48results about How to "Reduce data redundancy" patented technology

The invention relates to the technical field of side slope monitoring and early warning, in particular to a mine site side slope remote online real-time monitoring and early warning system which comprises a multi-source data monitoring unit, a data processing and analyzing unit, a side slope instability judging unit, an instability grading early warning unit and an early warning verification pushing unit. The method comprises the following steps: collecting monitoring data of a plurality of data sources to obtain time sequence monitoring data of each data source, carrying out noise reduction on the time sequence monitoring data, then decomposing the time sequence monitoring data, calculating a time-frequency feature vector through an energy density function, and optimizing the time-frequency feature vector through feature screening; calculating a slope stability evaluation index by optimizing the time-frequency feature vector, constructing an instability risk index to judge a slope instability risk level, constructing an early warning index, and combining the early warning index with the slope instability risk level to establish a graded early warning mechanism to obtain a slope instability early warning level; and verifying the slope instability early warning grade, and performing early warning according to the slope instability early warning grade passing the verification. According to the invention, the false alarm rate of slope monitoring and early warning can be reduced.

The invention discloses a fault analysis method and system applied to a 5G base station transmission link, and the method comprises the following steps: obtaining alarm information of the 5G base station transmission link through integrating a real-time data stream processing mechanism and an incremental learning model; the alarm information is preprocessed; based on a time dimension, a topology dimension and a text dimension, converting the pre-processed alarm information into multi-dimensional vector representation; grouping aggregation is carried out by combining a DBSCAN algorithm; through an Incident root cause analysis algorithm, performing deep suspected root cause analysis on the grouped and aggregated alarm information, and determining suspected root cause alarms; and performing fault diagnosis through the knowledge graph and the diagnosis rule, generating a repair process and recording the whole process. According to the method, the accuracy and speed of fault positioning can be remarkably improved, the intelligence and automation level of fault analysis is enhanced, and meanwhile, the real-time performance and flexibility of fault processing are ensured, so that the operation and maintenance management of a 5G network is optimized, and a solid guarantee is provided for the stability and reliability of communication service.

The invention relates to the technical field of wireless communication, and discloses a low-power-consumption communication method and device for wireless audio equipment, an SoC chip and a storage medium. The method comprises the following steps: sampling acoustic characteristics of heterogeneous audio data of a plurality of target audio devices, calculating a voice spectrum corresponding to device characteristics, and extracting multi-device acoustic characteristics, performing multi-frequency sub-band speech enhancement, heterogeneous segmentation and grouping of multi-target audio equipment, verification value calculation and differential coding on each extracted acoustic feature sequence to obtain a multi-source coding speech segment; performing transmission unit division and cooperative signal modulation, cooperative resource allocation and data stream transmission of each transmission unit on the multi-source coding voice segment to obtain a transmission voice data stream; and obtaining a transmission voice data stream transmitted with low power consumption and performing audio recovery on the obtained data to obtain a target audio data stream transmitted by the multi-target audio equipment. The communication power consumption of the multiple target audio devices is reduced, and the audio transmission quality is ensured.

The invention discloses a method, a device and equipment for testing the uniformity of a light guide film, and the method comprises the steps: carrying out the dynamic temperature adjustment of the light guide film, and obtaining the multi-wavelength dynamic spectrum data of an edge region; nonlinear optical response characteristics are extracted; generating a dynamic optical characteristic diagram and performing three-dimensional structure analysis; calculating a thermo-optical coupling complexity index; generating dynamic change data of the optical performance of the edge region; and executing multi-dimensional evaluation index processing and time sequence analysis to obtain a dynamic accurate evaluation result. According to the technical scheme, the optical performance of the edge area of the light guide film can be accurately evaluated under the dynamic temperature condition, the influence of temperature change on the uniformity of the light guide film is effectively captured, the accuracy and practicability of a test result are improved, and a more reliable basis is provided for design optimization and quality control of the light guide film.

The invention discloses a pavement disease inspection method based on a vehicle-mounted edge device, and relates to the technical field of pavement disease inspection, and the method comprises the steps: 1, obtaining image data, thermal imaging data and road geometric data of a pavement through an information obtaining module; 2, the information processing module processes the image data to obtain a disease area I; matching the image data with the thermal imaging data to obtain a disease area II; performing height change analysis on the geometric data of the road to obtain a disease area III; 3, the information processing module matches the disease area I, the disease area II and the disease area III with the position of the road surface, and when any position of the road surface is successfully matched with more than two disease areas I, disease areas II or disease areas III, the position of the road is marked as a disease part. According to the method, the multi-modal road surface data are adopted, and various light-weight means are adopted, so that the remarkable optimization effect is achieved in the aspects of performance, efficiency, resource utilization and the like.

