78 results about "Information quality" patented technology

The invention relates to the technical field of robot decision making, and provides a robot multi-modal fusion autonomous decision making method and system based on a large language model.The method comprises the steps that a robot obtains multi-modal environment information through a visual sensor, a touch sensor, an auditory sensor and a laser radar which are carried by the robot; performing preliminary filtering and noise reduction processing on the original sensor data, and synchronously recording all the sensor data by timestamps; performing space-time semantic alignment on the preprocessed multi-modal data, mapping pixel coordinates of a target in a visual target coordinate quantization original image to a robot coordinate system, performing uncertainty evaluation on a multi-modal signal through a dynamic Bayesian network, and taking entropy or variance as an uncertainty quantitative evaluation index. According to the method, the information quality is improved from a data fusion source, accurate and reliable basic support is provided for subsequent decision making, and decision making errors caused by data deviation are greatly reduced.

The invention relates to the technical field of food safety intelligent tracing, and discloses a livestock and poultry product epidemic disease and tracing information quality tracing system based on artificial intelligence. The system comprises a raw material file construction module, an abnormal active prediction module, a multi-modal information fusion module, a tracing knowledge graph construction module and an intelligent tracing decision module. The system generates a raw material archive by collecting livestock and poultry raw material information, and analyzes production monitoring data in real time by using a time sequence model to actively predict abnormal nodes of epidemic diseases. After the abnormity is recognized, multi-link heterogeneous traceability information is synchronously called and fused, an abnormal event panorama is generated, and then a traceability knowledge graph is dynamically constructed in combination with an external knowledge base. And finally, automatically generating an optimized traceability query path according to the knowledge graph, and driving a precise traceability process. According to the invention, the conversion from passive recording to active early warning is realized, and the accuracy and efficiency of epidemic disease tracing are improved through deep fusion and intelligent reasoning of multi-source information.

The invention relates to the technical field of data processing, in particular to a laser and binocular camera-based position positioning system, which comprises an acquisition unit, a processing unit, a fusion unit, an abnormality judgment unit, an adjustment unit and a correction unit. According to the method, multi-source information such as a laser point cloud matching result, binocular visual odometer output and the number of feature points is subjected to joint modeling in an extended Kalman filter, so that the AGV obtains stable pose estimation in different environments, and the pose estimation accuracy is improved by analyzing the change trend of pose covariance in an adjusted monitoring window. A density threshold value, an information entropy threshold value and a dynamic proportion threshold value are automatically corrected, so that the threshold values can adapt to real working conditions for a long time, and performance degradation caused by a fixed threshold value is avoided; the problems that due to the fact that sensor information quality fluctuation cannot be recognized and processed, positioning precision is lowered, accumulative errors are increased, and positioning loss is prone to occurring in a complex environment are effectively solved.

The invention relates to the field of data analysis and cleaning, in particular to a method and system for automatically collecting and cleaning public opinion experimental data. The method comprises the following steps of performing periodic data crawling on a public information website, performing public opinion hotspot analysis, and extracting a to-be-processed hotspot event stream; performing keyword detection and global content distribution analysis on the to-be-processed hot event stream to obtain a keyword frequency distribution diagram; performing negative emotion deep recognition according to the to-be-processed hot event stream, and extracting negative emotion public opinion data; performing negative public opinion evolution trend prediction based on the keyword frequency distribution diagram to obtain a negative public opinion propagation situation; and performing IP address tracing on the negative emotion public opinion data to obtain the negative public opinion region sensitivity. According to the method, comprehensive and accurate abnormal public opinion detection and deletion are realized, and the network information quality and the public governance level are improved.

The invention relates to the technical field of computer information processing, and provides an early warning information quality inspection method and device based on an AI large model, and a medium. The method comprises the following steps: inputting an early warning service information text to be subjected to quality inspection, which is screened out according to an early warning trigger source identifier and an early warning level label carried by a front push optimization instruction, into a pre-trained AI large model, and executing semantic analysis mining in combination with a preset early warning field knowledge base, outputting the core semantic elements, the potential association risk features and the logic dependency relationship; generating a dynamic semantic error correction rule base based on semantic association mapping of the core semantic elements and the potential association risk features; using a cross-modal semantic understanding layer of the AI large model to execute semantic deviation recognition and correction guide processing to obtain a semantic problem recognition result; generating early warning correction information for balancing semantic accuracy and risk conductivity through a semantic reconstruction layer; and the push strategy generation network driven by the AI large model is input to generate a differentiated front push priority sequence.

