An open software-defined satellite system scientific and technological innovation training platform and its application

Abstract

The present invention relates to the technical field of software defined network, and specifically discloses an open software defined satellite system science and technology innovation training platform and its application. A target user obtains a scene selection list from a historical database, selects a first application scene from the scene selection list, and obtains a second application scene by customizing the first application scene; the second application scene and the first application scene are respectively written into a science and technology innovation training module as uploaded files, and a standard simulation scheme is obtained by performing standardization processing in the science and technology innovation training module; a scene simulation evaluation value of the standard simulation scheme is calculated by a preset evaluation function, and an application scene with a high scene simulation evaluation value is selected as a target application scene; simulation training is performed on the target application scene in different servers to obtain a satellite simulation data set; the satellite simulation data set is summarized and updated to the historical database, and the scene selection list is automatically updated according to the actual needs of the target user.

Description

Technical Field

[0001] The present invention relates to the technical field of software-defined networks, and more specifically, to an open software-defined satellite system scientific and technological innovation training platform and its application. Background Art

[0002] Software-defined satellites are a new generation of intelligent satellites that use space-based supercomputing platforms as their core, adopt an open system architecture, have aerospace application stores and open source software ecosystems, support plug-and-play payloads, on-demand loading of application software, and dynamic reconstruction of system functions. Various sensors and actuators are connected as a whole through software, and most satellite functions are ultimately software-based. Therefore, it is necessary to provide a highly integrated and feature-rich open software-defined satellite system scientific and technological innovation training platform that provides a comprehensive satellite software development and training environment. Therefore, most software operating procedures have the disadvantages of complex logic and large processing resource usage, and the data collection and transmission logic is messy and there is no unified standard, which easily leads to problems such as high system failure rate and slow processing speed, and subsequent maintenance and upgrades are more troublesome.

[0003] For example, the Chinese patent application number is: CN115830700A, which provides a federated learning training platform and training method for wireless sensing scenarios; it allows multiple participants to jointly conduct model training without sharing original data to protect the user's privacy information. At the same time, distributed model training increases potential multi-domain training samples and improves the generalization performance of machine learning models. The existing scientific and technological innovation training platform also needs to meet the sharing of multiple participants. If the content on the platform is templated, it will increase the difficulty of sharing data, resulting in a poor experience for the participants. If templates are not used, the platform data will be too complicated, which is not conducive to beginners to learn; with the increase in the number of platform services and users, it is difficult to meet the real-time nature of the data when processing large-scale data sets and high-concurrency requests. Therefore, the interaction between network transmission data and control data is standardized to facilitate users to understand and use all functions.

[0004] In view of this, the present invention provides an open software-defined satellite system scientific and technological innovation training platform and its application to solve the above problems. Summary of the invention

[0005] In order to overcome the problems in the prior art, the present invention proposes an open software-defined satellite system scientific and technological innovation training platform and its application.

[0006] In a first aspect, the present invention provides an open software-defined satellite system science and technology training platform, including a target confirmation module, a scene import module, a target acquisition module, a server cluster and a cloud server, and each module is connected by wire or wirelessly;

[0007] The target confirmation module, the target user obtains a scene selection list from the historical database, selects a first application scene from the scene selection list, performs custom settings on the basis of the first application scene to obtain a second application scene, and sends the second application scene and the first application scene to the scene import module;

[0008] The scenario import module writes the second application scenario and the first application scenario as uploaded files into the science and technology innovation training module respectively, performs standardization processing in the science and technology innovation training module to obtain a standard simulation solution; and sends the standard simulation solutions corresponding to the second application scenario and the first application scenario to the target acquisition module;

[0009] A target acquisition module takes the standard simulation scheme as an input element, calculates the scenario simulation evaluation value of the standard simulation scheme through a preset evaluation function, selects an application scenario with a high scenario simulation evaluation value as a target application scenario, and sends the target application scenario to a server cluster;

[0010] The server cluster initiates a simulation training request based on the target application scenario. After the training permission restriction is lifted, simulation training is performed on the target application scenario in different servers to obtain a satellite simulation data set, and the satellite simulation data set is sent to the cloud server.

[0011] The cloud server aggregates the satellite simulation data set and updates it to the historical database, automatically updating the scene selection list according to the actual needs of the target users.

