227results about How to "Maintain consistency" patented technology

The invention belongs to the technical field of electric power data security management and intelligent question answering, and particularly relates to an electric power data security policy large model question answering system and method based on relation pooling. The system comprises a power data security policy knowledge base, a language model, a question processing module, an answer generation module and a user output module. Data of the electric power data security policy knowledge base comes from an electric power data security policy file; the language model converts a natural language problem into a structured query for knowledge base retrieval; the question processing module retrieves policy terms related to the natural language question to serve as retrieval results; the answer generation module generates a final answer according to the natural language question and a retrieval result of the knowledge base; by introducing the intelligent question-answering system combining the large language model and the knowledge base, the problems of low efficiency, inaccurate interpretation, incapability of dynamically updating and the like in the existing power data security policy query and management are solved.

The invention discloses a generation and evaluation method for acquiring long text description from a laparoscopic surgery image, which comprises the following steps of: constructing a cue word containing the laparoscopic surgery image, short text description, a target bounding box and surgery knowledge, and constructing long text description data by utilizing a large language model based on the cue word; constructing an image long text description generation model which comprises a pre-trained visual encoder, a visual feature query converter, a language decoder and an external operation concept vector database; performing supervised training on the image long text description generation model by using the long text description data; constructing a long text description evaluation method to evaluate the trained model; the method comprises the following steps: acquiring an input laparoscope image video stream through a laparoscope image system, and screening a key frame as a to-be-processed image; and inputting a to-be-processed image into the trained and evaluated model to obtain an image long text description result. According to the method, the ability of understanding operation details in the image can be enhanced, and more comprehensive operation image description can be generated.

The invention relates to multi-mode signal processing, and provides a signal processing method of a computer system. The method comprises the following steps: acquiring different modal signal data by using a plurality of sensors and performing timestamp synchronization; a depth time sequence alignment network and a multi-layer dynamic time warping algorithm are utilized to ensure signal time consistency; multi-modal signal features are extracted and fused through a multi-stream depth feature extraction network and a cross-modal attention mechanism; the system adopts a dynamic convolution kernel generation and meta-learning technology to carry out adaptive signal processing; noise suppression and signal optimization are carried out by using a multi-mode noise reduction auto-encoder and a generative adversarial network, and parameters are optimized and processed through closed-loop feedback control and reinforcement learning strategies. According to the method, synchronization, fusion, adaptive processing, noise suppression and real-time feedback control of multi-mode signals are realized, and the method has the advantages of high precision, high robustness and real-time performance.

The invention relates to the technical field of plant extraction, in particular to an intelligent plant extraction control method and system, and the method comprises the following steps: based on historic plant extraction data, including temperature, pressure and pH value during extraction, analyzing the long-term trend of parameters, predicting the requirements of plant extraction conditions by simulating parameter reactions under various conditions, and obtaining a plant extraction result; and obtaining a parameter prediction result. According to the method, long-term trend prediction of parameters such as temperature, pressure and pH value is realized through analysis of historically recorded plant extraction data, so that the parameters of extraction equipment are adjusted in advance, changes of different plant materials and environmental conditions are effectively adapted, the extraction efficiency is optimized, and by dynamically simulating the expression of the extraction efficiency in various time periods, the extraction efficiency is improved. According to the innovative scheme, an optimal extraction time window is mined, resource consumption and extraction time in the extraction process are reduced, and meanwhile the quality and consistency of extracts are kept.

The invention relates to the technical field of assembly welding, and particularly discloses an assembly welding positioning method and device for automobile parts. A welding state image between a target hush pipe and a target partition plate is collected through a camera; carrying out welding state mask segmentation on the welding state image by using an image identification and analysis algorithm based on computer vision, and then carrying out welding state feature extraction on the segmented welding detection area state mask image; and according to the expression obtained through neighborhood importance optimization of the extracted welding detection state characteristics, intelligent detection on whether defects exist in the welding state between the target hush pipe and the target partition plate or not is achieved. In this way, tiny defects such as tiny cracks and internal pores can be captured, and therefore the accuracy of defect recognition is improved. Moreover, the detection speed is greatly improved, the consistency and stability can be maintained, and the probability of missing detection or false detection is reduced, so that each welding point is ensured to be subjected to strict quality control.

