818 results about "Dataspaces" patented technology

The invention provides a cross-modal retrieval method for semantic and vector fusion in a data space, which belongs to the field of cross-modal information retrieval, and comprises the following steps: firstly, collecting and preprocessing multi-modal data; generating modal embedding and storing by utilizing the pre-training model; a shared semantic space is constructed, cross-modal vector alignment is optimized through comparative learning, and a modal mapping network is designed to enhance the embedding projection effect; storing the aligned embedding by using a Milvus database, and constructing an HNSW index; user text or image query is processed, text query analyzes limiting conditions to generate enhanced embedding, and image query extracts characters through OCR and fuses the characters with image features to generate embedding; in a database, through condition screening and semantic similarity calculation, a Top-K candidate item is retrieved; performing multi-modal correlation sorting on the candidate results and returning the results; according to the method, the shared semantic space is constructed, the alignment effect of different modal embedding is optimized, efficient storage and index management of multi-modal embedding are carried out, and real-time retrieval of large-scale cross-modal data is achieved.

The invention provides an automatic pavement settlement monitoring method and system based on a shield undercrossing airport runway. The dynamic database is constructed by collecting operation parameters such as shield tunneling machine propelling pressure, cutterhead torque and synchronous grouting pressure in real time and combining three-dimensional deformation data obtained through laser scanning. Strain sensing units are arranged in the soil layers to form a layered monitoring network, strain changes of the soil layers of different depths are collected, and spatial correlation is established between the strain changes and the tunneling position. And analyzing a spatial attenuation rule through a dynamic association processing unit, and generating a multi-dimensional feature data set. And establishing a settlement prediction model, fusing the shield dynamic load sequence and the layered strain conduction characteristics, and outputting settlement distribution information. And the system automatically compares the settlement difference value of the adjacent areas with a preset safety threshold value, and generates a graded early warning signal after verification of the three-dimensional deformation data space. According to the technical scheme provided by the invention, real-time three-dimensional prediction and spatial verification type graded early warning of settlement of the airport runway are realized.

The invention provides a business data sharing fusion system and method based on a trusted data space, and relates to the technical field of data sharing. According to the method, sharing and fusion of service data are realized by constructing a trusted data space infrastructure. The method comprises the following steps: firstly, establishing a node path planning model for priority evaluation and data matching; then forming a model collaborative deployment scheme to distribute tasks to edge nodes; then perception scoring and resource scheduling are carried out on the tasks, and a multi-task concurrent transmission scheme is generated; constructing a multi-domain network service level protocol evaluation model to perform service decomposition and business collaborative management; and finally carrying out heterogeneous processing and data fusion on the business data. According to the method, the problems of information islands, multi-source heterogeneous data fusion and cross-domain business collaboration among regional mechanisms are solved, and the system performance and the user experience are improved.

The invention discloses a federated learning driven trusted data space cross-domain cooperative computing method, and relates to the technical field of data processing, and the method comprises the following steps: carrying out access trust verification on a plurality of data providing domains according to a dynamic trust mechanism; after the verification is passed, accessing each data providing domain into a trusted data space for local training, and generating a local model; performing cross-domain cooperative calculation on the plurality of local models, and establishing an initial global model; and carrying out loss generalization evaluation on the initial global model, and triggering a differential feedback learning module to carry out iterative reinforcement to generate a global reinforcement model. According to the method, the technical problems of limited data privacy protection, trust missing among different mechanisms and insufficient model generalization ability of cross-domain data cooperative calculation in the prior art are solved, multi-party cooperation is realized on the premise of no data leakage through a dynamic trust mechanism and differential privacy protection, and the reliability of the cross-domain data cooperative calculation is improved. And the precision and generalization ability of the global model are improved.

The invention discloses a multi-factor authentication trusted data space access control method, platform and medium, and relates to the technical field of data security, the method comprises the following steps: analyzing the authority, record, path and target of a request access user, and obtaining access parameters; generating a verification gradient based on the security levels of parameter matching permissions, records, paths and targets; in combination with the gradient and the user authentication record, creating an authentication demand factor with gradient constraint; and generating a space access permission according to the authentication result, and controlling the trusted data access permission. According to the scheme, the data security protection capability is enhanced through a dynamic multi-factor verification mechanism. According to the method and the device, the technical problem of insufficient data security protection capability caused by lack of a multi-factor dynamic authentication and fine-grained access control mechanism in a data space access process in the prior art is solved; the technical effects that the access authority is dynamically adjusted based on multi-factor authentication, and the data security and credibility in the data space access process are effectively improved are achieved.