The invention belongs to the technical field of geographic information processing, and discloses a CORS surveying and mapping information quality control method combined with space-time big data analysis. The method comprises the following steps: identifying an ionized layer abnormal disturbance region based on spatio-temporal multi-scale wavelet decomposition, accurately positioning a resolution attenuation boundary through a second derivative mutation feature, constructing a resolution defect compensation weight matrix, and generating an adaptive enhanced high-resolution delay prediction field by using tensor decomposition. Empirical mode decomposition is adopted to recognize a weak fluctuation mode, early capture of precision degradation threatening features is achieved, a time-varying quality threshold curved surface is dynamically constructed based on an evolution trend, and grading quality marking of CORS observation data is achieved. According to the invention, the misjudgment rate of quality evaluation is reduced, and the reliability of surveying and mapping information is improved.

The invention relates to the technical field of insurance business processing, and particularly discloses an automatic car insurance business handling method based on an AI customer service robot. The method comprises the following steps: receiving and standardizing business related information through an information acquisition unit, screening effective information through an information quality evaluation model, extracting key fields by means of OCR text recognition, and generating structured insurance data in combination with multi-modal consistency comparison; a vehicle information system is called to verify data integrity and accuracy in real time and automatically complement and correct errors, and compliance verification is completed through an underwriting rule engine according to a preset rule of an insurance company to generate standardized insurance data; a rate engine is called based on the data to generate a quotation scheme, the quotation scheme is submitted to an underwriting system to generate an underwriting conclusion after being confirmed by the user, a payment two-dimensional code is automatically generated after underwriting is passed, an electronic insurance policy is pushed when the user pays successfully, and meanwhile, whole-process data is stored persistently, and a service ledger is generated.

The invention discloses an unmanned aerial vehicle autonomous strike decision self-adaptive adjustment system based on multi-source information fusion, and particularly relates to the technical field of unmanned aerial vehicle autonomous control and self-adaptive decision, the system comprises an information fusion and decision inner ring and a meta-cognitive self-adaptive adjustment outer ring, the inner ring executes multi-source information fusion and generates a strike decision, and the outer ring executes a meta-cognitive self-adaptive adjustment. And the outer ring evaluates the environment and information quality in real time, drives the adjustment strategy generator based on reinforcement learning by comparing the expected efficiency and the actual efficiency of the decision, and dynamically adjusts the fusion weight and the decision parameter of the inner ring or switches the decision model. The problems that an existing system is poor in environmental adaptability and cannot achieve online self-optimization are solved, autonomous, closed-loop and continuous optimization of decision-making performance in a dynamic battlefield environment is achieved, and the autonomous combat effectiveness, the environmental adaptability and the task robustness of the unmanned aerial vehicle are remarkably improved.

The invention discloses an intelligent mobile terminal tourism information personalized pushing system based on a user portrait, and relates to the technical field of mobile terminal tourism pushing, and the system comprises a user portrait construction module which collects basic information, mines behavior data and generates an interest label; the tourism information processing module is used for collecting multi-source tourism data, carrying out structured processing and evaluating the quality; the personalized push decision module is used for matching user interests and situations and determining a push strategy; the interaction feedback module is used for tracking user operation and optimizing portraits; and the privacy protection module is used for desensitizing the data, managing the authority, encrypting and storing. According to the method, the pushing accuracy and timeliness are improved, the user experience is optimized, the information quality and privacy security are guaranteed, and the method is adaptive to the whole travel process demand.

The invention discloses a multi-modal heterogeneous knowledge base automatic construction and evolution updating method and system, and belongs to the technical field of artificial intelligence and knowledge base data processing, and the method comprises the following steps: S1, multi-modal data collection and cross-modal semantic alignment; s2, human-social multi-source data labeling and information quality screening are carried out; s3, constructing and dynamically updating a multi-modal heterogeneous knowledge base; and S4, system integration and packaging service: packaging the above processes into an integrated multi-mode knowledge base construction and updating system. Unified representation, high-quality knowledge precipitation and dynamic evolution of multi-source heterogeneous data in the human society field can be realized, and a high-quality, reasonable and high-timeliness knowledge infrastructure is provided for human society intelligent service.