[0012] As a first aspect of the present invention, a preferred technical solution is provided, wherein the acquisition logic of the second application scenario is:

[0013] Collect the user's identity information in advance, and obtain the target user through credit authorization based on the identity information. The target user extracts the historical matching application scenarios that match the identity information from the historical database, and displays all the historical matching application scenarios through the scenario selection list;

[0014] The target user queries the scenario selection list, selects the application scenario with the highest matching degree, marks it as the first application scenario, and obtains the historical user demand for the first application scenario;

[0015] The historical user demands are repeatedly deleted according to the pre-set custom options, and the dynamically recommended application simulation scenarios are viewed in real time during the corresponding interactive operations by repeated deletions until the application simulation scenario that satisfies the user is selected, and the application simulation scenario that satisfies the user is marked as the second application scenario.

[0016] As a first aspect of the present invention, a preferred technical solution is provided, wherein the update logic of the first application scenario is:

[0017] The crawler identifies user behavior data during the interactive operation process; analyzes user needs again based on the user behavior data, re-matches the application scenarios in the scenario selection list based on the user needs, and updates the application scenario with the highest matching degree as the first application scenario.

[0018] As a first aspect of the present invention, a preferred technical solution is provided, wherein the acquisition logic of the standard simulation solution is:

[0019] Based on the scientific and technological innovation training module, the uploaded file is sliced ​​into blocks to obtain scene file information, and the scene file information is sorted through a standard scene template to obtain a standard scene file;

[0020] Based on the standard scene file matching standardized slicing simulation scheme, the standardized slicing scheme is assembled into a standard simulation scheme in the order of uploaded files.

[0021] As a first aspect of the present invention, a preferred technical solution is provided, wherein the application logic of the preset evaluation function is:

[0022] The file block information in the standard simulation scheme is used as the input of a preset evaluation function, the preset evaluation function takes the predicted scenario simulation evaluation value of the standard simulation scheme as the output, takes the user expectation value of the target user for the target application scenario simulation as the prediction target, and takes minimizing the sum of the prediction errors of all scenario simulation evaluation values ​​and user expectation values ​​as the training target; the preset evaluation function is trained until the sum of the prediction accuracies reaches convergence and the training is stopped; the preset evaluation function is any one of a deep neural network model or a deep belief network model.

[0023] As a first aspect of the present invention, a preferred technical solution is provided, in which the server cluster 4 temporarily combines at least one of the servers that establish communication with the local server to build a regional server, and at least one of the servers in the regional server cooperates to perform simulation training, and obtains satellite simulation data marked by different servers in turn based on the target application scenario.

[0024] As a first aspect of the present invention, a preferred technical solution is provided, wherein the historical database includes a Redis database, and the satellite simulation data set is sliced ​​based on the Redis database to obtain file block information corresponding to the target application scenario, and the scene selection list is updated based on the file block information, and the application scenario is selected according to the scene selection list, and the file integrity is integrated and verified.

[0025] In a second aspect, the present invention provides an application method of an open software-defined satellite system scientific innovation training platform, based on the implementation of the first aspect, comprising the following steps:

[0026] The target user obtains a scene selection list from a historical database, selects a first application scene from the scene selection list, and performs custom settings based on the first application scene to obtain a second application scene;

[0027] Writing the second application scenario and the first application scenario as uploaded files into the science and technology innovation training module respectively, and performing standardization processing in the science and technology innovation training module to obtain a standard simulation solution;

[0028] The standard simulation scheme is used as an input element, a scene simulation evaluation value of the standard simulation scheme is calculated by a preset evaluation function, and an application scene with a high scene simulation evaluation value is selected as a target application scene;

[0029] Initiate a simulation training request based on the target application scenario, and after removing the training permission restriction, perform simulation training on the target application scenario based on different servers to obtain a satellite simulation data set;

[0030] The satellite simulation data set is aggregated and updated to the historical database, and the scene selection list is automatically updated according to the actual needs of the target users.

[0031] In a third aspect, the present invention provides an electronic device, comprising:

[0032] at least one processor; and,

[0033] A memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor so that the at least one processor can execute the system of the first aspect.

[0034] In a fourth aspect, the present invention provides a computer-readable storage medium storing instructions, which, when executed on a computer, enable the computer to execute the system of the first aspect.