The invention discloses an efficient intelligent data compression and feature extraction method and system. The method comprises the following steps: S1, data preprocessing: performing data cleaning, denoising and standardization processing on to-be-processed data; s2, data compression and storage: determining a compression algorithm according to the type of the data, and uploading a compressed data file to a database; s3, feature extraction: deploying a machine learning model, and extracting representative features from the compressed data; and S4, data post-processing: further processing and optimizing the extracted features. According to the method, the data compression technology and the feature extraction technology are combined, the most representative information is extracted from the original data, meanwhile, the data storage and transmission cost is reduced, key features in the data are automatically recognized and reserved through an intelligent algorithm, and therefore efficient data compression and feature extraction are achieved.

The invention discloses a method and a system for rapidly extracting morphological indexes of an erosion gully, and belongs to the technical field of water and soil conservation. The method comprises the following steps: S1, watershed segmentation; s2, identifying an erosion gully object; comprising the following steps: performing spectral feature analysis based on an orthoimage to obtain a first principal component; selecting a texture feature variable and a topographic feature variable; performing multi-scale image segmentation on the first principal component based on the texture feature variable; identifying whether each object is an erosion gully according to the topographic feature variables; and correcting the identification result to obtain a final erosion gully object identification result. S3, channel line extraction is carried out on the erosion gully; extracting a river network water system through hydrological analysis, correcting the river network water system, and taking the corrected river network water system as a channel line of the erosion gully; and S4, extracting the morphological index of the erosion gully according to the erosion gully object identification result and the gully line. The method can effectively improve the extraction precision of the morphological characteristics of the erosion gully, and breaks through the problem of poor extraction precision of the erosion gully.

The invention provides a lithology identification method and system for a shale oil reservoir, and relates to the technical field of geological exploration. According to the method, the logging data from multiple sources, the X-ray diffraction (XRD) data and the microscopic image analysis data are fused, so that the influence of complex and changeable mineral components and other physical parameters on lithology identification is effectively overcome, and the accuracy and reliability of an identification result are remarkably improved. Furthermore, dimension reduction is carried out on the fused features by adopting a principal component analysis (PCA), data redundancy is reduced, the most representative features are extracted, and the efficiency of the model is improved. An attention mechanism is introduced into the lithology identification model, the weight of each logging data feature is adaptively adjusted, the influence of key features on the lithology identification result is enhanced, and the interference of useless features is reduced, so that the accuracy and reliability of lithology identification are further improved, and a more accurate basis is provided for distribution prediction of shale oil.

The invention relates to the technical field of picture rendering, in particular to a media picture rendering optimization method and system based on artificial intelligence. The method comprises the following steps: acquiring a terminal video stream; performing RGB format conversion on the terminal video stream to generate an RGB type frame image set; pixel partitioning is carried out on the RGB type frame image set, and RGB pixel matrix blocks are generated; performing color space acceleration conversion on the RGB pixel matrix block to generate a YUV cache data matrix; the YUV storage data matrix is sent to a DSP internal processing unit for key frame selection, and YUV key video frame data and YUV non-key video frame data are obtained; and performing intra-frame coding on the YUV key video frame data so as to generate YUV key frame coded data. According to the method, the media picture rendering efficiency is improved by optimizing data processing, transmission and rendering and combining user visual focus analysis.

The invention discloses a dynamic sliding window optimization method for a 3D laser radar inertial SLAM system, relates to the technical field of SLAM, and aims to improve the precision of pose estimation of an existing laser inertial SLAM system in a complex motion state of a robot. According to the method, the key frame is selected according to the displacement difference and the rotation difference, the key frame is further divided into the strong key frame and the weak key frame, when the window slides, a multi-slide-in and multi-slide-out dynamic optimization strategy of the strong and weak key frames is designed, and the dynamic optimization of the strong and weak key frames is realized in combination with double standards of whether the window meets optimization conditions or not. And the SLAM system is endowed with the capability of dynamically adjusting the window size according to different motion states of the robot. Besides, a two-time optimization scheme of key frame optimization in the sliding window and local common frame optimization in the sliding window is designed, a relatively accurate optimization reference can be provided for common frame optimization after key frame optimization, and more reliable marginalized prior information can be provided for next key frame optimization after common frame optimization. Therefore, the pose estimation precision of the SLAM system in the complex motion state of the robot is improved.