The invention discloses a scale-effect-free mine dynamic disaster fine monitoring and dynamic early warning method, which comprises the following steps of: arranging a multi-point micro-seismic monitoring network on a coal mine working face, and continuously acquiring and preprocessing micro-seismic signals; an innovative analysis positioning algorithm is adopted to accurately analyze the accurate position and time information of the micro-seismic source; in combination with signal features and positioning data, a four-dimensional joint kernel density estimation and confidence interval theory is innovatively applied, a rock burst risk assessment model is constructed, and a danger level classification standard is determined; and the system calculates risk indexes in real time and dynamically issues early warning. According to the invention, the precision, timeliness and reliability of monitoring and early warning of the dynamic disasters in the mining area are obviously improved, and key technical support is provided for safe production of a coal mine.

The invention discloses an intelligent driving method and system for a small-spacing display screen based on a glass substrate, and relates to the technical field of display driving, and the method comprises the steps: building a light source characteristic model of the small-spacing display screen based on the glass substrate according to the current intensity of an input signal and the adjustment parameters of a backlight source; acquiring brightness output at the current moment according to the light source characteristic model, and acquiring operation parameters of the small-spacing display screen based on the glass substrate at the current moment; according to the brightness output and operation parameters at the current moment, multi-dimensional adjustment factors are calculated, and the multi-dimensional adjustment factors comprise a brightness compensation factor, a power optimization factor and a backlight dynamic adjustment factor; and performing threshold judgment according to the multi-dimensional adjustment factor, and when a preset threshold condition is met, performing brightness compensation, power optimization and backlight dynamic adjustment. Through comprehensive application of dynamic brightness adjustment, self-adaptive power optimization and multi-dimensional adjustment factors, stability, energy conservation and adaptive optimization of the display effect under different environmental conditions are realized.

The invention relates to the technical field of projectors, in particular to a projector control method and a projector. The method comprises the following steps: performing image projection signal processing on target projection image data to generate initial projection picture data; performing projection point cloud space-time registration on the initial projection picture data by using the dual laser radar assembly to obtain projection scanning point cloud space data; performing shielding area geometric feature analysis on the projection scanning point cloud spatial data, determining an ideal projection area, and generating ideal rectangular projection area data; performing intelligent projection control parameter processing on the ideal rectangular projection area data to obtain intelligent projection control parameters; and performing projection attitude control instruction processing on the intelligent projection control parameters to obtain projection control optimization effect data. According to the invention, the projection control parameters are automatically adjusted through intelligent identification of the projection surface, so that the projector can maintain a stable projection effect in different environments, and the quality of a projection image is remarkably improved.

The invention discloses a multi-task image processing method, system and device, and relates to the technical field of image processing, and the method comprises the following steps: constructing a multi-task network model; inputting the image data set into a multi-task network model to respectively obtain an infrared enhanced image, an infrared super-resolution image, an infrared and visible light image fusion image and an infrared image colorization image; and calculating a loss function between different images output by the multi-task network model and the infrared image and the visible light image in the input image data set, and carrying out loop training on the multi-task network model. According to the technical scheme, through unified training of the multi-task model, local details are effectively extracted, global consistency is kept, the processing efficiency and the image quality are greatly improved, redundant steps in the processing process are reduced, and the robustness and adaptability of the system are improved.

The invention discloses a user track privacy protection method and system fusing a generative model and three-stage personalized differential privacy, and relates to the technical field of data security, and the method comprises the steps: obtaining real user track data, and carrying out the preprocessing of the real user track data to form standardized track representation; training a depth generation model to generate synthetic trajectory data; performing density clustering on the synthetic trajectory to obtain a feature region and calculating a region centroid; point-level privacy budgets are distributed according to three stages of the area proportion, the centroid distance and the global density; constructing an adaptive elliptical disturbance domain based on the regional covariance, sampling candidate confusion points in the disturbance domain and applying road feasibility screening; and calculating a score based on the privacy budget and the utility function, and sampling replacement points by adopting an index mechanism to output a privacy protection trajectory. According to the technical scheme, the track structure continuity and the road semantic consistency are remarkably improved under the condition that the differential privacy constraint is met, and the privacy intensity and the data availability are both considered.