The invention discloses a power transmission line state simulation and prediction method based on digital twinning, and the method comprises the following steps: accessing meteorological data, electrical data, space and asset data and historical state data, carrying out the preprocessing, and generating a multi-source spatial-temporal feature sequence set; constructing a double-domain cross-coupling time convolution twinborn model, and obtaining corresponding feature representation through a quick response path and a slow response path; physical consistency state representation is generated through a physical constraint cross gating layer; outputting a prediction result set through a simulation engine; online observation data are obtained, and the model is corrected based on virtual and real residual errors; and generating a current prediction result set by using the corrected model, and converting the current prediction result set into a scheduling and operation and maintenance strategy set. According to the method, the double-domain cross-coupling time convolution twin model and a virtual-real closed-loop correction mechanism are adopted, multi-scale state simulation prediction of the power transmission line is achieved, and the method has the advantages of being high in precision, robustness and performability.

The invention relates to the technical field of geological disaster monitoring, and discloses a point-like landslide and debris flow potential degree adaptive monitoring and early warning method. According to the method, a dot matrix monitoring equipment array is arranged, and displacement data and environmental parameters of multiple monitoring points are collected; analyzing the displacement data timestamp through a timeline analysis module, generating a dynamic timeline, and marking geological event nodes; a geographic information system is combined to carry out spatial mapping on displacement data, and environmental parameters are fused to obtain a preliminary potential degree evaluation result. The pattern recognition engine classifies displacement speed and deformation characteristics in the preliminary result to generate a deformation characteristic spectrum with a space-time label; calculating a dynamic potential degree evaluation map according to the multi-factor weighted evaluation model; and adjusting an early warning threshold according to a user instruction, generating a personalized early warning rule set, and scanning the atlas to output a multi-stage early warning response scheme. On the basis of an early warning feedback iteration updating model and an engine, monitoring data are newly added to trigger and re-analyze in real time, a related scheme is updated in a linkage mode, and different scene requirements are met.

The invention discloses a remote proving method for a trusted data space, which relates to the technical field of computer and data security, and comprises the following steps: initializing a trusted environment and generating a dynamic identity key for a heterogeneous terminal containing a CPU (Central Processing Unit), a GPU (Graphic Processing Unit) and an FPGA (Field Programmable Gate Array) based on a hardware security module and a physical unclonable function, and generating a challenge value by a verifier by using a quantum random number; the method comprises the following steps of: firstly, transmitting to a proving party through quantum encryption and a neuromorphic photonic network, constructing proving by the proving party by adopting a tensor decomposition zero-knowledge proving protocol, finishing multi-stage verification on a verification party in combination with a space-time cause and effect graph and quantum signature aggregation, and finally realizing dynamic trust evaluation and adaptive strategy adjustment through a quantum Bayesian network, reinforcement learning and biological feedback. According to the method, the remote attestation performance of the trusted data space is improved, dynamic trust evaluation is realized by means of the quantum Bayesian network and biological feedback, attacks are effectively resisted, real-time requirements are met, trust is accurately evaluated, and the development of the trusted data space is promoted.

The invention belongs to the technical field of logistics information, and discloses a multimodal transport trusted data space construction method based on privacy calculation and a block chain. The method comprises the following steps: deploying a modular intelligent data gateway at a core node of a multimodal transport line, unifying the format of multi-source heterogeneous original data, and chaining a hash value; after the multi-source heterogeneous data is subjected to customization processing, key metadata attributes of all the data are registered and linked in real time; constructing a core ontology model, and establishing a cross-domain semantic interoperation capability; establishing a privacy calculation and block chain collaborative dual-channel architecture, and cooperatively training an ETA prediction model in a local data isolation environment by adopting transverse federal learning to ensure that original trajectory data is not out of a domain; constructing a dispute arbitration and credible verification system, and realizing an arbitration process of judicial verification when a transportation dispute occurs; data minimization disclosure and compliance sharing are achieved through dynamic access control. According to the method, multimodal transport data can be available and invisible, and the whole operation process can be audited.