[0035] The specific advantages of the present invention are as follows:

[0036] The present invention realizes efficient simulation training and evaluation of satellite application scenarios through automated processes and standardized processing, provides users with the right to choose independently, and intelligently analyzes user behavior, advancing in both directions, and understanding users' real needs more efficiently and accurately. It can also increase users' understanding and application of the training platform and improve the efficiency of satellite system development. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a schematic diagram of the framework structure of the training platform of the present invention;

[0038] Figure 2 It is a schematic diagram of the application method of the training platform of the present invention;

[0039] Figure 3 It is a schematic diagram of the structure of the electronic device of the present invention.

[0040] In the figure, 1. Target confirmation module; 2. Scene import module; 3. Target acquisition module; 4. Server cluster; 5. Cloud server; DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] Example 1: Please refer to Figure 1 ,The present invention provides a technical solution: an open software-defined satellite system science and technology training platform, a target confirmation module 1, a scene import module 2, a target acquisition module 3, a server cluster 4 and a cloud server 5, and each module is connected by wire or wireless;

[0043] Target confirmation module 1, the target user obtains a scene selection list from a historical database, selects a first application scene from the scene selection list, and performs custom settings on the basis of the first application scene to obtain a second application scene;

[0044] It should be noted that: in actual applications, because different users have different scientific and technological innovation purposes in choosing satellite systems, matching application scenarios according to the adaptability of target users can reduce user errors and improve user experience; if aerospace engineering students want to understand satellite orbit simulation applications through the training platform, they can select the first application scenario as the satellite orbit simulation scenario, which includes the current satellite orbit position, the earth's gravity field model and other astrophysical data; aerospace engineering students can simulate different orbital maneuvers by defining orbital parameters, including orbital altitude, inclination and orbital shape, and orbital maneuvers include orbit change and orbit maintenance; they can also design and test attitude control algorithms to simulate the attitude control state of the satellite during movement.

[0045] Specifically, the target users include students, researchers and aerospace practitioners; user needs include simulation control of satellite orbit and attitude, analysis and processing of remote sensing data, acquisition of satellite communication links and aerospace mission planning training;

[0046] The acquisition logic of the second application scenario:

[0047] Collect the user's identity information in advance, and obtain the target user through credit authorization based on the identity information. The target user extracts the historical matching application scenarios that match the identity information from the historical database, and displays all the historical matching application scenarios through the scenario selection list;

[0048] The target user queries the scenario selection list, selects the application scenario with the highest matching degree, marks it as the first application scenario, and obtains the historical user demand for the first application scenario;

[0049] The historical user needs are repeatedly deleted according to the preset custom options, and the dynamically recommended application simulation scenarios are viewed in real time in the corresponding interactive operations by repeatedly deleting them until the application simulation scenario that the user is satisfied with is selected, and the application simulation scenario that the user is satisfied with is marked as the second application scenario;

[0050] It should be noted that the second application scenario is an application scenario selected by the target user based on the on-site matching data. However, it should be taken into account that the target user may be affected by external factors or misleading indication information in actual operation. The second application scenario selected independently is not the target user's own demand.

[0051] The crawler identifies user behavior data during the interactive operation process; analyzes user needs again based on the user behavior data, re-matches the application scenarios in the scenario selection list based on the user needs, and updates the application scenario with the highest matching degree as the first application scenario.

[0052] It should be noted that there is a question here: whether the target user can select any application scenario from the scenario selection list as the first application scenario. After all, after selecting the first application scenario, you can also customize the options, so is the step of selecting the first application scenario necessary? In fact, this step is designed mainly to consider the user interaction experience; especially for the experiencer, as follows:

[0053] During the user identity information collection stage, it is necessary to collect the user's identity information in advance. The more comprehensive the user's identity information is, the higher the matching degree will be when combined with the user's credit. The higher the matching degree, the closer the scene selection list obtained is to the user's real needs, ensuring that the user can quickly access platform information.

[0054] However, if all historical matching application scenarios are too complicated, it is necessary to provide users with a preliminary selection range, query the scenario selection list, and filter according to keywords, tags or categories. Users select the first application scenario to provide a reference point to help understand possible options and customization directions. Continue to try and adjust until a satisfactory application simulation scenario is found, simplify the user's selection process, and avoid feeling overwhelmed by a large number of options; to ensure that the final scenario meets the user's actual needs.