A method for compressing Sounding Reference Signal (SRS) channel information in massive MIMO systems is disclosed. When SRS channel estimation is performed in a Radio Unit (RU), the resulting channel estimates create significant fronthaul bandwidth demands. The method transforms SRS channel estimates from antenna space to domains with superior energy compacting properties, enabling transmission of only a subset of channel values while preserving information quality. The method includes beam space compression using mathematical transforms such as DFT, SVD, or EVD to convert channel estimates to beam space, followed by selection of the most significant beams. Alternative embodiments include tap domain compression using DCT or DFT, and delay-Doppler domain compression. The methods support static beam space compression using predefined beam bases and dynamic compression employing adaptive beam bases. O-RAN C-Plane implementations extend Section Type 6 to support the compression methods. The methods significantly reduce fronthaul bandwidth requirements while maintaining channel estimation accuracy, enabling improved system capacity in massive MIMO deployments.

This invention relates to the field of battery parameter identification technology, and particularly to an enhanced battery parameter identification method based on sinusoidal pulse current. The method comprises the following steps: S101. Building a test platform and collecting data; S102. Modeling the battery equivalent circuit; S103. Population initialization; S104. Generating sinusoidal excitation current; S105. Inferring response voltage; S106. Constructing the response voltage envelope; S107. Optimization objective based on the sum of squares error; S108. Constructing auxiliary optimization objective based on sinusoidal features; S109. Genetic evolution; S110. Termination condition judgment and optimal solution output extraction. This method fully and differentially excites the dynamic processes of different time constants within the battery. Without increasing any measurement hardware or testing costs, it improves information quality from the data source, opening a new path for achieving higher accuracy and greater robustness in parameter identification. This significantly improves the convergence efficiency and recognition accuracy of battery parameter identification.

The invention relates to a real-time three-dimensional modeling system fused with unmanned aerial vehicle target recognition, and relates to the technical field of unmanned aerial vehicle application, and the system comprises a data collection module which is used for obtaining multi-source sensor data; the real-time modeling module is used for constructing a real-time three-dimensional model of the environment The target identification module is used for identifying a specific target in the scene and associating the specific target with the three-dimensional model. The information quality evaluation module is used for quantifying the observation information quality of the recognized target in real time according to factors such as the shielding degree, the resolution ratio and the observation angle; and when the information quality evaluation result is lower than a preset threshold value, the flight path planning module is triggered to autonomously plan a dynamic flight path going to the optimal viewpoint, and the flight control module executes the flight path and drives the unmanned aerial vehicle to perform supplementary data acquisition. According to the method, the autonomous closed loop of the perception evaluation decision action is established, so that active and intelligent fine modeling of the key target is realized, and the integrity of model information and the operation efficiency are improved.

The invention relates to the technical field of natural language processing and information retrieval, and discloses a retrieval enhancement generation method and device based on self-feedback driving, and the method comprises the steps: determining a to-be-queried problem through a pre-obtained query request; retrieving in the knowledge base according to the to-be-queried question, and generating an answer of the round of retrieval; calculating an information quality index of the current round of retrieval according to the answer and the to-be-queried question, and if the current round of retrieval is not the first retrieval, calculating an information gain rate of the current round of retrieval according to an information quality index of the previous round of retrieval and the information quality index of the current round of retrieval; and if the information gain ratio does not meet the preset condition, returning to determine the to-be-queried question in combination with the pre-acquired query request to perform the next round of retrieval, and stopping iteration and outputting the final answer until the information gain ratio meets the preset condition. The problems that an existing retrieval enhancement generation method depends on a fixed retrieval threshold value and lacks dynamic judgment capacity are solved, and the information utilization efficiency and the answer accuracy are improved.

The application provides an electric vehicle instrument electronic guide book implementation method and device and electronic equipment, and relates to the field of data processing. The working procedure position and working content of a worker in the production work of an electric vehicle instrument are acquired, and the worker wears AR glasses; electronic guide content is determined from the electronic guide book according to the working procedure position and working content, and a first image is generated; the first image is displayed to the worker through the AR glasses; quality detection information of the electric vehicle instrument sent by a detection device is received, the quality detection information includes operated step information, operated step completion time and defective product conditions, and the quality detection information is used to indicate whether the quality of the electric vehicle instrument is qualified; the quality detection information is marked in the first image to generate a second image; and the second image is displayed to the worker through the AR glasses. Through the reasonable combination of the electronic guide book and product traceability, the beneficial implementation of the electronic guide book is facilitated.