The present disclosure describes methods, systems, apparatus, and media for object identification and classification, utilizing multi-feature and multi-modal data. This includes shape, material, brand, price, odor, taste, tactility, and sound. The system integrates a server space for data processing, a querying device for iterative searches, and a data interface module for refining results. It features AI-driven image optimization, feature extraction, and pattern recognition, employing novel techniques for fusing multi-feature and multi-modal embeddings utilizing multi-head attention. Additionally, a linker module powered by two active learning with feedback loops AI models consolidates scattered data into a unified object information database. The system also employs novel AI algorithms for isolating the object of interest through a saliency map and semantic analysis, as well as for enhancing raw images with a GAN-autoencoder.

The invention discloses an AI-based automatic connection and handshake protocol for a trusted data space connector. The AI-based automatic connection and handshake protocol comprises a data supply end connector, a data demand end connector and a platform operation end, the data supply end connector is used for collecting and preprocessing data; the demand end connector is used for receiving and processing data; the platform operation end is used for connection management, authority distribution and security auditing; the method has the beneficial effects that through automatic connection and an intelligent handshake protocol, manual intervention is reduced, and the data circulation cost is reduced; multi-factor authentication, dynamic encryption and privacy protection technologies are adopted to ensure the safety of the whole life cycle of the data; aI and machine learning technologies are introduced, so that the system can intelligently select an optimal strategy according to real-time network conditions and data features; interoperation and data sharing among different data spaces are realized, and circulation and value mining of data elements are promoted.

The invention discloses a real-time interaction and intelligent management method for a multi-dimensional data space, and relates to the technical field of data interaction management, and the method comprises the following steps: I, collecting multi-source data, including structured data, unstructured data and spatio-temporal data, in real time through a diversified collection terminal, and dynamically adjusting the sampling frequency based on a data entropy value, carrying out cross-device space-time synchronization calibration and edge end lightweight processing on the acquired data; iI, preprocessing the data flow in real time, fusing the multi-modal data, and the like. According to the method, the sampling frequency is dynamically adjusted based on the data entropy value, and in combination with edge end lightweight processing, invalid data transmission is reduced, and the key data acquisition efficiency is improved; hot data is stored in a time sequence database and a memory database, real-time monitoring of an emergency scene and second-level response of emergency command are supported, dynamic capacity expansion and shrinkage of computing resources are matched, edge-cloud end collaboratively distributes tasks, network delay is reduced, and system stability and response speed in a high-concurrency scene are guaranteed.

The invention provides a data security method and system fusing an MIN and a unified AI theory, and the method comprises the steps: S1, completing the multi-dimensional identification registration and synchronization of a data space in a multi-identification network MIN based on a data space identity identification DSID and an ontology semantic mapping frame; s2, acquiring a data acquisition record from a multi-identifier network MIN, and constructing an access control atlas in combination with a semantic vector of a data subject identifier DSID-Item; s3, analyzing the access request and verifying the authority, identifying the sensitivity level of the access request, and triggering a privacy enhancement mechanism when the sensitivity level is marked as medium-high-level privacy data; and S4, judging whether the data object reaches a value end point in the life cycle of the data object or not by taking a data space identity (DSID) registered in the multi-identifier network (MIN) as a retrieval anchor point, and if so, executing a verifiable multi-stage destruction operation. According to the invention, a full-life-cycle trusted data security technical scheme can be realized, and intelligent, explainable and efficient security management of data streams in a network space is realized.

The invention provides a data traceability verification method in a trusted data space, and relates to the technical field of zero-knowledge certification, the method comprises the following steps: collecting a plurality of operation records of target data in the trusted data space, and arranging the operation records according to a timestamp sequence to generate an operation sequence; converting into a state transition constraint condition; inputting the operation sequence into a pre-trained key node identification model, and outputting position identifiers of one or more key state transition nodes in the operation sequence; constructing a zero-knowledge proof circuit according to the operation sequence, the state transition constraint condition and the key state transition node, and operating the zero-knowledge proof circuit to generate a composite zero-knowledge proof; and providing the composite zero-knowledge proof as a data traceability voucher of the target data to a verification party to complete traceability verification of the whole processing process of the target data. The technical problems of privacy disclosure risk and low verification efficiency of data traceability verification in the prior art are solved.

