45 results about "SIMPLE algorithm" patented technology

The invention relates to the technical field of particle state detection, in particular to a shield sealed cabin muck state visualization system and method.According to the shield sealed cabin muck state visualization system and method, through stress direction difference matching of an SIMPLE algorithm, inter-particle shear strength distribution is converted into a computable parameter set, quantitative extraction of shear characteristics can be achieved in a complex stress environment, and the detection accuracy is improved. Stable mechanical boundary conditions are provided for flow state calculation, a numerical coupling model of momentum exchange is established, judgment of turbulent fluctuation and slow flow partitions in a flow field does not depend on empirical thresholds any more, characteristic value changes of a mathematical matrix serve as partition bases, the adaptability and accuracy of flow field partition are enhanced, and the flow field partition efficiency is improved. A main load channel in a particle contact network can be automatically identified through combination of an intensity matrix and a centrality algorithm, the connectivity is used as a core calculation index for path sorting, the structural hierarchy of load transmission is clearly presented, and a stable matrix is formed based on weighted superposition of a path shearing and supporting force ratio. Extreme point extraction enables low-stability region identification to have quantification precision.

An object motion pose reproduction method based on a Marker ball comprises the following steps that firstly, size measurement is carried out on a target object, a model file is generated through three-dimensional scanning, and denoising and zooming optimization are carried out; then, a reflective Marker ball is pasted on the surface of an object, and three-dimensional coordinate data of the reflective Marker ball are collected through an optical motion capture system; then, a template group is constructed based on the initial Marker ball position of the object, a target group is constructed in combination with motion capture data, and a rigid body transformation matrix containing a rotation matrix and a displacement vector is solved through least square optimization; and finally, acting the transformation matrix on the model file to reproduce the pose, and reversely optimizing the modeling precision or the Marker point position through error analysis. The object motion pose reproduction method is high in precision, strong in anti-interference capability, simple in algorithm and suitable for the fields of industrial automation, movie and television games and the like.

The invention relates to the technical field of laser measurement, and particularly discloses a paper roll specification measurement device and an installation method, and the measurement system comprises the steps: S1, obtaining the position information of a first range finder and a second range finder; s2, obtaining multiple groups of distance values of the paper roll detected by the first range finders and the second range finders, removing abnormal distance values through an algorithm, and then calculating the residual average value to obtain a value required by the breadth calculation of the paper roll to be detected; s3, according to a breadth measurement mathematical formula, automatically solving a paper roll breadth value W; when the paper roll specification measuring device calculates the specific value, abnormal data are eliminated through an algorithm, and the value is more accurate. And when the angle cosine value is calculated by the measuring device, the method of measuring at a plurality of positions by adopting the actual and accurate breadth value of the same paper roll, eliminating abnormal measurement data through an algorithm and calculating an average value is adopted, and compared with the prior art, the method has the advantages of small data volume, simple algorithm and high precision.

The invention discloses a method for rapidly evaluating an S parameter of a multi-layer PCB port in a multi-stage waveguide structure, and the method comprises the steps: decomposing a system into a plurality of mutually independent subsystems, representing a propagation channel of electromagnetic energy as a signal pipeline, and representing a reflection position of the energy as a reflection node, thereby building a signal energy flow diagram of the system. On the basis, scattering parameters of the subsystems are obtained through a numerical simulation method, and a corrected BLT equation capable of representing the electromagnetic field-circuit bidirectional coupling relation between the subsystems is deduced in combination with propagation equations of all signal pipelines and scattering equations of all reflection nodes of the system; and the S parameter of the multi-layer PCB port in the multi-stage waveguide structure can be obtained by solving the equation. The method has the advantages of being simple in algorithm, accurate in result, high in efficiency and the like, is suitable for a multi-stage waveguide structure of any geometrical shape, and can achieve rapid evaluation and analysis of the electromagnetic coupling effect in electronic equipment with a waveguide-shaped shielding structure in a complex electromagnetic environment.