The invention discloses a number-real fusion test method for reliability of a blade disc structure of an aero-engine, and is applied to the field of time-varying reliability evaluation of the aero-engine. The method comprises the following steps: acquiring response data of a key part of a leaf disc structure under a full flight cycle; establishing a finite element virtual entity to obtain a time-varying input variable and a time-varying output response of the aero-engine bladed disc structure under the full flight cycle; establishing a physical information embedded loss function, and establishing an optimal physical information embedded multi-response regression model based on a Bayesian neural network inference framework; and extracting a large batch of time-invariant data sets, fitting a limit state function by using the established multi-response regression model, and calculating the reliability of the time-varying system based on the Monte Carlo thought to complete the reliability evaluation of the time-varying system. According to the method, a complex time-varying reliability evaluation problem is converted into a time-invariant response regression problem, and the calculation precision is effectively improved while the calculation task is simplified.

The invention belongs to the technical field of machine vision detection, and discloses a product appearance defect identification method and device, equipment and a medium. The method comprises the following steps: obtaining a to-be-recognized image of a product appearance, and processing the to-be-recognized image into a binary image; carrying out contour extraction in the OpenCV model to obtain a contour boundary of the product defect in the to-be-identified image; using a Douglas-Peucker algorithm to extract contour vertex coordinates from the contour boundary, and calculating the contour area of the product defect based on the contour vertex coordinates; determining a minimum bounding box containing a contour boundary through a contour searching method, extracting vertex coordinates of the bounding box, and calculating the area of the bounding box based on the vertex coordinates of the bounding box; and based on the contour area and the bounding box area, calculating an area error ratio of the contour area to the bounding box area, and based on the area error ratio, determining an identification result including qualified product appearance and unqualified product appearance. The detection efficiency can be effectively improved, and the product omission ratio is reduced.

The invention discloses a medical image segmentation method and device based on hierarchical multi-scale CNN-Transform, and relates to the field of deep learning, a medical image segmentation model based on CNN-Transform is constructed and trained, a trained medical image segmentation model is obtained, a to-be-segmented medical image is obtained and input to the trained medical image segmentation model, and the to-be-segmented medical image is obtained. Inputting a to-be-segmented medical image into the stem layer for block segmentation to obtain a block image, and inputting the block image into a coding module to obtain a coding feature of a first stage and a coding feature of a third stage; inputting the coding feature of the first stage and the coding feature of the third stage into a double-layer feature fusion module to respectively obtain a calibrated coding feature of the first stage and a calibrated coding feature of the third stage; and inputting the calibrated coding characteristics of the first stage and the calibrated coding characteristics of the third stage into a decoding unit to obtain a prediction segmentation result. According to the method, the modeling capability of the model on the multi-scale long-range dependency relationship and the local space information can be improved.

The invention discloses a virtual fitting video generation method, a model training method, electronic equipment and a computer readable storage medium. The video generation method comprises the following steps: acquiring a human body video and a costume picture corresponding to target costume; extracting target clothing features and human body features corresponding to the video frames; fusing the target clothing feature with each human body feature in a spatial dimension; performing feature adjustment on the target clothing feature based on each human body feature to obtain each human body matching clothing feature matched with the human body in each video frame; and fusing each space fusion feature and each human body matching clothing feature in a time dimension to obtain a time fusion feature, and obtaining each human body try-on video frame on which the target clothing is tried according to the time fusion feature. Through the scheme provided by the invention, the generated virtual try-on video has better inter-frame continuity and fluency, so that the authenticity of the final virtual try-on video is improved, and the virtual try-on effect is better.

The invention discloses a commodity recommendation system based on artificial intelligence, and the system comprises a user behavior tracking module which is used for collecting and processing the multi-source behavior data of a user; the commodity feature extraction and fusion module is used for acquiring and analyzing multi-modal information of commodities; the dynamic updating module is used for adjusting a recommendation list in real time according to instant user behaviors and long-term preferences in combination with short-term memory and long-term memory; the situation awareness module takes external factors such as time, place and weather as input; the explanatory enhancement module is used for adding an explanatory layer for a black box model by using an explanatory machine learning model; the personalized sorting optimization module is used for dynamically adjusting the feature weight and improving the click rate and the conversion rate; and the privacy protection module is used for protecting user privacy by adopting a differential privacy technology. According to the commodity recommendation system and method provided by the invention, many problems existing in a traditional recommendation system are overcome, and a more efficient, more intelligent and safer commodity recommendation service is realized.