The invention relates to the field of data traceability, and particularly discloses a natural resource data dynamic monitoring traceability method and system, and the method comprises the steps: building a multi-tense database, automatically writing real-time data into a corresponding partition according to a timestamp, and carrying out the incremental updating of a workflow; data confidence coefficient weights are introduced into SQL screening statements according to attribute tracing logic, and data legality is judged through weighted logic; constructing a land class evolution state transition matrix, determining a legal change path and an illegal path, and carrying out path deduction on attribute data missing to judge whether the attribute data missing is illegal change or not; and detecting land type mutation according to NDVI index change of a target remote sensing image, forming a three-dimensional tracing database of attribute data, space evidence and business files according to the attribute data and the spatial relationship, and dynamically monitoring and tracing natural resource data. The problems that the legal source of the construction land cannot be accurately traced due to land judgment errors and real-time data analysis and traceability are difficult in the prior art are solved.

The invention relates to a regional distributed photovoltaic power prediction method and system based on multivariate data cross-modal fusion, and belongs to the technical field of photovoltaic power prediction. Firstly, adaptive extraction of meteorological data spatial features and power data spatial heterogeneity is realized through a dynamic perception convolution kernel of AG-CNN, and a high-quality spatial basis is provided for cross-modal fusion; secondly, utilizing a two-dimensional dynamic attention mechanism of a DR-Transform to deeply mine cross-modal association of'historical power time sequence-future weather driving ', adapting to fusion requirements in different scenes through dynamic weight distribution, and capturing association evolution in a long period; thirdly, designing a cross-modal feature bridging module; and finally, verifying the robustness of the model in a typical scene, and ensuring that the model meets the precision requirement of multi-scale scheduling of the power grid.

The invention provides a credible data space construction method and system based on data sharing, and relates to the technical field of data processing.The method comprises the steps that S1, in response to a request of a user for sharing target data, credible preprocessing is conducted on the target data to obtain credible data; s2, establishing a decision-making capability model for a user to autonomously perform credible authorization on the credible data; s3, analyzing a multi-dimensional sharing risk of the trusted data; s4, planning an optimal authorization auxiliary unit sequence based on the multi-dimensional sharing risk and the decision ability model; s5, in the process that the user autonomously performs credible authorization on the credible data, sequentially executing the authorization auxiliary units in the optimal authorization auxiliary unit sequence; and S6, aggregating the credible data subjected to credible authorization to construct a credible data space. According to the method, the credibility and the security in the data sharing process are remarkably improved, and the quality of the shared data and the protection of user privacy are ensured.

The invention relates to the technical field of data cross-domain access control, in particular to a block chain-based trusted data space cross-domain access control method, system and device and a medium, comprising: receiving a data access request, and analyzing a target data identifier, a target heterogeneous system identifier and access scene information; obtaining the data attribute of the target data according to the target data identifier, generating a dynamic access strategy in combination with the access scene information, and deploying the dynamic access strategy into the block chain; mapping the dynamic access strategy into an equivalent access control rule, and converting the data access request into target compatible request data; verifying zero-knowledge proof provided by the user based on an equivalent access control rule and a user public key; after the verification is passed, routing the target compatible request data to the target heterogeneous system; and the target heterogeneous system generates original response data, converts the original response data into user-side compatible response data and returns the user-side compatible response data to the user. According to the invention, cross-system efficient cooperation is realized, and the real-time adaptability and privacy enhancement security of access control can be improved.

The invention discloses an implementation system, method and device for a multi-source heterogeneous data connector in a trusted data space and a storage medium, and relates to the technical field of data processing, the implementation system for the multi-source heterogeneous data connector in the trusted data space comprises a data source access layer, a data analysis layer, a data conversion and mapping layer and a data output layer; wherein the data source access layer is used for receiving a data source access request of a user and establishing connection with a target data source according to the data source access request; the data analysis layer is used for acquiring original data from the target data source and analyzing the original data according to a preset analysis strategy to obtain preliminarily analyzed data; the data conversion and mapping layer is used for processing the preliminary analysis data according to a semantic mapping rule to generate standardized data; and the data output layer is used for outputting the standardized data to a specified target application system through a standard interface.

The invention discloses a cross-data-space identity authentication method and device and a medium, and belongs to the technical field of identity authentication. The method comprises the following steps: constructing a cross-chain connector, and constructing an identity total chain connected with the cross-chain connector to store and manage decentralized identity documents of a plurality of data spaces; sending a data access request to the basic connector of the target data space through the basic connector of the to-be-accessed data space, so as to generate a receiving signal through the basic connector of the target data space; submitting a verifiable voucher to the target data space according to the voucher submitting requirement through the to-be-accessed data space; sending the verifiable voucher to a cross-chain connector through the target data space, and verifying the verifiable voucher based on the identity total chain and the identity chain of the to-be-accessed data space to generate a verification result; and if the verification result is passed, establishing a connection relationship between the target data space and the to-be-accessed data space. According to the method, cross-data-space safe and efficient identity authentication is realized.