The invention provides an elevator brake failure early warning device, and relates to the technical field of elevators. According to the failure early warning device for the elevator brake, the temperature sensing assembly, the vibration sensing assembly, the torque sensing assembly, the air gap sensing assembly and the pressure sensing assembly are arranged through the sensor module, so that a plurality of key parameters such as the temperature of a brake shoe, a vibration signal, a brake torque, a brake air gap and hydraulic pressure or spring pressure can be collected in real time; the comprehensive monitoring of the working state of the elevator brake is realized; the data processing and analysis module applies a multi-dimensional data analysis technology, combines various failure judgment algorithms such as a simple algorithm based on threshold judgment, an intelligent algorithm based on pattern recognition and a prediction algorithm based on machine learning, and a data analysis model comprising a feature layer, a prediction layer and a decision layer; and the collected data can be deeply analyzed and processed, whether the brake has a failure risk or not is comprehensively judged, and the accuracy and reliability of early warning are greatly improved.

The invention discloses an optimal arrangement and curve estimation method based on IMU nodes, and belongs to the technical field of three-dimensional curve measurement and restoration. According to the method, initial nodes are generated through uniform sampling on a curve, and the sensitivity value of each node to a curve recovery error is calculated by using local attitude information collected by an IMU sensor, so that a local error distribution function is constructed. And aiming at the error sensitivities of different nodes, a density adaptive sampling strategy is adopted to realize the optimization of the overall node distribution. According to the method, the validity of the optimization point distribution strategy is quantitatively verified by combining an error evaluation index. Through the combination of density adaptive point distribution and spherical interpolation restoration, the method can significantly reduce curve reconstruction errors, improves the space efficiency of IMU arrangement, and is suitable for flexible cables and other three-dimensional curve accurate measurement scenes. The method has the advantages of being simple in algorithm, capable of achieving automatic point distribution, high in error control precision and the like, and an efficient and reliable technical scheme is provided for three-dimensional curve measurement and restoration.

The invention discloses an amplitude detection method for eliminating a multi-beam sounding sonar tunneling effect. The method comprises the following steps: collecting array element data of a receiving array; generating a beam forming amplitude data matrix according to the array element data; calculating a double-domain dynamic gain normalization matrix; calculating a sampling moment index corresponding to the amplitude maximum value of each receiving beam by using the double-domain dynamic gain normalization matrix, and calculating an amplitude detection time gate by using the index; and calculating propagation time: after the amplitude detection time gate is determined, solving the positions of the centroids of the beam forming amplitude data in all the receiving beam time gates by adopting a weighted average time method, and obtaining the propagation time corresponding to all the receiving beams. The improved amplitude detection method based on the double-domain dynamic gain normalization algorithm provided by the invention has the advantages of obvious tunnel effect inhibition, simple algorithm, no need of parameter setting, and convenience for engineering realization and application.

A method and device for integrating measurements in a land vehicle navigation system with an increased frequency of inertial sensor data readings differ from the prior art by virtue of an increase in the frequency of rough accuracy IMU measurements and the subsequent cascade processing thereof. Furthermore, the computational complexity of the algorithms in each cascade increases while the frequency of incoming data to be processed decreases: high-frequency IMU measurements are processed using simple algorithms, the processing results are transmitted to the next cascade with a decrease in data frequency, and in the next cascade, less frequent data are processed using more complex algorithms. As a result of this solution, algorithms for combining navigational measurements can be executed on cheaper and more widely available microprocessors having a lower clock frequency and a lower capacity for representing floating point numbers. By analyzing the mathematical principles of navigation algorithms, the claimed invention makes it possible to achieve a significant increase in the frequency of IMU measurements without impacting the frequency with which a navigation solution is updated and without increasing the required computing power. In addition, the claimed invention makes it possible to reduce the frequency of a navigation solution and the power of the computing device while maintaining the frequency of IMU measurements and a set accuracy of the navigation solution.

The present disclosure relates to the fields of data processing technology, specifically to map navigation, artificial intelligence, and other technical fields, and more particularly to methods, devices, and guide point determination methods for extracting polygon centerlines. A specific implementation involves obtaining a polygon's contour point sequence; inputting this contour point sequence into a centerline extraction model trained using a neural network; the centerline extraction model outputs a polygon's centerline point sequence, and based on this centerline point sequence, the polygon's centerline is obtained. The centerline extraction model, trained through deep learning, can predict the polygon's centerline based on its contour points, resulting in an accurate centerline prediction using a simple algorithm.