The invention relates to the technical field of industrial operation safety monitoring and hazard source intelligent identification, and discloses an operation site hazard point identification method based on an attention mechanism neural network model. Sensor nodes capable of outputting multi-modal data are arranged along the line, and original data containing spatial positions and multi-dimensional observation values are collected at a plurality of discrete sampling moments; standardizing nodes, time and feature dimensions, and obtaining a unified embedded vector by using linear projection; self-attention is constructed based on node correlation in each mode, and weighted output is generated; the modal information quality is evaluated according to the output distribution dispersion at each moment, fusion factors are obtained and weighted fusion is carried out to form a multi-modal feature matrix; a risk score and a threshold value are obtained according to fusion feature statistical deviation, a modal contribution degree is calculated, and a risk label is generated; and finally, constructing a structured output vector, forming a dangerous point and non-dangerous point set, and realizing coverage enhancement, cross-modal balance, adaptive fusion and explainable output closed loop.

This invention discloses a new source evaluation method for internet technology information, belonging to the field of new source evaluation technology. To address the problems in existing technologies, such as users struggling to quickly find valuable information from a large volume of technology news, significant differences in information quality between different sources, and the lack of an effective source evaluation system, which prevents users from filtering information based on source reputation, this new source evaluation method for internet technology information effectively improves information acquisition and processing efficiency, ensures content quality and credibility, enhances readability and usability through sentiment analysis, topic classification, and relevance calculation, supports users in making informed decisions, promotes a virtuous cycle in the information ecosystem through multi-dimensional considerations in the evaluation system, and dynamically optimizes source evaluation through a user feedback mechanism, enabling personalized content recommendations, meeting user needs, and improving satisfaction.

According to the intelligent model reliability evaluation system based on the improved D-S evidence theory provided by the invention, the Wasserstein distance is introduced as a quantification tool for conflicts among evidences, and the measurement can accurately reflect essential differences among probability distributions of different evidence sources; the problem that the measurement is inaccurate when the distribution pattern difference of the traditional Euclidean distance or Jousseme distance is large is solved; meanwhile, Dane entropy is introduced to evaluate the information quality and uncertainty degree of the evidence, cognitive uncertainty and random uncertainty are effectively distinguished, and an information theory basis is provided for subsequent evidence weighting; namely, the Wasserstein distance and the Dane entropy are fused in order to quantify the distribution difference between the evidences and the uncertainty of the evidences more finely and improve the robustness, the accuracy and the interpretability of a reliability evaluation result, so that reliable evaluation support can be provided for landing application of a high-risk intelligent system, and the reliability evaluation method has the advantages of being high in reliability and high in reliability. The method is especially suitable for reliability capability evaluation of intelligent models in high-risk scenes such as complex systems and industrial control systems.

The invention relates to a method for outputting information in an output device having a display area, in particular of a vehicle, wherein the method comprises: Receiving information and associated metadata that indicate the quality of the respective information, wherein the metadata includes at least one piece of information about the source of the respective information; Determining a quality level for the respective information based on the associated metadata; Selecting or rejecting information based on the quality level; and outputting the selected information in the output device, wherein the output is at least partially adapted to the quality level of the information, characterized in that the method further comprises: Providing a means for a user, particularly via an HMI interface, to influence the evaluation of different information sources.

The invention discloses a scene parallax information generation method and device and electronic equipment, and relates to the field of image analysis, and the method comprises the steps: generating first type parallax information through a laser radar and a binocular camera; generating second-class parallax information through a deep stereo matching large model; third-class parallax information with the density larger than a preset threshold value is generated through the stereo matching system; generating a pseudo depth truth value by adopting a monocular depth estimation algorithm; performing preliminary fusion on the first to third types of parallax information to generate a preliminary fusion parallax; obtaining a scale value and an offset value based on the sparse parallax value and the pseudo depth truth value of the preliminary fusion parallax, and then adjusting the pseudo depth truth value to obtain fourth-class parallax information; and fusing the fourth type of parallax information with the first to third types of parallax information to obtain target parallax information. The problems of insufficient generalization ability, low parallax information quality and insufficient density in a complex real environment due to domain offset and point cloud sparsity of an existing stereo matching method are solved.