The invention provides an underground comprehensive pipe gallery intelligent operation and maintenance management system based on BIM, and relates to the technical field of building information, and the system comprises a three-dimensional integration module which is used for constructing a three-dimensional digital integration platform of an underground comprehensive pipe gallery at a cloud end, uploading full life cycle data, ownership unit information and real-time operation parameters of the communication pipeline to a cloud central database, distributing a unique code for each pipeline unit, and establishing a corresponding cloud index relationship; and the space correction module is used for presetting three positioning monitoring nodes at the main inlet of the pipe gallery, the ventilation key node and the pipeline intersection based on the three-dimensional digital integration platform, constructing a stable triangular positioning monitoring architecture, calculating the geometric center and side length relation of the monitoring architecture through the three-dimensional coordinates of the three positioning monitoring nodes, and correcting the three-dimensional coordinates of the three positioning monitoring nodes according to the three-dimensional coordinates of the three positioning monitoring nodes. And generating a space topology correction value. According to the invention, the safety of the operation and maintenance of the underground comprehensive pipe gallery is realized by integrating the whole life cycle data of the pipe gallery, spatial positioning, intelligent risk early warning and multi-department cooperative linkage.

The invention relates to the technical field of distributed resource scheduling, and discloses a power distribution network distributed resource cluster optimization regulation and control method, system and device considering power communication coupling and a medium, and the method comprises the steps: obtaining the related data of a power distribution network and a communication network, and building a comprehensive division index set based on a target communication network; performing cluster division according to the index set to obtain a plurality of power distribution network distributed resource clusters; an optimization regulation and control model is constructed based on the division result, a target function is oriented to the minimum cluster operation cost, and power flow, communication operation and resource operation characteristic constraints are comprehensively considered; solving the model by adopting a time and event dual-drive solving strategy; a rapid solving method based on multi-graph convolution is utilized to extract a data space dependency relationship, a mapping mechanism from an operation state to an optimal strategy is constructed, and solving efficiency is improved; and performing optimization regulation and control on the cluster according to the solved optimal strategy to realize efficient and stable operation of the power distribution network under power communication coupling.

The invention relates to the technical field of projection display, and discloses a multi-projection picture splicing method and system based on geometric correction. The method comprises the following steps: acquiring initial parameters and original picture data of the multi-projection equipment, wherein the original data contains an overlapped region image and is acquired according to a preset direction; geometric correction is carried out on the original image, geometric distortion feature points are extracted, and a mapping relation matrix is generated; dividing projection boundaries based on the matrix, and adjusting parameters to form a correction parameter set; performing spatial registration on the picture data according to the parameter set to generate multi-channel data; and carrying out fusion processing on the multi-channel data overlapping region, eliminating light intensity difference and color deviation, and generating a continuous splicing picture. The system comprises a data acquisition module, a geometric correction module, a parameter adjustment module, a space registration module and a fusion processing module. Through high-precision geometric correction, adaptive fusion and dynamic adjustment, the precision and visual effect of multi-projection image splicing are improved, and the method is suitable for large-size display scenes and has the advantages of being high in environmental adaptability, high in automation degree and the like.

The invention belongs to the technical field of data circulation, and discloses a data circulation method and system based on a slice network and a trusted data space. Comprising the following steps: a connector obtains private network generation feedback to allow a user to access the connector through a corresponding slice private network on the basis of a pre-configured static route; obtaining a user credible voucher and an authentication message forwarded after addressing by the first router; verifying the user credible credential, analyzing the authentication message, and forwarding an obtained network attribute label to a network controller; and allowing the user to enter the trusted data space for data interaction through a second router when the user trusted certificate passes verification and the network attribute tag passes verification by a network controller. According to the invention, the security during data circulation is effectively improved.

The invention discloses a data life cycle management system in a trusted data space, which belongs to the technical field of data management, and comprises the following steps of: counting data from different sources, recording various change operations of the data and generating a data log; performing preprocessing and privacy judgment on the data to obtain the type and sensitive identification of the data; the method comprises the following steps: acquiring various change operations of data, and constructing a data change graph in a directed acyclic graph form; the change operation of the data is monitored by adopting an isolated forest algorithm, and the detection of the abnormal operation is realized; privacy protection is carried out when the data is queried through a preset self-adaptive noise mechanism; performing credibility evaluation on the data according to a preset credibility evaluation index system, and dynamically adjusting the size of the set noise based on the obtained credibility score of the data; according to the method, the acquisition timestamp of the data is obtained and is compared with the current UTC time for judgment, so that a judgment result is obtained, and the data is archived or destroyed.

