Online evaluation data processing method and device based on real-time simulation deduction

Abstract

The invention provides an online evaluation data processing method and device based on real-time simulation deduction. The method comprises the steps of simulation initialization and scene loading, real-time simulation deduction and data acquisition, data real-time processing and sending and online dynamic evaluation. On the basis of the whole process from simulation deduction to evaluation tuning, real-time simulation data acquisition is achieved, the real-time performance and the high efficiency of online dynamic evaluation are improved, and the data packet loss rate and the time delay are reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of computer simulation and data processing, and particularly relates to an online evaluation data processing method and device based on real-time simulation deduction. BACKGROUND

[0002] In current decision support systems, it is crucial to implement or near real-time evaluation on complex systems. Traditional evaluation methods mostly rely on historical data analysis and static models, which have obvious hysteresis. When the system state changes, it is difficult for traditional methods to update the evaluation results in a timely manner, resulting in outdated decision-making basis and decreased evaluation accuracy.

[0003] In the prior art, there are also some methods that combine simulation and evaluation, which usually have the following defects: Offline processing, simulation and evaluation processes are separated, and simulation produces massive data, which is then analyzed offline by the evaluation system, which cannot meet the needs of real-time decision-making; feedback lag, evaluation results cannot be fed back to the simulation system in real time to dynamically adjust simulation parameters or paths, forming an open-loop system, which reduces the adaptability and prediction accuracy of deduction; low data processing efficiency, lack of real-time cleaning, fusion and feature extraction capabilities for massive, high-dimensional and heterogeneous data generated during simulation, serious data pipeline blockage, affecting overall timeliness; single evaluation dimension, evaluation models are usually static and preset, and it is difficult to dynamically adjust evaluation indicators and weights according to the deduction situation, and the flexibility is insufficient.

[0004] Therefore, there is an urgent need for an integrated solution that can deeply integrate real-time simulation, online data processing and dynamic evaluation. SUMMARY

[0005] The present application provides an online evaluation data processing method and device based on real-time simulation deduction, which realizes the closed-loop linkage of simulation, data processing and evaluation, and improves the real-time performance, accuracy and self-adaptive ability of evaluation.

[0006] The present application provides an online evaluation data processing method based on real-time simulation deduction, comprising: Step one: simulation initialization and scene loading: according to the evaluation target, load the preset simulation deduction file, initialize the simulation engine, configure the entity model, environment model parameters and deduction rules; Step two: real-time simulation deduction and data collection: start the simulation engine, advance the deduction process according to the simulation clock step; simultaneously collect multi-source heterogeneous real-time data generated in the deduction process, standardize and package into JSON format message body, real-time data including entity state data, interaction event data, environment situation data; Step three: Real-time data processing and sending: Create a connection channel for the simulation real-time data collection, send data in real time, and evaluate the tool subscription message queue. Real-time data is listened to, deserialized and processed after listening to the message, and filtered and rearranged. Step four: Online dynamic evaluation: Based on the processed real-time data, input the online evaluation model, and dynamically select or weight multiple evaluation sub-models according to the current deduction stage and situation to generate comprehensive evaluation results. The evaluation results include performance indicators, efficiency indicators, prediction results, and confidence analysis.

[0007] Optionally, in step two, the real-time output of the key structure data by the embedded interface collection component is used as the main data input source of the evaluation system; The JSON format message body contains the timestamp, unique structure ID, structure type identifier and corresponding field value generated by the evaluation system automatically. All structure data is broadcast to the evaluation tool message subscription node through UDP broadcast.

[0008] Optionally, the key structure data includes task status, platform information, sensor report, and weapon effectiveness.

[0009] Optionally, in step three, a multi-threaded non-blocking listening mechanism is used to receive multiple broadcast data sent by the evaluation system simulation node in parallel; The evaluation tool message subscription node based on thread pool technology and lightweight buffer processing framework has the ability to tolerate packet loss when receiving, supports buffer rearrangement and structure verification for out-of-order data, and ensures that the data meets the time consistency and structure integrity before entering the middleware. After the legal data received is re-encapsulated into a standard message format, it is immediately pushed into the RabbitMQ message queue to provide a stable and controllable data flow entrance for subsequent processing links.

[0010] Optionally, in step three, the memory buffer area of the simulation structure is built based on RabbitMQ to realize the decoupling and asynchronous transfer of data between collection and evaluation processing; Each type of structure corresponds to an independent message queue Queue in the buffer area, and the received online evaluation data is automatically distributed based on the structure type field of each queue to ensure that different data types are managed in the system.