The invention discloses a multipoint average phase extraction method and system based on local Hilbert difference, and belongs to the technical field of signal processing. The method comprises the following steps: removing a direct-current component of a beat frequency signal; constructing a complex analysis signal through Hilbert transformation, and carrying out amplitude normalization to obtain a standard cosine signal; suppressing noise by using moving average triangular filtering; and selecting a plurality of fixed points in the middle section of each modulation period, calculating an initial phase through an arc cosine function, extracting and averaging phase variations of the plurality of points in combination with an uphill and downhill region judgment and period expansion mechanism, and outputting high-precision phase data. Amplitude correction and peak detection in a traditional method are avoided, and the method has the advantages of being simple in algorithm, high in real-time performance and high in stability and is particularly suitable for a frequency modulation continuous wave laser interference displacement measurement system.

The present invention provides a method and device for processing credit business data based on artificial intelligence, which relates to the field of intelligent decision-making technology and the financial field. The method includes: extracting risk factors corresponding to the credit business to be approved; determining the risk level corresponding to the credit business to be approved based on the risk factors and a preset risk mapping relationship; and approving the credit business to be approved according to the approval method corresponding to the risk level to obtain an approval processing result. The artificial intelligence-based credit business data processing method and device of the present application improves computing efficiency by distinguishing business risk types, adopting a more accurate calculation method for high-risk businesses, and adopting a computing model with a simple algorithm and small amount of computing for low-risk businesses, thereby reducing the amount of system computing and improving the operating efficiency of the automatic approval system.

The invention discloses a rotational inertia and friction torque identification method and system. The method comprises the following steps: establishing a kinematic model of a controlled object; analyzing the kinematic model of the controlled object to obtain the motion speed and the driving torque of the controlled object; and obtaining the rotational inertia and the friction torque of the controlled object according to the movement speed and the driving torque of the controlled object. The method provided by the invention is simple and easy to implement, the algorithm is simple, the calculated amount is small, the application range is wide, and the adaptive capacity of the control system to the load change is improved.

A broadband space-time anti-jamming method for reconstructing the direction vector, and its implementation steps are as follows: (1) Establish a space-time uniform linear array model; (2) Divide the entire target signal frequency band into I frequency sub-bands, and reconstruct the desired signal direction vector c for each frequency sub-band i ; (3) According to the reconstructed sub-band direction vector c i , further construct the constraint matrix C; (4) Establish the linear constraint minimum variance criterion expression of the broadband signal space-time anti-jamming filtering algorithm; (5) Use the Lagrange multiplier method to solve the optimal weight expression as w opt ; (6) The array beam synthesis outputs the received signal after anti-jamming. The present invention can achieve the suppression of broadband interference signals, maintain the flatness of the in-band array gain of the broadband desired signal, and has the advantages of small degrees of freedom consumption and simple algorithm. The present invention can be applied to fields such as broadband satellite communication

The present invention relates to an on-orbit estimation method for spacecraft mass characteristic parameters based on thrusters, including: spacecraft actuator configuration, establishment of a dynamic model, establishment of a kinematic model, establishment of an attitude measurement component model, on-orbit estimation of the three-axis moment of inertia based on thrusters, on-orbit estimation of the center of mass in the steady state mode and the orbital maneuver mode, and on-orbit estimation of the spacecraft mass. The present invention solves the problems of on-orbit estimation of the spacecraft moment of inertia, center of mass, and mass, and lays a solid technical foundation for the on-orbit redesign or correction of attitude and orbit control algorithms that rely on mass characteristic parameters. Through simulation analysis, this method is reasonable and effective, with a simple algorithm, small computational load, low fuel consumption during implementation, and is easy to implement in engineering. At the same time, a flexible model is added to the simulation of this method, so it is also applicable to flexible spacecraft.

The present application belongs to the field of image processing and computer vision technology, and particularly relates to a sea-sky line real-time detection method and system. The present application divides the sea-sky line detection into two parts of coarse calculation and precise calculation. The first part is coarse calculation, the method of which is to down-sample and calculate a longitudinal gray gradient graph for the collected visible light or infrared image, to carry out threshold segmentation on the longitudinal gray gradient graph to obtain a binary image, to calculate the boundary of the binary image, and to calculate the approximate intercept and slope of the sea-sky line through hough transformation. The second part is precise calculation, the method of which is to search for the maximum value position of the image longitudinal gray gradient graph in the sea-sky line vicinity area of the longitudinal gray gradient graph calculated in the first part according to the sea-sky line intercept and slope calculated in the first part, to carry out hough transformation on the obtained position points, and then to calculate the accurate position and slope of the sea-sky line. The scheme has small calculation amount, small memory occupation, simple algorithm principle and high implementation efficiency.