[0055] The scenario import module 2 writes the second application scenario and the first application scenario as uploaded files into the science and technology innovation training module respectively, performs standardization processing in the science and technology innovation training module to obtain a standard simulation solution; and sends the standard simulation solutions corresponding to the second application scenario and the first application scenario to the target acquisition module 3;

[0056] Specifically, the acquisition logic of the standard simulation scheme is:

[0057] Based on the scientific and technological innovation training module, the uploaded file is sliced ​​into blocks to obtain scene file information, and the scene file information is sorted through a standard scene template to obtain a standard scene file;

[0058] Based on the standard scene file matching standardized slicing simulation scheme, the standardized slicing scheme is assembled into a standard simulation scheme in the order of uploaded files.

[0059] It should be noted that: when the target user uploads the second application scenario and the first application scenario, the uploaded file is sliced ​​into blocks to obtain the scenario file information and saved in the historical database, turning the uploaded file from a large whole into multiple small file blocks. The science and technology training module obtains multiple file blocks at the same time at a smaller granularity, standardizes the file blocks, reduces the difficulty of operation, and can also retain more details, which are finally assembled into a large file, and then the scenario simulation evaluation value of the large file is evaluated, which is more convincing.

[0060] The target acquisition module 3 takes the standard simulation scheme as a parameter, calculates the scenario simulation evaluation value of the standard simulation scheme through a preset evaluation function, selects an application scenario with a high scenario simulation evaluation value as a target application scenario, and sends the target application scenario to the server cluster 4.

[0061] Specifically, the application logic of the preset evaluation function is:

[0062] The file block information in the standard simulation scheme is used as the input of a preset evaluation function, the preset evaluation function takes the predicted scenario simulation evaluation value of the standard simulation scheme as the output, takes the user expectation value of the target user for the target application scenario simulation as the prediction target, and takes minimizing the sum of the prediction errors of all scenario simulation evaluation values ​​and user expectation values ​​as the training target; the preset evaluation function is trained until the sum of the prediction accuracies reaches convergence and the training is stopped; the preset evaluation function is any one of a deep neural network model or a deep belief network model.

[0063] Server cluster 4 initiates a simulation training request based on the target application scenario, and after removing the training authority restriction, performs simulation training on the target application scenario based on different servers to obtain a satellite simulation data set, and sends the satellite simulation data set to cloud server 5;

[0064] Specifically, the server cluster 4 temporarily combines at least one of the servers that establish communication with the local server to build a regional server, and at least one of the servers in the regional server cooperates to perform simulation training, and obtains satellite simulation data marked by different servers in turn based on the target application scenario.

[0065] The cloud server 5 aggregates the satellite simulation data set and updates it to the historical database, and automatically updates the scene selection list according to the actual needs of the target users.

[0066] Specifically, the historical database includes a Redis database, based on which the satellite simulation data set is sliced ​​to obtain file block information corresponding to the target application scenario, the scene selection list is updated based on the file block information, the application scenario is selected according to the scene selection list, and the file integrity is integrated and verified.

[0067] Example 2: Figure 2 As shown, the part not described in detail in this embodiment is as shown in Example 1. This embodiment provides an application method of an open software-defined satellite system science and technology training platform, including the following steps:

[0068] The target user obtains a scene selection list from a historical database, selects a first application scene from the scene selection list, and performs custom settings based on the first application scene to obtain a second application scene;

[0069] Writing the second application scenario and the first application scenario as uploaded files into the science and technology innovation training module respectively, and performing standardization processing in the science and technology innovation training module to obtain a standard simulation solution;

[0070] The standard simulation scheme is used as an input element, a scene simulation evaluation value of the standard simulation scheme is calculated by a preset evaluation function, and an application scene with a high scene simulation evaluation value is selected as a target application scene;

[0071] Initiate a simulation training request based on the target application scenario, and after removing the training permission restriction, perform simulation training on the target application scenario based on different servers to obtain a satellite simulation data set;

[0072] The satellite simulation data set is aggregated and updated to the historical database, and the scene selection list is automatically updated according to the actual needs of the target users.

[0073] The acquisition logic of the second application scenario:

[0074] Collect the user's identity information in advance, and obtain the target user through credit authorization based on the identity information. The target user extracts the historical matching application scenarios that match the identity information from the historical database, and displays all the historical matching application scenarios through the scenario selection list;

[0075] The target user queries the scenario selection list, selects the application scenario with the highest matching degree, marks it as the first application scenario, and obtains the historical user demand for the first application scenario;

[0076] The historical user demands are repeatedly deleted according to the pre-set custom options, and the dynamically recommended application simulation scenarios are viewed in real time during the corresponding interactive operations by repeated deletions until the application simulation scenario that satisfies the user is selected, and the application simulation scenario that satisfies the user is marked as the second application scenario.