The present application relates to remote sensing geological information processing technical field, disclose a kind of mineral geological exploration system based on remote sensing image texture analysis, comprising: time series baseline library construction unit, for generating the time series statistical baseline of normal fluctuation range definition, ecological proxy texture channel processing module, it is purified according to time series statistical baseline to the normalized vegetation index texture of current image, to generate ecological proxy texture anomaly map, construct texture channel processing module, for generating construction texture anomaly map, and collaborative verification engine module, before executing spatial coupling determination, first according to image information entropy evaluation two channel information quality and dynamically select verification logic, the information of surface covering in traditional exploration, which is regarded as interference, is converted into an independent verification dimension, and through the double constraints of space and time and the adaptive evaluation of information quality, an internal cross-validation evidence chain is constructed.

The invention discloses a coal transaction data quality control method and system, relates to the technical field of data quality control, adopts a layered architecture design, and comprises a data source layer, a data acquisition layer, a data cleaning layer, a data storage layer, a data quality monitoring layer, a data application layer and a user interaction layer. The data source layer is used for gathering multi-channel coal transaction related data of an enterprise direct reporting system, a market acquisition interface and a sensor network, and covering transaction core data, logistics information, quality detection data and market quotation data; according to the coal transaction data quality management and control method and system, through the multi-source adaptive acquisition module and the unified data format, in combination with the timestamp and the data source identifier, the problems of manual filling errors and difficult multi-source data adaptation are solved, and the data acquisition accuracy is improved.

The invention provides an ultrasonic video quality detection method and device, electronic equipment and a storage medium. The method comprises the steps that an ultrasonic video is acquired, the ultrasonic video comprises multiple frames of ultrasonic images, and the ultrasonic images are section images of a target part; for each frame of ultrasonic image in the ultrasonic video, identifying a section category corresponding to the ultrasonic image; image information of ultrasonic images belonging to a target category in the ultrasonic video is determined, and the target category is a section category meeting a preset requirement in section categories corresponding to the ultrasonic images of the ultrasonic video; the image information comprises the number of the ultrasonic images belonging to the target category and / or quality evaluation information of the ultrasonic images belonging to the target category, and the quality evaluation information is used for indicating the quality of the corresponding ultrasonic images; and determining the quality of the ultrasonic video at least based on the image information of the ultrasonic image belonging to the target category in the ultrasonic video. According to the method, the quality of the ultrasonic video can be accurately determined.

The invention provides a large model interaction system based on a cognitive behavior therapy, relates to the technical field of large model interaction, and realizes specialized intelligent intervention based on the cognitive behavior therapy by integrating a cognitive challenge technology library, a process modeling module, a double-track agent collaboration module and a quantitative evaluation module. Wherein the process modeling module is used for calling a structured cognitive reconstruction technology, dividing the whole process of the cognitive behavior therapy into stages with definite quantitative switching standards, and ensuring the continuity and target orientation of the therapy; the double-track intelligent agent works cooperatively, the dialogue interaction intelligent agent guides a user to complete a task in a natural language, and meanwhile, the process evaluation intelligent agent evaluates information quality and a target achievement condition in real time to realize dynamic process regulation and control; the quantitative evaluation module generates a quantifiable improvement signal through multi-dimensional scoring, and provides an objective basis for completion degree judgment and process promotion of each stage of the whole process of the cognitive behavior therapy, so that the normalization and effectiveness of psychological intervention are improved.

The present application relates to the technical field of food safety intelligent tracing, and discloses a livestock product epidemic disease and traceability information quality tracing system based on artificial intelligence. The system comprises a raw material archive construction module, an abnormal active prediction module, a multi-modal information fusion module, a traceability knowledge graph construction module and an intelligent tracing decision module. The system generates a raw material archive library by collecting livestock raw material information, uses a time series model to analyze production monitoring data in real time to actively predict abnormal nodes of epidemics. After identifying the abnormality, multi-link heterogeneous traceability information is synchronously called and fused to generate an abnormal event panoramic view, and then a traceability knowledge graph is dynamically constructed in combination with an external knowledge base. Finally, an optimized tracing query path is automatically generated according to the knowledge graph to drive a precise tracing process. The present application realizes the change from passive recording to active early warning, and improves the accuracy and efficiency of epidemic tracing through deep fusion of multi-source information and intelligent reasoning.