The invention discloses a point cloud intelligent cutting and dynamic optimization method based on edge computing, and belongs to the technical field of intelligent traffic systems and edge computing, and the method comprises the steps: collecting three-dimensional point cloud data through a multi-line laser radar disposed on an RSU; generating a three-dimensional bounding box through a three-dimensional target detection network in an RSU edge calculation unit, generating an ROI mask, expanding a buffer region, and performing adaptive region cutting on the point cloud to form an ROI point set and a background point set; a perception-driven cutting decision is realized, and ROI extraction is converted into a self-learning process based on semantic features from fixed threshold judgment; voxelizing the non-uniform resolution point cloud, generating a unique hash index for each voxel unit, comparing a hash set of a current frame with a hash set of a previous frame, extracting newly added and disappeared point sets, and constructing a differential data packet according to a change ratio; while high timeliness is kept, data redundancy is reduced, and the point cloud updating rate and the incremental transmission efficiency are improved; and dynamic optimization of communication-calculation cooperation is realized.

The invention discloses a path planning method, system and device for a complex terrain and a storage medium. The method comprises the following steps: acquiring topographic data of a complex terrain through a laser radar, and constructing a map model based on an irregular triangular network; calculating the topographic cost of each triangle according to the topographic features of the map model, and converting the topographic cost of each triangle into the total topographic cost; and inputting the total terrain cost of each triangle into a Double DQN algorithm, and planning an optimal path. By combining the three-dimensional terrain modeling technology and the reinforcement learning algorithm, efficient, accurate and real-time path planning can be realized in a complex three-dimensional environment, the limitation of the prior art is overcome, and the development of the autonomous navigation technology of the robot is promoted.

The invention discloses a quantitative laser speckle blood flow imaging method based on a neuromorphic visual sensor, and relates to the technical field of biomedical engineering. The method solves the problem that static scattered light caused by physiological behaviors and electronic noise of imaging equipment have adverse effects on blood flow imaging quality in a traditional laser speckle contrast imaging method, and comprises the following steps: step 1, using a helium-neon laser as a light source, and irradiating a scattering medium with an expanded laser beam to form a speckle pattern; 2, a microfluidic injector is adopted, two parameters of the inner diameter and the flow of the injector are set, and the flow speed range is controlled; 3, asynchronously sensing the change of the light intensity of the speckle pattern by using an event camera, and shooting the speckle pattern by using a frame camera; and 4, acquiring event stream data by the event camera, and processing the data by using an algorithm. Real-time and high-resolution blood flow imaging and flow velocity calculation are achieved, and the inherent limitation of a traditional method is overcome.

The invention discloses an embedded firmware camera data modification method and device, a medium and equipment, and relates to the technical field of computer vision, and the method comprises the steps: collecting image data in real time, and carrying out the primary processing; a frame difference method and a background modeling algorithm are adopted to carry out region division and priority distribution on the image data after primary processing, and a region priority mapping table is generated; extracting feature points of a high-priority motion area in the optimized image data through an optical flow method, and calculating a motion vector between continuous frames; according to the calculated motion vector between the continuous frames, an event-driven frame processing mechanism is triggered, and the frame rate and the processing precision are automatically adjusted; through the motion vector extracted through the optical flow method, the motion speed of the object can be calculated in real time, the frame rate and the processing precision are dynamically adjusted according to the motion speed, it is ensured that enough details are captured in the rapid motion process, and processing resources are saved in the static process.

The embodiment of the invention provides a multimedia editing method and device and electronic equipment, and the method comprises the steps: generating initial data layer data according to the editing operation of a multimedia material, and the initial data layer data comprises multimedia material track fragment data obtained through the editing operation; determining an editing effect attribute indicated by the editing operation, associating the editing effect attribute with the initial data layer data, and taking the initial data layer data associated with the editing effect attribute as target data layer data; and according to a received display instruction, acquiring multimedia material track fragment data and the editing effect attribute from the target data layer data by utilizing a consumption view layer, and generating multimedia fragment content after editing operation based on the multimedia material track fragment data and the editing effect attribute. And data redundancy occurring in the multimedia editing process is reduced.