The invention discloses a ship stack mold resistance CFD calculation method adapting to different grid masses, and relates to the technical field of ship CFD. According to the method, a non-orthogonal correction super-relaxation method is adopted for a diffusion term in a momentum discrete equation, the influence of poor grid orthogonality on a calculation result is considered, a convection term adopts a second-order windward format containing a gradient limiter, and a non-orthogonal correction super-relaxation method is adopted for a non-orthogonal correction super-relaxation method. The problem of extreme value of interface speed reconstruction caused by uneven grid density and large slope rate can be effectively avoided, in addition, during solving based on the SIMPLE algorithm, a dual sub-relaxation method combining global implicit sub-relaxation with local explicit sub-relaxation is adopted, the problem of divergence of an iteration process under the condition of low-quality grids can be effectively avoided, and the method is suitable for solving the interface speed. The method can effectively avoid the influence of low-mass grids such as violent scale change, large slope rate and poor orthogonality, ensures the calculation stability under the condition of the low-mass grids, and is beneficial to improving the stability and calculation precision of ship stack mold resistance CFD calculation.

The application discloses an aircraft wall ablation response data processing method based on an interpolation algorithm and relates to the field of ablation response data processing. The method comprises the following steps: ablation sites are laid out, and initial coordinate information of the ablation sites is output; coordinate information of ablation wall surface grid core points is acquired, and ablation site coordinates after ablation recession are calculated in combination with the initial coordinate information of the ablation sites; ablation information at the ablation sites is acquired, interpolation is performed on the ablation information based on the ablation site coordinates after ablation recession, and ablation information after interpolation is obtained; wall surface mapping is performed on the ablation information after interpolation, and continuous distribution of material ablation response on the entire ablation wall surface is acquired. The method can realize interpolation processing of multiple ablation information in limited scattered ablation sites on a complex ablation surface, and has the advantages of simple algorithm, strong applicability and high calculation efficiency compared with typical two-dimensional or three-dimensional interpolation algorithms.

This invention discloses a high-performance speed control parameter optimization and self-adjustment method for switched reluctance motors under variable speed and load conditions, comprising the following steps: constructing a mathematical model between the optimization object and the optimization target; obtaining n sets of load torque, speed, and acceleration data; using a reinforcement learning algorithm to obtain the corresponding optimal control parameters; using a numerical fitting method to obtain the functional relationships between each optimal control parameter and the load torque, speed, and acceleration; obtaining the optimal control parameters under the current operating condition; and implementing control of the switched reluctance motor based on the obtained optimal control parameters to achieve optimal control of the switched reluctance motor throughout the entire process under variable speed and load conditions. This invention effectively improves the dynamic and steady-state performance of switched reluctance motors under variable speed and load conditions, and has the advantages of simple algorithm and easy implementation.

The invention provides a seismic data denoising method and device based on mathematical morphology. According to the method, mathematical morphology is applied to seismic data processing, the characteristics and advantages of noise can be accurately identified through mathematical morphology operation, and seismic wave field information is detected by using structural elements in a specified shape in combination with the characteristics of seismic data, so that the purpose of high-fidelity denoising of effective wave detail information is kept while interference is removed is achieved. The embodiment of the invention also has the beneficial effects of simple algorithm, strong noise adaptability, high automation degree, convenient design of implementation parameters and the like.

Embodiments of the present disclosure provide a coordinate system alignment method, a device, a storage medium, and a program product. The method comprises: acquiring the current pose of one's own device in a first coordinate system; under the current pose, acquiring image feature data of display content of a target device by means of a camera of one's own device, and on the basis of the image feature data, determining a relative pose of the target device in a camera coordinate system of the camera; and adjusting the origin of the first coordinate system to a target position on the basis of the current pose and the relative pose, achieving alignment with coordinate systems of other head-mounted devices of which the origins of the coordinate systems are adjusted to the target position. The method provided by the embodiments involves a simple algorithm, and a large amount of image or map data does not need to be transmitted between devices in the process, thereby achieving low cost and high efficiency.