[0011] Optionally, the online evaluation data processing method based on real-time simulation deduction comprises: Step five: Real-time feedback and simulation optimization of evaluation results: The evaluation result is presented in real time, the simulation process and the simulation state of the entity model are analyzed, the evaluation result is taken as feedback information, and the behavior strategy, the environment parameter or the deduction rule of the simulation entity is dynamically adjusted to realize closed-loop control of simulation-evaluation-optimization.

[0012] The second aspect of the present application provides an online evaluation data processing device based on real-time simulation deduction, which executes the online evaluation data processing method based on real-time simulation deduction as any one of the first aspect.

[0013] The third aspect of the present application provides a computer readable storage medium, comprising: a memory and a processor. The memory is configured to save executable instructions. The processor is configured to implement the online evaluation data processing method based on real-time simulation deduction as any one of the first aspect when executing the executable instructions saved by the memory.

[0014] The fourth aspect of the present application provides a computer program product, the computer program product comprising instructions which, when executed by a computer, implement the online evaluation data processing method based on real-time simulation deduction as any one of the first aspect.

[0015] The present application provides an online evaluation data processing method and device based on real-time simulation deduction, which constructs a full process based on simulation deduction to evaluation optimization, collects data in real time during simulation, improves the real-time performance and efficiency of online dynamic evaluation, reduces the data packet loss rate and latency, and has the following beneficial effects: 1. High real-time performance: through the streaming processing pipeline and the online evaluation model, millisecond-level delay is realized from data generation to evaluation result output, meeting the needs of high real-time application scenarios.

[0016] 2. Closed-loop adaptability: the mechanism of feeding back the online evaluation result to the simulation process in real time enables the simulation system to adaptively adjust according to the evaluation situation, making the deduction path more intelligent and the prediction result more reliable.

[0017] 3. High processing efficiency: a special real-time preprocessing and feature extraction process is designed according to the characteristics of simulation data, greatly improving the efficiency and effectiveness of data processing.

[0018] 4. Evaluation dynamicity: the evaluation model set can be dynamically adjusted according to the deduction process, making the evaluation dimension more comprehensive and the evaluation conclusion more suitable for the actual stage and target of deduction. BRIEF DESCRIPTION OF DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. The drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0020] Fig. 1 The overall work flow chart of the online evaluation data processing method based on real-time simulation deduction; Fig. 2 The data real-time processing flow chart of the online evaluation data processing method based on real-time simulation deduction. DETAILED DESCRIPTION

[0021] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the following will combine the drawings in the embodiments of the present application to make a clear and complete description of the technical solutions in the embodiments of the present application. Obviously, the described embodiments are some of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the protection scope of the present application.

[0022] The features and illustrative embodiments of various aspects of the present application will be described in detail below. In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the present application. However, it will be apparent to those skilled in the art that the present application can be practiced without some of these specific details. The following description of embodiments is merely provided to give a better understanding of the present application by showing examples of the present application. The present application is in no way limited to any specific settings and methods presented below, but covers any improvements, replacements and modifications of structures, methods and devices without departing from the spirit of the present application. In the drawings and the following description, well-known structures and technologies are not shown to avoid unnecessary obscuring of the present application.

[0023] In the description of the present application, it should be noted that the directions or position relationships indicated by "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer" and the like are based on the directions or position relationships described in the drawings, and are only for the convenience of describing the present application and simplifying the description, and cannot be understood as limiting the present application. In addition, the ordinal numbers (such as "first and second", etc.) are used to distinguish objects, and are not limited to the order, and cannot be understood as indicating or implying relative importance.

[0024] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly, encompassing both direct connection and indirect connection via an intermediate medium. Those skilled in the art can understand the specific meaning of these terms in this invention based on the specific circumstances.

[0025] It should be noted that, unless otherwise specified, the embodiments of the present invention and the features thereof can be combined with each other, and the various embodiments can be referenced and cited in each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0026] The present invention will be further described in detail below with reference to the embodiments and accompanying drawings, but the embodiments of the present invention are not limited thereto.