The invention discloses an intelligent grouting progress monitoring management and control method and system, and relates to the technical field of intelligent grouting, and the method comprises the steps: obtaining a preset video monitoring frequency range and a preset video monitoring duration range, and obtaining a plurality of random video monitoring vectors based on a random number generation method; analyzing monitoring redundant data and monitoring load data of grouting progress monitoring under different video monitoring vectors; constructing a progress monitoring effect evaluation model based on machine learning according to the monitoring redundant data and the monitoring load data; constructing a video monitoring vector effect display model based on the three-dimensional model according to the output of the progress monitoring effect evaluation model and the corresponding video monitoring vector, and performing data analysis on the video monitoring vector effect display model to obtain an optimal video monitoring vector which is used for managing and controlling the monitoring process of the grouting progress; the method is used for solving the problem of poor monitoring caused by shooting disorder during grouting progress monitoring in the prior art.

The invention relates to the field of three-dimensional Gaussian scene color rendering, in particular to a three-dimensional Gaussian scene color rendering method and a computer device. The method comprises the following steps: converting Gaussian ellipsoids of an RGB color space into an HSL color space, and extracting a basic hue of each Gaussian ellipsoid; solving the color when the Gaussian ellipsoid is observed from different angles, and representing the color by using the basic hue and the saturation and the brightness at the observed part through the combination fitting of the spherical radial basis functions; a user activity space is segmented according to fixed length, width and height, and for segmented space blocks, indexes of Gaussian ellipsoids seen from different positions and different angles in the space blocks and indexes of SRBF seen in the space blocks are obtained through calculation preprocessing; and when a user accesses the 3D Gaussian ellipsoid resource online, real-time calculation, transmission and loading are carried out, and the 3D Gaussian ellipsoid resource is finally rendered to the user. The method is suitable for three-dimensional Gaussian scene color rendering.

The invention belongs to the technical field of intelligent prediction, and relates to a key gene identification method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining original sample data; preprocessing the original sample data to obtain preprocessed sample data; performing word segmentation operation on the preprocessed sample data according to the HFkme r to obtain word segmentation data; performing vector conversion operation on the word segmentation data to obtain word segmentation vector data; constructing an initial BGAC model, and performing model training operation on the initial BGAC model according to the word segmentation vector data to obtain a target BGAC model; obtaining a to-be-recognized genome protein sequence; and inputting the genome protein sequence into the target BGAC model for key gene recognition operation to obtain a key gene recognition result. The method not only solves the problems of high time and high cost in key gene identification in traditional molecular biology, but also provides a precious microscopic view angle for deeply exploring the origin and evolution of insect wings, and the complex biological macro-evolution process is better understood.

This invention discloses a broadband oscillation disturbance source localization method based on compressed sensing and graph convolutional neural networks (GCNs), comprising two stages: offline training and online localization. In the offline training stage, electrical quantities under subsynchronous / supersynchronous broadband oscillation modes are obtained using measurement data from actual systems or simulation examples, constructing a broadband oscillation offline sample library. Compressed sensing is used to encode and compress the electrical quantities in the offline sample library, obtaining a training set and a test set. The constructed GCN localization model is trained using the training set until the test set reaches the target localization accuracy, resulting in a broadband oscillation localization model. In the online localization stage, a substation collects electrical quantity data and compresses and encodes it using compressed sensing technology; the substation data is uploaded to the master station; at the master station, the feature matrix and system adjacency matrix are input into the trained GCN localization model, and the oscillation source location is output. This invention's method is applicable to broadband oscillation disturbance source localization under various operating conditions.

This invention relates to the field of cable inspection and maintenance technology, and discloses a robot for the operation and maintenance of power transmission lines in mountainous areas. The robot includes a main body, a sliding buffer assembly, a camera inspection assembly, a positioning assembly, and a drive assembly. The sliding buffer assembly decouples the camera mechanism from the robot body through a sliding groove and a slider, allowing the robot to move forward continuously at a constant speed while the camera mechanism remains stationary, eliminating motion blur and channel misalignment. Driven by the drive assembly, the positioning assembly first stretches the cable section to be tested axially and then pushes it axially, forcibly opening circumferential and axial micro-cracks to facilitate the visualization of early damage. Four sets of multispectral high-definition cameras in a ring array employ an intermittent static shooting strategy, requiring only one key image to be acquired for each detection section during the stretching and pushing states. This invention achieves high-precision, low-miss-rate detection of micro-cracks in cables in mountainous areas, simplifies the system structure, and improves the robot's portability and operational stability.