[0077] The update logic of the first application scenario is:

[0078] The crawler identifies user behavior data during the interactive operation process; analyzes user needs again based on the user behavior data, re-matches the application scenarios in the scenario selection list based on the user needs, and updates the application scenario with the highest matching degree as the first application scenario.

[0079] The acquisition logic of the standard simulation scheme is:

[0080] Based on the scientific and technological innovation training module, the uploaded file is sliced ​​into blocks to obtain scene file information, and the scene file information is sorted through a standard scene template to obtain a standard scene file;

[0081] Based on the standard scene file matching standardized slicing simulation scheme, the standardized slicing scheme is assembled into a standard simulation scheme in the order of uploaded files.

[0082] The application logic of the preset evaluation function:

[0083] The file block information in the standard simulation scheme is used as the input of a preset evaluation function, the preset evaluation function takes the predicted scenario simulation evaluation value of the standard simulation scheme as the output, takes the user expectation value of the target user for the target application scenario simulation as the prediction target, and takes minimizing the sum of the prediction errors of all scenario simulation evaluation values ​​and user expectation values ​​as the training target; the preset evaluation function is trained until the sum of the prediction accuracies reaches convergence and the training is stopped; the preset evaluation function is any one of a deep neural network model or a deep belief network model.

[0084] The server cluster 4 temporarily combines at least one of the servers that establish communication with the local server to build a regional server, and at least one of the servers in the regional server cooperates to perform simulation training, and obtains satellite simulation data marked by different servers in turn based on the target application scenario.

[0085] The historical database includes a Redis database, based on which the satellite simulation data set is sliced ​​to obtain file block information corresponding to the target application scenario, based on the file block information, a scene selection list is updated, an application scenario is selected according to the scene selection list, and file integrity is integrated and verified.

[0086] Example 3: Figure 3 As shown, the parts not described in detail in this embodiment are detailed in Embodiment 1. This embodiment provides an electronic device, including:

[0087] At least one processor; and a memory in communication with the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can perform a real-time microscope focusing method as described above.

[0088] Among them, the memory and the processor are connected in a bus manner, and the bus may include any number of interconnected buses and bridges, and the bus connects various circuits of one or more processors and memories together. The bus can also connect various other circuits such as peripherals, voltage regulators, and power management circuits, which are well known in the art and are therefore not further described herein. The bus interface provides an interface between the bus and the transceiver. The transceiver can be one element or multiple elements, such as multiple receivers and transmitters, providing a unit for communicating with various other devices on a transmission medium. The data processed by the processor is transmitted on a wireless medium via an antenna, and further, the antenna also receives data and transmits the data to the processor.

[0089] The processor is responsible for managing the bus and general processing, and can also provide various functions, including timing, peripheral interfaces, voltage regulation, power management, and other control functions. Memory can be used to store data used by the processor when performing operations.

[0090] Example 4: For details of the parts not described in this example, please refer to Example 1. This example provides a computer-readable storage medium storing instructions. When the instructions are executed on a computer, the computer executes the above-mentioned real-time microscope focusing method.

[0091] That is, those skilled in the art can understand that all or part of the steps in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a program, and the program is stored in a storage medium, including several instructions to enable a device (which can be a single-chip microcomputer, chip, etc.) or a processor to execute all or part of the steps of each embodiment method of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0092] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

