,s H Not the same; The last training course does not need to be switched, so the value of a row and column of the matrix is 0, that is, The training courses with high similarity in terms of objective function, constraints and resources are arranged together to obtain the optimal course sequence.

4. The one-key switching method for training environments with different training contents according to claim 3, characterized in that: In the step 2: for the different training contents of individual personnel training and overall personnel training, the background resource reorganization adopts different construction methods to meet the training needs: in the individual personnel training mode, relying on the container cloud on the supporting server, build multiple sets of minimal system operating environments that meet the training needs, and each set of minimal system operating environments can support one training seat to carry out training; in the overall personnel training environment, adopt the actual system technology architecture, and the core and basic application services of the actual system technology architecture run on the core basic server, hosted by the lightweight service cluster, and the supporting application services run on the container cloud of the supporting server, thereby building a complete training system to support all training seats to carry out training.

5. The one-key switching method for training environments with different training contents according to claim 4, characterized in that: The step 2 includes: the software developer uses a packaging tool to uniformly package the backend service software into two forms: an image and a software installation package, and uploads them to the image warehouse and the software warehouse respectively; During training, according to the order of training courses, before the start of each course training, the system automatically stops and withdraws resources that are no longer needed in the previous course's operating environment. According to the training resource configuration plan for each course group, the system automatically identifies the construction method of the operating environment and constructs it.

6. The one-key switching method for training environments with different training contents according to claim 5, characterized in that: The automatic identification and construction of the operating environment in step 2 include: when the actual system technology architecture is adopted in the overall personnel training environment, the core basic server automatically downloads the software installation package of the core basic application service from the software warehouse for installation and deployment, and the container cloud automatically creates the supporting application service instance, completes the resource configuration of each application and database service and the injection of hypothetical data, and starts the application cluster and the application service container in the container cloud.

7. The one-key switching method for training environments with different training contents according to claim 6, characterized in that: The automatic identification and construction of the operating environment construction method in step 2 also includes: when using the container cloud to build multiple sets of minimal system operating environments in the single-personnel training mode, automatically extracting the service images required for the training courses, automatically creating the required application service instances and database instances on the container cloud, completing the resource configuration of each application and database service and the injection of hypothetical data, starting the application service container in the container cloud, and building multiple sets of minimal systems that meet the training needs, supporting each trainee to carry out training without interference at the same time.

8. The one-key switching method for training environments with different training contents according to claim 7, characterized in that: The step 3 includes: Relying on the functional modules of QT, Poco and Java, a lightweight client integration architecture is constructed, including the basic function layer, the framework extension function layer and the application support function layer. Among them, the basic function layer provides plug-in integration based on the Poco module for the general client software integration architecture; the framework extension function layer provides functional extension for the general client software integration architecture; and the application support function layer provides support capabilities for application plug-ins and application systems. The client application software used in different training courses is different, and corresponding client application software is provided to trainees according to the training courses; all client application software of the training environment are deployed in all training seats, and they are managed uniformly, providing a unified startup entrance; according to the user identity, current training course and preset training course knowledge rules, the application resources required for this training course are matched, and the corresponding function menu is switched to complete the rapid loading and operation of the training environment.

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