The invention provides a receiving waveform position judging method of an ultrasonic flow metering device, and aims to improve the reliability of flight time measurement and reduce flow metering errors. According to the method, head wave and tail wave detection is achieved through the variable threshold comparator, the threshold is dynamically adjusted to adapt to different detection stages, and it is ensured that echo signals are accurately recognized. Through combination of zero crossing point flight time measurement and pulse width difference comparison, the method can determine the position of a tail wave, forwards presumes the position of an echo waveform, and judges the accuracy of a zero crossing point. In addition, the measurement accuracy is further improved by adjusting the phase of the transmitted ultrasonic signal to enhance the tail wave characteristic. The method is suitable for the field of flow measurement of water meters, heat meters, gas meters and the like, and metering errors caused by signal fluctuation or interference are effectively reduced.

The invention belongs to the field of sequence recommendation, and particularly relates to a contrast learning sequence recommendation method and system based on time interval data enhancement. The method comprises the following steps: acquiring original sequence recommendation data, wherein the original sequence recommendation data is a user behavior sequence of a plurality of users; dividing each user behavior sequence into a plurality of subsequences, and determining the longest uniform subsequence according to the time standard deviation and the sequence length of each subsequence; replacing and inserting the longest uniform subsequence in each user behavior sequence, and replacing the longest uniform subsequence in different user behavior sequences to obtain enhanced sequence recommendation data; wherein the enhanced sequence recommendation data is used for enhancing training of a contrast learning sequence recommendation model. According to the method, the uniformity of the global sequence and the local sequence is considered. By inserting new items between related items, it can be ensured that the time difference of local sequences is reduced, which helps to better capture user interest changes in a short term. And selecting the longest uniform sub-sequence to ensure that the longest uniform sub-sequence has enough similarity with the global sequence. And the inserted items are more similar to surrounding items, so that the consistency and coherence of recommendation can be kept. Therefore, the accuracy of the contrast learning sequence recommendation model is further ensured.

The invention relates to the technical field of LED semiconductor manufacturing, solves the problem that in the prior art, quality and consistency cannot be kept in the packaging and storage process of finished LED semiconductors, and provides an LED semiconductor production data tracing analysis method and system. The method comprises the steps that according to a unique identifier of a finished LED semiconductor, a taping scheme is obtained, and the taping scheme comprises a taping mode and a taping position; the finished LED semiconductor is subjected to braiding treatment according to the braiding scheme, and an LED light bar is obtained; the LED light bar is subjected to quality detection, a quality detection result is obtained, and quality detection comprises optical detection, electrical detection and mechanical detection; generating a unique identifier corresponding to the LED light bar passing the quality detection; and according to the unique identifier and the corresponding quality inspection result, carrying out warehousing processing on the LED light bar to obtain an LED product. The quality and the consistency can be kept in the packaging and storing process of finished LED semiconductors.

The invention provides a query page generation method and device based on data configuration, equipment and a medium, and relates to the field of data processing. According to the method, by calling the initial query component, it is ensured that a unified starting point exists in the development process, so that the consistency and maintainability of codes are kept, and meanwhile the development time is saved. The target query component is generated by configuring the query page attribute of the initial query component, the query interface can be quickly customized and adjusted according to different query requirements, consistency and reusability between different query pages are ensured, and the workload of repeated development is reduced. The query page of the target data is generated by utilizing the target query component, so that a new query function can be quickly deployed, manual layout and coding do not need to be performed every time, repeated work is reduced, the code reuse rate is improved, the development process is simplified, and the development efficiency of the query page is improved.

The invention discloses a cold-chain pork quality dynamic evaluation method and system based on multi-source data fusion, and relates to the technical field of data processing and intelligent evaluation, and the method comprises the following steps: collecting multi-source signal information of a whole cold-chain transportation process, sorting according to a unified time sequence, continuously arranging all signals on a time axis, and carrying out data processing on all the signals; a complete dynamic record is formed; and extracting each time interval and signal amplitude change track from the formed dynamic record, analyzing a signal section with repeated wave crests in a short time, and generating a preliminary data manuscript for reflection interference judgment. According to the invention, through time sequence arrangement and dynamic association of multi-source signals, a wave crest track analysis mechanism is constructed, real-time identification and correction of reflection interference are realized, and continuity and accuracy of a gas concentration curve are ensured; and by generating a reflection source position list and adjusting numerical value distribution of repeated fragments, false fluctuation is eliminated, and the stability and reliability of cold-chain pork quality evaluation are improved.