The invention relates to the technical field of wireless communication IC (integrated circuit) chips, and discloses a chip data acquisition method, which comprises the following steps of: acquiring physical layer acquisition data of different nodes in a physical layer and preprocessing the physical layer acquisition data; wherein the physical layer acquisition data comprises physical layer data and physical layer maintenance and measurement signals; sOC working information is recorded while physical layer collection data is collected, so that a current SOC maintenance and measurement signal is collected through a data bus; combining the SOC maintenance and measurement signal and the physical layer acquisition data into an acquisition signal, and performing data processing on the acquisition signal; wherein the data processing comprises data selection processing, extraction, trigger control and trigger length control; and the acquisition signal after data processing is written into the Memory unit through the data bus to be recorded or is output from the direct peripheral interface. According to the chip data acquisition method provided by the invention, the physical layer data and the maintenance signal of the chip are acquired, and the technical problem of how to acquire the chip data more efficiently, accurately and comprehensively is solved.

The invention discloses a medical multi-modal large model intelligent system and method based on federated learning, relates to the technical field of medical information, and solves the technical problem that existing federated learning still has defects in the aspects of processing heterogeneous data quality, ensuring model interpretability and promoting multi-party effective cooperation. The system comprises a federated architecture module, a federated reasoning module and a model collaboration module, the federal architecture module is used for adjusting modal weight in real time according to data quality; the federated reasoning module is used for constructing a knowledge graph; introducing the knowledge graph into a medical multi-modal large model; setting an atlas constraint loss function; the model collaboration module is used for optimizing the medical multi-modal large model through distributed training and localized deployment; according to the method, multi-modal data can be effectively integrated, and the model training and reasoning process is optimized by utilizing medical knowledge, so that the accuracy and reliability of medical diagnosis are improved.

This invention provides an artificial intelligence-based internet property rights transaction risk assessment and decision-making system, relating to the field of data processing technology. The system includes: a data acquisition and preprocessing module for real-time acquisition of raw transaction data, followed by cleaning and standardization; a multi-dimensional feature construction module for modeling by time windows and constructing a multi-level interaction relationship graph to obtain time-series feature data and graph-related feature data; and for normalizing and weighting the features; a risk identification module for extracting suspicious transfer behavior chains and tracing the flow of benefits, performing composite risk discrimination; and an intelligent decision-making module for performing hierarchical adaptive discrimination and case migration comparison, summarizing and generating risk assessment results and pushing early warnings; and receiving feedback from the management terminal, which is then used to optimize identification and decision-making parameters. This invention improves the autonomy and accuracy of property rights transaction risk assessment and decision-making.

The present disclosure relates to a method, device, electronic device and storage medium for matching patent applicants. The matching method includes: based on the feature information corresponding to the applicant to be stored in the patent document to be stored, retrieving the candidate applicant corresponding to the applicant to be stored in a preset database; determining the similarity between the candidate applicant and the applicant to be stored; based on the similarity, determining whether the applicant to be stored successfully matches the candidate applicant. The matching method, device, electronic device and storage medium for patent applicants provided by the present disclosure have a higher correlation between the selected candidate applicants and the applicant to be stored, thereby effectively improving the matching accuracy between the applicant to be stored and the candidate applicant, and reducing the probability of data redundancy or matching errors in related technologies.

The invention relates to the technical field of unmanned driving, and particularly discloses an obstacle detection system for unmanned driving, which is characterized in that a multi-modal acquisition module acquires vehicle surrounding environment data according to near, middle and far layers, a data preprocessing and synchronizing module performs standardization processing on the acquired data and then outputs a standardized heterogeneous data set with a detection interval identifier; two types of feature libraries are arranged in the dynamic weighted fusion judgment module, after obstacle features are extracted from a data set, an obstacle judgment result is output through hierarchical weight distribution, dynamic correction, feature fusion and two-dimensional judgment, and the master control terminal receives the judgment result and outputs normal driving, constant speed deceleration, steering avoidance or emergency braking instructions. The obstacle detection accuracy, the response timeliness and the environmental adaptability of the unmanned vehicle under the complex road condition are improved, and reliable guarantee is provided for safe driving of the unmanned vehicle.