[0093] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An open software-defined satellite system scientific and technological innovation training platform, characterized in that: It includes a target confirmation module (1), a scene import module (2), a target acquisition module (3), a server cluster (4) and a cloud server (5), and each module is connected via wired or wireless communication; The target confirmation module (1) obtains a scene selection list from a historical database, selects a first application scene from the scene selection list, performs custom settings based on the first application scene to obtain a second application scene, and sends the second application scene and the first application scene to the scene import module (2); The acquisition logic of the second application scenario: Collect the user's identity information in advance, and obtain the target user through credit authorization based on the identity information. The target user extracts the historical matching application scenarios that match the identity information from the historical database, and displays all the historical matching application scenarios through the scenario selection list; The target user queries the scenario selection list, selects the application scenario with the highest matching degree, marks it as the first application scenario, and obtains the historical user demand for the first application scenario; The historical user needs are repeatedly deleted according to the preset custom options, and the dynamically recommended application simulation scenarios are viewed in real time in the corresponding interactive operations by repeatedly deleting them until the application simulation scenario that the user is satisfied with is selected, and the application simulation scenario that the user is satisfied with is marked as the second application scenario; The update logic of the first application scenario is: The interactive operation process is used by crawlers to identify user behavior data; Analyze user needs again based on user behavior data, re-match the application scenarios in the scenario selection list based on user needs, and update the application scenario with the highest matching degree as the first application scenario; The scenario import module (2) writes the second application scenario and the first application scenario as upload files into the science and technology innovation training module respectively, performs standardization processing in the science and technology innovation training module to obtain a standard simulation solution; and sends the standard simulation solution corresponding to the second application scenario and the first application scenario to the target acquisition module (3); A target acquisition module (3) takes the standard simulation scheme as an input element, calculates a scenario simulation evaluation value of the standard simulation scheme through a preset evaluation function, selects an application scenario with a high scenario simulation evaluation value as a target application scenario, and sends the target application scenario to a server cluster (4); The server cluster (4) initiates a simulation training request based on the target application scenario, and after removing the restriction on the training authority, performs simulation training on the target application scenario in different servers to obtain a satellite simulation data set, and sends the satellite simulation data set to the cloud server (5); The cloud server (5) aggregates the satellite simulation data set and updates it to the historical database, and automatically updates the scene selection list according to the actual needs of the target users.

2. The open software-defined satellite system scientific innovation training platform according to claim 1, characterized in that: The acquisition logic of the standard simulation scheme is: Based on the scientific and technological innovation training module, the uploaded file is sliced ​​into blocks to obtain scene file information, and the scene file information is sorted through a standard scene template to obtain a standard scene file; Based on the standard scene file matching standardized slicing simulation scheme, the standardized slicing scheme is assembled into a standard simulation scheme in the order of uploaded files.

3. The open software-defined satellite system scientific innovation training platform according to claim 2, characterized in that: The application logic of the preset evaluation function: The file block information in the standard simulation scheme is used as the input of a preset evaluation function, the preset evaluation function takes the predicted scenario simulation evaluation value of the standard simulation scheme as the output, takes the user expectation value of the target user for the target application scenario simulation as the prediction target, and takes minimizing the sum of the prediction errors of all scenario simulation evaluation values ​​and user expectation values ​​as the training target; The preset evaluation function is trained until the sum of the prediction accuracies reaches convergence and the training is stopped; the preset evaluation function is any one of a deep neural network model or a deep belief network model.

4. The open software-defined satellite system scientific innovation training platform according to claim 3, characterized in that: The server cluster (4) temporarily combines at least one of the servers that establish communication with the local server to form a regional server, and at least one of the servers in the regional server cooperates to perform simulation training, and sequentially obtains satellite simulation data marked by different servers based on the target application scenario.

5. The open software-defined satellite system scientific innovation training platform according to claim 4, characterized in that: The historical database includes a Redis database, based on which the satellite simulation data set is sliced ​​to obtain file block information corresponding to the target application scenario, based on the file block information, a scene selection list is updated, an application scenario is selected according to the scene selection list, and file integrity is integrated and verified.

6. An application method of an open software-defined satellite system scientific innovation training platform, based on the implementation of an open software-defined satellite system scientific innovation training platform according to any one of claims 1 to 5, characterized in that: The following steps are involved: The target user obtains a scene selection list from a historical database, selects a first application scene from the scene selection list, and performs custom settings based on the first application scene to obtain a second application scene; Writing the second application scenario and the first application scenario as uploaded files into the science and technology innovation training module respectively, and performing standardization processing in the science and technology innovation training module to obtain a standard simulation solution; The standard simulation scheme is used as an input element, a scene simulation evaluation value of the standard simulation scheme is calculated by a preset evaluation function, and an application scene with a high scene simulation evaluation value is selected as a target application scene; Initiate a simulation training request based on the target application scenario, and after removing the training permission restriction, perform simulation training on the target application scenario based on different servers to obtain a satellite simulation data set; The satellite simulation data set is aggregated and updated to the historical database, and the scene selection list is automatically updated according to the actual needs of the target users.

7. An electronic device, characterized in that: include: at least one processor; as well as, A memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute an open software-defined satellite system scientific and technological innovation training platform as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: Instructions are stored, and when the instructions are executed on a computer, the computer executes an open software-defined satellite system scientific and technological innovation training platform as described in any one of claims 1 to 5.

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