This invention relates to a method for efficient cutting of continuously cast irregular-shaped billets, belonging to the technical field of continuously cast irregular-shaped billet production methods. The technical solution of this invention is as follows: Real-time data during continuous casting production is collected; the casting speed is accumulated over time to calculate the cumulative length of the billet in real time, and the corresponding time when the billet is in the liquid state is calculated; based on the corresponding time when the billet is in the liquid state and the process parameters, the heat flux density of each billet is determined; the correspondence between the time of changing the tundish / intermediate ladle and the cutting time of the affected billet is found to identify the affected billet; the state of the molten steel and the distribution of defects are monitored in real time, and the cutting scheme is dynamically calculated in conjunction with process constraints. The beneficial effects of this invention are: it can simulate data for all billets in continuous casting, optimize the cutting of areas with dense defects, record all key time nodes, generate billet information quality reports, and perform detailed quality control of the billets.

The invention discloses a multi-feature power grid data fusion method based on dynamic quality estimation, and the method comprises the following steps: S1, processing various input power data, and calculating the view-level classification probability output; s2, performing sample-level three-dimensional dynamic quality evaluation according to the obtained probability output; s3, implementing residual gating of consensus perception, and obtaining a sample weight through multiplicative gating and normalization; and S4, according to the calculated sample weight, carrying out dynamic fusion on various kinds of power data. According to the method, the problem that the existing method cannot maintain the robustness of low-quality information and conflict data on the premise of ensuring interpretability of the decision process is solved, and the robustness of the method in complex scenes such as information quality change and conflict is effectively improved.

The ground target indication radar is an air defense information radar, usually uses a medium-range or short-range two-coordinate radar or three-coordinate radar with strong maneuverability and high data rate, and timely and continuously provides information such as position, speed and nature of the target. The interaction with the radar is generally realized through a radar situation display and control software, and mainly completes functions such as system parameter control, target monitoring, discrimination, intervention and the like. When a target indication radar personnel monitors a radar target, full graphical information is presented, and no numbers, words or tables are needed. Traditional graphical display forms include P display, H display, B display and E display and the like. The traditional graphical display method can display the target detection situation on different sides, but cannot give sufficient information support for the attributes such as authenticity of the target. Especially for low-altitude targets, it is necessary to complete the preparation discrimination of the information quality of the detected target as soon as possible in a very short time. The present application proposes a radar combined situation analysis method, which is more suitable for the research and judgment of the authenticity and quantity of the target by combining the echo D-V data with the traditional situation combined display, and provides strong support for the rapid acquisition of information by the target indication radar.

The invention relates to the technical field of battery parameter identification, in particular to an enhanced battery parameter identification method based on sinusoidal pulse current, and the method comprises the steps: S101, building a test platform, and collecting data; s102, modeling a battery equivalent circuit; s103, performing population initialization; s104, generating a sinusoidal excitation current; s105, reasoning the response voltage; s106, constructing a response voltage envelope line; s107, optimizing a main target based on a quadratic sum error; s108, constructing an auxiliary optimization target based on sinusoidal features; s109, carrying out genetic evolution; and S110, judging a termination condition and outputting and extracting an optimal solution. According to the method, the dynamic process of different time constants in the battery is fully and differentially excited, on the premise of not increasing any measurement hardware or test cost, the information quality is improved from a data source, a brand new path is opened up for realizing parameter identification with higher precision and higher robustness, and the method has a wide application prospect. Convergence efficiency and identification precision of battery parameter identification can be significantly improved.

The application discloses a relay type unmanned ship air-sea integrated monitoring method, system, equipment and storage medium, relates to the technical field of unmanned ship cooperative communication and monitoring, and comprises the following steps: constructing a task priority calculation model, and generating grid data priority of each grid; based on the grid data priority, a dynamic buffer and transmission sequence generation mechanism is generated in combination with a dual-machine communication link state to output dual-machine state parameters; the dual-machine communication link state is combined, the relay path and bandwidth allocation are scheduled through link state sensing and spatial constraint, and when the mother ship receives each grid data, based on the priority and the dual-machine state parameters, a link quality weighted fusion and time synchronization correction mechanism is applied to dynamically adjust the dual-machine transmission parameters in combination with a micro-vibration and environmental disturbance compensation algorithm; the method disclosed by the application improves the cooperative efficiency, transmission reliability and information quality through dynamic scheduling, adaptive buffering and anti-disturbance fusion.