[0027] like Figs. 1-2 As shown, this invention provides an online evaluation data processing method based on real-time simulation and deduction, comprising: Step 1: Simulation Initialization and Scene Loading: Based on the evaluation objectives, load the preset simulation simulation files, initialize the simulation engine, and configure the parameters of the entity model, environment model, and simulation rules. Step 2: Real-time simulation and data acquisition: Start the simulation engine and advance the simulation process according to the simulation clock step; synchronously acquire multi-source heterogeneous real-time data generated during the simulation process, and standardize and encapsulate it into a JSON format message body. The real-time data includes entity status data, interaction event data, and environmental situation data. Step 3: Real-time data processing and transmission: Create a connection channel for the data collected in real time from the simulation, transmit the data in real time, the evaluation tool subscribes to the message queue, listens for the data in real time, deserializes the data after listening for messages, and performs filtering and data rearrangement. Step 4: Online Dynamic Evaluation: Based on the processed real-time data input into the online evaluation model, the evaluation model dynamically selects or weights and merges multiple evaluation sub-models according to the current simulation stage and situation to generate a comprehensive evaluation result; the evaluation result includes performance indicators, effectiveness indicators, prediction results, and confidence analysis.

[0028] Step 5: Real-time Feedback and Simulation Optimization of Evaluation Results: The evaluation results are visualized in real time, and the simulation process and the simulation state of the entity model are analyzed. The evaluation results are used as feedback information, and the behavior strategies, environmental parameters, or inference rules of the simulated entity are dynamically adjusted to achieve closed-loop control of simulation-evaluation-optimization. For example, when a certain evaluation index is unsatisfactory during simulation, the control variable method can be used to modify the experimental factors one by one, thereby identifying the key experimental factors with the highest relevance and performing targeted optimization.

[0029] Optionally, in step two, the key structure data (such as task status, platform information, sensor report, weapon effectiveness, etc.) output in real time by the embedded interface collection component is used as the main data input source of the evaluation system. All output structures are uniformly converted to standardized JSON format after collection, which includes system-generated timestamp, unique structure ID, structure type identification, and corresponding field values, with good scalability and analyzability. To reduce the load of the simulation main process, all structure data is broadcast to the evaluation tool message subscription node through UDP broadcast, realizing non-connection, non-blocking transmission, with high throughput and low coupling, suitable for fast distribution of data in distributed simulation systems.

[0030] Optionally, in step three, a multi-threaded non-blocking listening mechanism is used to receive multiple broadcast data sent by simulation nodes in parallel. Based on thread pool technology and lightweight buffer processing framework, the system has the ability to tolerate packet loss when receiving, supports buffer rearrangement and structure verification of out-of-order data, and ensures that the data meets the time consistency and structure integrity before entering the middleware. After the received legal data is re-encapsulated into the standard message format, it is immediately pushed into the RabbitMQ message queue to provide a stable and controllable data flow entrance for subsequent processing steps. Optionally, in step three, based on RabbitMQ, an in-memory buffer area of simulation structures is built to decouple and asynchronously transfer data between collection and evaluation processing. Each type of structure corresponds to an independent message queue (Queue) in the buffer area, and the received online evaluation data is automatically distributed based on the queue structure type field (such as StructType), ensuring that different data types are managed separately. This design supports multiple consumers subscribing to the same type of structure in parallel, achieving load balancing and data reuse among evaluation submodules.

[0031] To deal with sudden data write flood during simulation, RabbitMQ internally uses a combination of in-memory queues and disk buffering mechanisms to prioritize hot data caching and prevent message loss due to memory overflow. At the same time, the system supports configuring TTL (Time To Live) parameters and expiration discard policies for each type of message to prevent historical redundant data from entering the evaluation path and affecting processing efficiency and accuracy. Important structures (such as key target status, task results, etc.) support setting message priority and custom routing tags to ensure they are prioritized in message congestion scenarios, improving the evaluation system's response speed and decision-making ability for critical events. The buffer area acts as a "buffer valve" for data control, ensuring simulation performance while effectively ensuring the stability and real-time performance of the evaluation system processing link.

[0032] The application provides an online evaluation data processing method and device based on real-time simulation deduction, which constructs a full process based on simulation deduction to evaluation tuning, collects data in real time, improves the real-time performance and efficiency of online dynamic evaluation, reduces the data packet loss rate and latency, and has the following beneficial effects: 1. High real-time performance: Through the stream processing pipeline and online evaluation model, millisecond-level delay is realized from data generation to evaluation result output, meeting the demand of high real-time application scenarios.

[0033] 2. Closed-loop adaptability: The mechanism of real-time feedback of online evaluation results to the simulation process enables the simulation system to adaptively adjust according to the evaluation situation, making the deduction path more intelligent and the prediction result more reliable.