The invention discloses a space target initial orbit determination method suitable for space-based ultra-short arc optical observation, and the method comprises the steps: employing short arc optical observation data, based on the assumption that a measurement residual error weighted square sum meets chi-square distribution, combining an L-M nonlinear optimization function and a Lanbert problem, and carrying out the initial orbit determination of a space target. And carrying out adaptive fitting on the distance from the initial epoch observation platform to the target and the corresponding minimum measurement residual weighted sum of squares to realize the initial orbit determination of the target. According to the method, high-precision pointing information of a target is required to be provided, position information of an observation platform is required to be known, initial orbit determination of short-arc optical observation can be completed by utilizing a simple algorithm on the basis, and the method is a simple and efficient short-arc initial orbit determination method.

This invention provides a novel, reversible data transformation method that, while employing a simple algorithm, offers the potential for data scrambling while simultaneously producing output of the same length as the original data. [Solution] The method calculates the Hamming weight of the input symbol sequence and reverses the symbol at the Hamming weight position from the start or end until the symbol sequence reaches a predetermined convergence state (e.g., all zeros). The history information obtained during this reversal process is encoded using delta coding and Huffman transform based on occurrence intervals, etc. Finally, padding is applied to the encoded data based on the original data length, and converted data with the same length as the original input symbol sequence is output. This makes it possible to achieve data transformation that eliminates statistical bias in the data and has both confidentiality and diffusion capabilities, despite being a simple algorithm.

The invention relates to the technical field of concrete 3D printing path optimization, in particular to a concrete 3D printing path optimization method and system based on reinforcement learning, and the method comprises the following steps: collecting structure, equipment and environment parameters through an equipment sensor, and preprocessing the parameters into state information; a digital twinning environment and reinforcement learning model framework is synchronously constructed, a multi-stage training module, a lightweight inference engine and a constraint adaptation module are included, embedded deployment is adapted, and a digital twinning environment generates a path optimization simulation sample; establishing a multi-factor coupled rheological agent model based on the state information, associating an environment with an equipment state, and correcting rheological parameters in real time; and collecting a physical sample. According to the method, the reinforcement learning model framework is combined with the digital twinning environment and the multi-factor rheological agent model, so that the problems that the path optimization precision is insufficient and the printing quality is unstable due to the fact that most of traditional concrete 3D printing path optimization adopts fixed path parameters or simple algorithms are solved.

The invention discloses a coupling characterization method for multi-component variable mass fluid in a shaft. The coupling characterization method comprises the following steps: establishing a gas component-thermophysical property dynamic incidence matrix; through thermodynamic coupling calculation, the influence of the reaction process on the flow in the shaft is dynamically reflected; establishing a three-dimensional shaft control body, and simultaneously establishing a variable mass continuity equation, a momentum conservation equation and an energy conservation equation; boundary conditions are set, meanwhile, distributed heat source items are embedded in catalytic reaction sites, local component mass source items are synchronously updated, and a constraint system conforming to actual working conditions is provided for equation solving; and adopting an SIMPLER algorithm, carrying out iterative calculation through an iterative strategy until the residual error of the energy equation and the component transport equation meets the requirement, outputting the on-way temperature field and pressure field data of the shaft, and generating a dynamic map. According to the method, the complex conditions of variable temperature, variable pressure and variable components in the shaft can be responded in real time, and high-fidelity depiction of the real physical and chemical process can be achieved.

The invention relates to an umbrella skirt surface pressure inflection point-based hard composite insulator heavy pollution area determination method, which comprises the following steps of S1, constructing a flow field equation near an insulator by using an RNG k-epsilon equation model, solving by adopting a Phase Couple SIMPLE algorithm, and analyzing a flow field around the insulator after a steady-state value is reached; s2, performing two-dimensional planarization processing on the surface of the umbrella skirt of the insulator, constructing an x-z coordinate system, drawing a plurality of groups of concentric circle lines, extracting pressure numerical values on the circle lines on the surface of the umbrella skirt, constructing a pressure-coordinate pressure distribution equation, performing derivation on the equation, and recording a coordinate value when the derivative is zero, wherein the coordinate value is a pressure inflection point; s3, forming a fitting curve on the two-dimensional planarized umbrella skirt of the insulator; and S4, constructing a high-voltage transmission line composite insulator heavy pollution area, defining boundary points, determining the shortest distance between two arcs, and then calculating each parameter. The method is low in operation difficulty, wide in application range and high in accuracy.