The invention relates to the field of industrial control, and discloses a control authority distribution system which comprises an authority request module, an authority distribution module, an authority release module and a safety fault-tolerant module. The permission request module is used for collecting control permission requests of the operation terminals; the authority distribution module dynamically processes the requests according to an M / M / 1 queuing model, a game theory model and a Markov decision process, determines the priorities of the operation terminals, and adopts the game theory model to solve conflicts if a plurality of operation terminals request simultaneously; the permission release module automatically releases the control permission under the condition that the operation is completed or overtime; and the security fault-tolerant module verifies the consistency and security in the permission allocation process through a Byzantine fault-tolerant algorithm. According to the invention, the response speed of the system can be improved, the security of multi-terminal operation and the resource utilization efficiency are ensured, and strong fault-tolerant capability and stability are provided.

The invention relates to the technical field of weld joint dynamic modeling, in particular to a thin-wall shell weld joint dynamic modeling method based on a common shell unit, which comprises the following steps of: S1, dispersing the middle surface of a welding part by a global shell grid, and simulating a weld joint by using a CSE instead of a rigid connection unit; s2, simplifying the modeling process of the CSE by adopting a grid common node processing method; s3, constructing an interface shell unit to replace part of GSM on the two sides of the welding area, and achieving the grid consistency requirement; s4, the CSE welding seam modeling method is applied to welding of the thin-wall shell for dynamic simulation analysis; and S5, performing result verification and adjustment on the data obtained by simulation in the step S4. According to the method, the ISE unit is introduced to meet the grid consistency requirement of the non-matched connection interface; building a weld joint dynamic model based on a CSE and RE modeling method, and carrying out dynamic simulation analysis and experimental research; the problem that the finite element analysis accuracy is affected due to the fact that an existing connecting unit cannot accurately simulate the real characteristics of weld joints is solved.

The invention discloses an image-text question answering method and system based on multi-modal alignment, electronic equipment and a medium, and the method comprises the steps: obtaining a scene image and a question text corresponding to a current dialogue round in response to a dialogue instruction, and determining an initial weight corresponding to the scene image; obtaining a historical image feature set and a historical text feature set of a preset multi-modal feature alignment model; inputting the scene image and the question text into a feature extraction module for feature extraction, and outputting image features and text features; combining the image features and the initial weights into a historical image feature set to obtain an image coding set, and combining the text features into a historical text feature set to obtain a dialogue coding set; performing semantic alignment on the image coding set and the dialogue coding set through a weight matching module; and generating a reply text according to the target image coding features after semantic alignment. In the embodiment of the invention, the image features and the text data can be effectively combined to generate accurate answers.

The invention relates to the technical field of OLED micro-displays, and discloses a temperature sensor calibration and external temperature compensation method for an OLED micro-display, and the method comprises a temperature compensation parameter storage module which is used for storing the temperature calibration data of the OLED micro-display through a one-time programmable memory OTP. According to the temperature sensor calibration and external temperature compensation method for the OLED micro-display, the actual working temperature Tactual is calculated by using the current temperature register value REG1 measured by the temperature sensor and factory calibration data T0 and REG0, the brightness change is compensated by adjusting the common voltage Vcom in real time, and the temperature of the OLED micro-display is compensated by combining a temperature compensation formula. The brightness of the display is accurately controlled by adjusting the electric field intensity, the Vcom is improved in a low-temperature environment to compensate brightness reduction, and the Vcom is reduced in a high-temperature environment to prevent excessive light emission or thermal damage, so that the problem of inconsistent display effects in long-term use is solved, and the user experience is improved.

The invention provides a CBS-YOLOV5-based fabric defect detection method, which comprises the following steps of S10, capturing fabric defect images, establishing a data set, and preprocessing the images in the data set to obtain a fabric image data set with labels; s20, dividing the preprocessed data set into a training set, a verification set and a test set according to a given proportion, wherein the proportion of the training set to the verification set to the test set is 8: 1: 1; s30, adding the CA attention module, the BiFPN mechanism and the SIoU loss function into a network structure, and constructing a CBS-YOLOV5 model; s40, the paths of the training set and the verification set and the initial training weight file path are input into parameters required for training of the CBS-YOLOV5 model for training, and the trained CBS-YOLOV5 model is obtained; the invention provides a CBS-YOLOV5-based fabric flaw detection method and system, and the CBS-YOLOV5 model adopted by the invention is an end-to-end learning model, can automatically learn feature representation from an original image, does not need to depend on manual feature engineering, reduces the workload, and improves the flaw detection performance.