[0034] 3. High processing efficiency: A special real-time preprocessing and feature extraction process is designed according to the characteristics of simulation data, greatly improving the efficiency and effectiveness of data processing.

[0035] 4. Evaluation dynamicity: The evaluation model set can dynamically adjust according to the deduction process, making the evaluation dimension more comprehensive and the evaluation conclusion more suitable for the actual stage and target of deduction.

[0036] The above specific embodiments are detailed descriptions of the application, which cannot be considered as limiting the specific embodiments of the application to these descriptions. For ordinary skilled persons in the technical field to which the application belongs, some simple deductions and substitutions can be made without departing from the concept of the application, which should be considered as belonging to the protection scope of the application.

Claims

1. An online evaluation data processing method based on real-time simulation and deduction, characterized in that, include: Step 1: Simulation Initialization and Scene Loading: Based on the evaluation objectives, load the preset simulation simulation files, initialize the simulation engine, and configure the parameters of the entity model, environment model, and simulation rules. Step 2: Real-time simulation and data acquisition: Start the simulation engine and advance the simulation process according to the simulation clock step; Multi-source heterogeneous real-time data generated during the simulation process are collected synchronously and standardized and packaged into a JSON format message body. The real-time data includes entity status data, interaction event data, and environmental situation data. Step 3: Real-time data processing and transmission: Create a connection channel for the data collected in real time from the simulation, transmit the data in real time, the evaluation tool subscribes to the message queue, listens for the data in real time, deserializes the data after listening for messages, and performs filtering and data rearrangement. Step 4: Online Dynamic Evaluation: Based on the processed real-time data input into the online evaluation model, the evaluation model dynamically selects or weights and merges multiple evaluation sub-models according to the current simulation stage and situation to generate a comprehensive evaluation result; the evaluation result includes performance indicators, effectiveness indicators, prediction results, and confidence analysis.

2. The online evaluation data processing method based on real-time simulation and deduction according to claim 1, characterized in that, In step two, the key structure data is collected in real time through the embedded interface acquisition component, serving as the main data input source for the evaluation system; The JSON format message body contains a timestamp automatically generated by the evaluation system, a unique structure ID, a structure type identifier, and its corresponding field values; All structure data is broadcast to the evaluation tool message subscription node via UDP broadcast.

3. The online evaluation data processing method based on real-time simulation and deduction according to claim 2, characterized in that, Key structural data include: mission status, platform information, sensor reports, and weapon effectiveness.

4. The online evaluation data processing method based on real-time simulation and deduction according to claim 1, characterized in that, Step 3 employs a multi-threaded non-blocking listening mechanism to receive broadcast data from multiple evaluation system simulation nodes in parallel. The evaluation tool's message subscription node is based on thread pool technology and a lightweight buffer processing framework. It has packet loss tolerance when receiving data and supports buffering, rearranging, and structural verification of out-of-order data to ensure that the data meets time consistency and structural integrity before entering the middleware. After receiving legitimate data, it is repackaged into a standard message format and immediately pushed to the RabbitMQ message queue, providing a stable and controllable data flow entry point for subsequent processing.

5. The online evaluation data processing method based on real-time simulation and deduction according to claim 3, characterized in that, In step three, a memory buffer for the simulation structure is built based on RabbitMQ to achieve decoupling and asynchronous transfer of data between acquisition and evaluation processing; Each type of structure corresponds to an independent message queue in the buffer. The received online evaluation data is automatically distributed based on the structure type field of each queue, ensuring that different data types are managed separately in the system.

6. The online evaluation data processing method based on real-time simulation and deduction according to claim 1, characterized in that, The method also includes: Step 5: Real-time feedback of evaluation results and simulation optimization: The evaluation results are visualized in real time, the simulation process and the simulation state of the entity model are analyzed, the evaluation results are used as feedback information, and the behavior strategies, environmental parameters or inference rules of the simulated entity are dynamically adjusted to achieve closed-loop control of simulation-evaluation-optimization.

7. An online evaluation data processing device based on real-time simulation and deduction, characterized in that, Perform the online evaluation data processing method based on real-time simulation as described in any one of claims 1-6.

8. A computer-readable storage medium, characterized in that, include: Memory and processor; The memory is configured to store executable instructions; The processor is configured to implement the online evaluation data processing method based on real-time simulation as described in any one of claims 1-6 when executing the executable instructions stored in the memory.

9. A computer program product, characterized in that, The computer program product includes instructions that, when executed by a computer, implement the online evaluation data processing method based on real-time simulation as described in any one of claims 1-6.

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