The present invention provides a high-precision estimation algorithm for the phase difference of a sinusoidal signal with strong robustness to frequency error, and belongs to the field of information technology. The algorithm is mainly aimed at two noisy sinusoidal signals with the same frequency. First, a simple algorithm can be arbitrarily selected to obtain a signal frequency estimate; second, the obtained frequency estimate is used to frequency shift the signal; then, the spectrum value of the DFT transform of the frequency-shifted signal at zero frequency is calculated; finally, the phase difference between the two signals is calculated using the obtained zero spectrum line value. The algorithm can still accurately estimate the signal phase difference even when there is a significant error in the signal frequency estimate, effectively overcoming the transfer of frequency estimation error to phase difference estimation, and has a significant advantage in estimation accuracy, especially under high signal-to-noise ratio conditions, and can improve the accuracy by 1 to 2 orders of magnitude compared to traditional algorithms.

This invention relates to a far-field total magnetic moment measurement method based on the full magnetic gradient tensor, solving the technical problems of existing near-field measurement methods, such as inaccuracy in measuring large and complex magnetic moments, complex calculation methods, and bulky and expensive testing systems. This invention, based on the full magnetic gradient tensor, starts from the theoretical foundation of the far-field dipole equivalent method. In operation, the magnetic gradient tensor is measured instead of the magnetic field strength vector to obtain the measured magnetic moment, and the magnitude of the magnetic gradient tensor, a tensor invariant, is applied in the calculation. This method has advantages such as wide applicability, simple algorithm, ease of implementation, insensitivity to the Earth's magnetic field, and minimal influence from the attitude of the object under test and the testing platform.

The present invention discloses a method and device for exudate segmentation of fundus lesions based on deep learning. The method includes: obtaining a fundus image to be processed; constructing a deep learning network for exudate segmentation of fundus lesions based on the Encoder-Decoder structure; inputting the fundus image to be processed into the deep learning network to obtain an exudate segmentation result; wherein, the encoding end of the deep learning network includes a plurality of downsampling modules, which perform multiple downsamplings on the fundus image to be processed and then output a feature map to the decoding end; correspondingly, the decoding end includes a plurality of upsampling modules, which perform multiple upsamplings on the feature map to finally obtain an exudate segmentation result. The present invention constructs a fully convolutional deep learning network for exudate segmentation of fundus lesions by using the Encoder-Decoder structure. The network model not only has a small number of parameters and a simple algorithm, but also has the ability to quickly extract multi-scale features of images, thereby improving the accuracy of detection results.

The present invention discloses a Josephson junction array driving method and system based on a bidirectional successive approximation algorithm, which relates to the field of metering technology, including: pre-processing data; judging whether frozen flux occurs, and performing graded processing according to the severity of the frozen flux; calculating the junction bias state array B based on the bidirectional successive approximation method according to the graded processing result, and making the generated summary number as close as possible to the target junction number N; outputting the adjusted bias state array and the generated summary number. The present invention reduces the computational complexity, has high computational efficiency, and is suitable for processing large-scale junction array data; has a simple structure, strong versatility, and a simple algorithm structure that is easy to maintain and very convenient to improve, and is suitable for Josephson junctions with arbitrary junction arrangements; when frozen flux occurs, there is no need to switch to other algorithms, and only the input needs to be modified to continue using.

This invention relates to a method for analyzing international hot topics in cyber warfare, belonging to the field of cyber warfare technology. Existing technologies suffer from chaotic analysis of real-time international hot topics, high error rates, and easily tampered logical systems. This invention provides an original analysis method, with core elements including: 1. Defining clear analysis objectives; 2. Emphasizing the analysis of "people" involved in the event; 3. Constructing a rational and reasonable event logic system to ensure rigorous and unbiased logic; 4. Relying on verifiable facts to support analytical conclusions, ensuring credibility; and 5. Building a long-term stable analysis model to achieve continuous and reliable judgment. This invention collects information from multiple sources and extracts core elements of "people" and "events," forming an event logic chain through correlation analysis, creating a tamper-proof logical system, and outputting a credible analysis report after verification. Furthermore, this invention features a simple algorithm, high training accuracy, significantly improved operating efficiency, and low model deployment cost, requiring no complex hardware support. It solves the pain points of existing technologies, provides reliable support for cyber warfare situational assessment, and is applicable to various scenarios involving real-time international hot topics.