The invention discloses an engine grid-connected control method, and relates to generator grid connection, which comprises the following steps of: starting a timing period after entering a PTO (Power Take Off) mode, clearing an adjusted step length after the timing period is ended, restoring the adjusted step length to an initial step length, and restoring the rotating speed of an engine to a droop rotating speed at the same time. Potential instability caused by step length adjustment of the system is avoided, the overall efficiency of the system is improved, consistency and interpretability of data can be kept, and subsequent analysis and optimization are facilitated.

The embodiment of the invention provides a wafer batch management method and device, an MES system, a storage medium and a program, and the method comprises the steps: obtaining a Lot merging request which comprises a plurality of Lot identifiers of Lot; based on the Lot identifier, acquiring account information of a plurality of Lants; based on the account information, judging whether the plurality of Lets meet a merging condition, wherein the merging condition comprises that pollution identifiers in the account information are consistent and identifiers of the next process step are consistent; if the plurality of Lants meet a merging condition, merging the plurality of Lants to obtain a merged Lant, including: obtaining wafer identifiers of the plurality of Lants based on account material information, generating a virtual Lant identifier, and creating a first mapping relationship between the wafer identifiers and the virtual Lant identifier; storing updated account information, wherein the updated account information comprises the first mapping relation and the account information; and carrying out process dispatching on the merged Lot based on the virtual Lot identifier. The embodiment of the invention can improve the resource utilization rate of a production line and improve the wafer production efficiency.

The invention discloses a parasite egg detection method and system, and relates to the technical field of egg detection. Comprising the following steps: collecting a certain volume of a test sample, putting the test sample into a centrifugal tube, performing centrifugal operation, and reserving a precipitation part at the bottom of the tube; re-suspending the centrifuged precipitate part in normal saline, injecting the mixed liquid into a microfluidic chip, arranging a protruding electrode in the microfluidic chip, and coating the surface of the electrode with a specific antibody to capture eggs; current at different moments is calculated, and meanwhile microscope images of the electrodes are collected; establishing a Yo lov5s model, and training the Yo lov5s model by taking the contour of the parasite egg as a label; inputting a microscope image of the electrode into the Yo lov5s model, identifying a parasitic ovum contour in the image, and performing feature extraction on a contour image part; and jointly judging whether the parasitic eggs exist in the sample based on the change of the current at different moments in combination with the characteristic parameters, and if so, calculating the concentration of the parasitic eggs based on the change of the current and the number of the parasitic eggs.

The invention discloses a forestry remote sensing data lightweight method based on submerged space optimization, and belongs to the technical field of image processing, and the method comprises the steps: obtaining a to-be-compressed forestry remote sensing image data set D1; constructing a data lightweight network, wherein the data lightweight network comprises a variational auto-encoder, a clustering unit, an image classification network, a multilayer feature extraction network and a discriminator; training a variational auto-encoder and an image classification network by using the D1; generating a clustering data set D2 based on the encoder and the clustering unit; and training the data lightweight network to update the submerged space variable in the D2, and reconstructing the data by using a decoder. Through data set distillation improvement based on the variational auto-encoder and element gradient optimization, a compressed data set with high precision and representativeness is generated, the bottleneck problem of forestry remote sensing data set storage and processing is effectively solved, and the data storage amount can be reduced while the model training precision is kept. The method is suitable for various practical application scenes such as forestry resource monitoring, forest health assessment and disaster response.

The invention relates to the technical field of data asset management, in particular to a data asset management system and method. The method comprises the following steps: acquiring a data asset information set from different data sources in real time and performing tag structure sub-column division to obtain data asset information tag description structured sub-columns, and meanwhile, performing time sequence creation synchronization processing and integrating and storing the data asset information tag description structured sub-columns into a data asset management database; performing use frequency and sensitivity evaluation analysis on each piece of data asset sub-information in the data asset management database, and performing data asset access utility evaluation analysis to obtain data access utility of each piece of data asset sub-information; and performing dynamic access right control and full life cycle management design on each piece of data asset sub-information in the data asset management database, and performing automatic management and report feedback recording to generate a data asset information management report. The transparency, safety and efficiency of data asset management can be improved.