The application discloses a heterogeneous parallel material removal calculation method and system. The method comprises the following steps: constructing a heterogeneous parallel calculation environment comprising at least a first processing unit and a second processing unit, wherein at least one processing unit supports data parallel execution for a large number of discrete elements; constructing a discrete representation of a workpiece, and generating state data for representing a material state based on the discrete representation of the workpiece; generating space constraint information based on tool geometric parameters, relative motion information of the tool and the workpiece, and the state data; decomposing material removal simulation calculation into a preprocessing task and a relationship evaluation task; mapping at least two calculation tasks to the first processing unit and the second processing unit for execution, so that the first processing unit and the second processing unit concurrently or flow water overlap execute in at least part of a time period; updating the material state based on the space relationship quantity and calculating the material removal quantity, and iterating until the trajectory is completed. Therefore, the calculation efficiency is significantly improved, and the real-time simulation requirement is met.

The application discloses a kind of based on acoustic feature converter interturn short circuit detection method and system, method includes the following steps: constructing converter three-dimensional simulation model, setting electromagnetic-thermal-force-acoustic multi-physical field coupling, extracting temperature, equivalent stress and sound pressure level and normalizing processing, determine peak region and divide peak connected region;The spatial consistency factor between peak connected region is calculated, and acoustic sensitive area is identified;The acoustic thermal force joint sensitivity in acoustic sensitive area is calculated, to maximize total acoustic thermal force joint sensitivity as target, solve optimal monitoring point arrangement scheme;With optimal monitoring point arrangement scheme, monitoring point arrangement is carried out, the acoustic characteristic vector under different working conditions and actual working condition is calculated, and the actual state of converter under actual working condition is determined.The present application realizes the high-precision detection, accurate positioning of converter interturn short circuit fault by multi-physical field information, combined with acoustic sensitive area identification, monitoring point optimization arrangement and working condition matching analysis.

This invention discloses a chip tray optical feature acquisition and processing device and method, including an acquisition device and a processing device connected thereto. The acquisition device is used to position and illuminate the chip tray, and acquire a first image and a second image of the chip tray respectively. There is an overlapping area between the first image and the second image. The processing device is used to receive and process the image data acquired by the acquisition device, including: a distortion correction module, used to perform radial distortion correction and tangential distortion correction on the first image and the second image respectively, to obtain distortion-corrected image data; an image deduplication module, used to extract computer vision algorithm feature points from the distortion-corrected image data, match the overlapping area, and remove redundant data to obtain deduplicated image data; and a stitching and fusion module, used to register and fuse the deduplicated image data to generate a complete chip tray image.

The invention relates to the technical field of data integration, in particular to a multi-source heterogeneous data integration method, electronic equipment, a medium and a product, and the method comprises the following steps: screening multi-source heterogeneous data based on a target index condition to obtain at least one piece of effective multi-source heterogeneous data; performing data preprocessing on the effective multi-source heterogeneous data to obtain effective processed multi-source heterogeneous data; determining at least one target to-be-filled directory from a preset initial data topic domain based on the target index condition; identifying data features contained in each piece of effectively processed multi-source heterogeneous data, determining a target to-be-filled catalogue corresponding to each piece of effectively processed multi-source heterogeneous data based on each data feature, and integrating the effectively processed multi-source heterogeneous data corresponding to each target to-be-filled catalogue, obtaining to-be-filled data corresponding to each target to-be-filled directory; and determining a target integrated document according to each to-be-filled directory and the to-be-filled data corresponding to each to-be-filled directory. The accuracy of the data integration result can be improved.

The invention discloses a credit risk slow release grouping method and a related device, and the method comprises the steps: building a mortgage guarantee contract identifier and a slow release product identifier of a corresponding virtual slow release contract based on a mortgage guarantee contract to be subjected to risk slow release grouping and a corresponding slow release product; based on the business contract to be subjected to risk slow release grouping and the corresponding slow release product, establishing a business contract identifier and a slow release product identifier of the corresponding virtual business contract; and based on the virtual business contract and the virtual release contract, establishing a virtual business contract identifier and a virtual release contract identifier of the corresponding credit risk release group. According to the invention, by establishing the virtual business contract and the virtual release contract, direct comparison between debt items and release items is avoided, the data volume directly used by grouping is greatly reduced, the processing speed is improved, and double identifiers (the master node and the slave node) are adopted for grouping, so that the use of a data table is reduced, and the efficiency is improved. Judgment and grouping can be carried out only through double identifiers, so that the processing efficiency is greatly improved, and the data redundancy is reduced.