The invention provides a secure sandbox system of a trusted data space, which comprises a data source module, a data secure sandbox platform module and an interaction layer module, the method comprises the steps that a data source module is used for encrypting data, encrypted data is transmitted to a data security sandbox platform module through an encryption transmission channel, and only a data source administrator has the authority to decrypt and calculate, and relates to the technical field of data security. Multiple security defense lines are constructed for the data, the data are always in an encrypted state in the circulation process, different operation environments are isolated from one another, and the risk of data leakage is greatly reduced.

The invention discloses a data space data directory transmission control method based on a digital contract, and the method comprises the steps: carrying out the abstract processing of a data directory in a data space into a standardized metadata model, and forming a tree directory structure; in response to the data directory transmission request, generating a digital contract instance based on an intelligent contract engine, and performing block chain anchoring binding on a digital contract and a target data directory node; analyzing a control strategy set in the digital contract through a contract interpreter; executing at least one of the following control situations in real time in the data transmission process: directory visibility control based on timeliness constraint, directory access chain control based on data blood relationship, directory content desensitization control based on sensitivity level and directory routing control based on transmission path credibility; and after directory transmission is completed, triggering verification logic in the digital contract, comparing the integrity hash value and the authority change record of the data directory before and after transmission, generating a verifiable auditing report, and storing the verifiable auditing report in the distributed account book.

The invention is suitable for the technical field of data circulation, and provides a trusted data space connector layer data circulation method and system, and the method comprises the steps: enabling data to access a trusted data space connector, and carrying out the preprocessing of the data; dynamically configuring an access control strategy according to the identity and authority of the data requester; data are virtualized and circulated among different security domains through a data cross-domain virtualization technology, and in the data circulation process, an end-to-end data encryption transmission technology is adopted; after a data requester obtains the data, the data is processed and analyzed by using a micro-isolation data cross-domain fusion processing technology. According to the method, the fusing index is generated by dynamically fusing the aging feature vector, the frequency risk spectrum and the sensitivity matrix, so that real-time parameter customization and risk adaptive adjustment of the access control strategy are realized, and time sequence change, frequency anomaly and data sensitivity difference in a complex access scene are effectively dealt with; and the dynamic protection capability of cross-domain data circulation is obviously improved.

The invention relates to the technical field of data processing, and discloses a distributed trusted data space construction method and system based on a block chain, and the method comprises the steps: enabling a participant to complete registration under a unique identifier of a data space through a digital identity certificate; dynamically creating a fragment block chain of the data space according to the unique identifier; the participant encrypts structured data and stores the encrypted structured data to the corresponding fragmented block chain to obtain a data block of the structured data; when a data interaction request of the cross-fragment block chain appears, generating a cross-chain verification certificate of the cross-fragment block chain based on zero-knowledge proof; data interaction of the fragmented block chain is completed through the cross-chain verification certificate, and an interaction audit record of the data interaction is generated; periodically aggregating the state hash of the fragmented block chain, and updating the global state snapshot under the unique identifier; according to the invention, the security of the trusted data space can be improved.

The invention belongs to the technical field of intelligent traffic, and discloses a multi-scale space-time fusion image feature extraction method based on traffic flow, which comprises the following steps of: 1, constructing a dynamic image generation module; a self-adaptive adjacency matrix is generated in combination with historical traffic data, spatial embedding and time embedding, the matrix is used for spatial-temporal feature extraction of a GCN layer, and the generated adjacency matrix can flexibly capture static and dynamic relationships; 2, constructing a learnable weighting module; according to the module, the weights of different features are adaptively adjusted, so that various feature information is effectively fused; 3, constructing a sequence feature mapper; through a recurrent neural network (RNN) and a sequence compression-expansion mechanism, dynamic features of time sequence signals are effectively extracted and enhanced. According to the method, adaptive adjustment of an adjacent matrix is realized through a dynamic graph generation module, the multi-feature fusion capability is improved in combination with a learnable weighting mechanism, and the long sequence modeling capability of an RNN layer is optimized by adopting a sequence compression and expansion strategy.