539 results about "Link data" patented technology

A full-link reconciliation method based on a snowflake algorithm, an apparatus, a device, and a medium are provided. The method includes: responding to a reconciliation request of a cross-border service and acquiring bill source data from a service end; parsing the bill source data, and converting the bill source data into target bill data; calling a reconciliation rule engine to acquire a corresponding reconciliation rule, selecting a corresponding reconciliation algorithm, and performing a full-link reconciliation task on the target bill data to acquire a reconciliation result; transmitting unbalanced data to a corresponding exception processing system for a check processing of abnormal data; generating, based on an optimized snowflake algorithm, a unique target ID to perform a corresponding bill association with the reconciliation result, automatically penetrating, according to the unique target ID corresponding to the reconciliation result, full link data of an information flow and a fund flow, and tracing, according to the unique target ID, a whole process of the corresponding bill flowing between the fund flow and the information flow, to achieve a complete closed-loop of reconciliation.

The invention relates to the technical field of micro-services, can be applied to the field of science and technology finance / digital medical treatment, and discloses a high-guarantee link automatic guarantee method and device, electronic equipment and a storage medium. The method comprises the following steps: performing series recording on a calling link of a service interface of a first micro-service through a proxy probe to obtain service interface calling link data; rendering a screening result of the calling link data as a high-guarantee link panorama; analyzing the high-guarantee link panorama to obtain a high-guarantee link dependency relationship, and calculating a micro-service dependency score of the first micro-service; screening the first micro-service according to the micro-service dependency score to obtain a second micro-service; when the service interface of the second micro-service generates an alarm, automatically collecting alarm associated data; and inputting alarm data to the high-insurance decision large model for analysis, and automatically issuing and executing an alarm self-healing strategy output by the high-insurance decision large model through the model context protocol server. According to the method, high-guarantee link automation and system stability are improved.

The invention relates to the technical field of cluster video stream processing, and discloses a video stream real-time coding and decoding transmission method under a cluster. The method comprises the following steps: firstly, acquiring video stream coding parameter text data, link state time sequence data and equipment performance index data of multiple nodes of a target cluster to form a transmission link data set; semantic analysis is carried out on the coding parameter text data to obtain a coding semantic feature vector, dynamic fluctuation features are extracted from the link state time sequence data to obtain a link fluctuation feature vector, and cross-modal fusion is carried out to generate a fusion transmission feature set; generating an abnormal association degree score set by using a pre-trained multi-layer sensing network model, and obtaining an abnormal source node and an equipment defect type by combining root cause tracing according to the abnormal association degree score set; and finally, generating a dynamic optimization strategy and feeding back to the transmission control system to trigger parameter calibration. According to the method, the abnormal root cause can be accurately traced, the transmission parameters are optimized, and the cluster video stream transmission quality is improved.

The invention relates to the technical field of power distribution communication networks, and discloses a power distribution communication network fault path tracing method and system based on a knowledge graph, and the method comprises the steps: obtaining the dependency strength of a corresponding communication link according to the communication data of each communication link in the knowledge graph; identifying a fault propagation path in the directed edge set on the basis of a fault propagation rate obtained by calculation of the dependency strength; screening the fault propagation path diagram based on a preset fault propagation termination condition to obtain a first fault propagation path sub-diagram, and determining the degree of each level of node in the first fault propagation path sub-diagram; identifying key nodes in the first fault propagation path subgraph according to the first node importance; and expanding the first fault propagation path sub-graph based on the outgoing side link data to obtain a second fault propagation path sub-graph. According to the invention, key fault nodes and propagation paths can be quickly positioned.

The invention relates to a food traceability method based on a block chain, and the method comprises the steps: collecting production data, generating a unique data major key and an identifier, encrypting and uploading the data, and binding the data with a food batch; associating production link data, collecting processing data, performing secondary hash to generate a processing link data link, and binding a food unit after the processing link data link is linked; identifying a processing link identifier, collecting transportation data, carrying out chain association and timestamp progressive encryption and then carrying out uplink, generating a transportation link identifier and recording handover information; after full-link data are verified, sales data are collected, a full-link Merkel tree is formed through closed-loop association, a sales link identifier is generated after uplink encryption, and multi-node confirmation is triggered; a permission verification request is initiated through a query terminal, and after block chain type verification and local hash verification are carried out, a complete traceability link containing handover nodes, persons in charge and equipment information is displayed according to a time axis. According to the invention, full-life-cycle traceability of food is realized.

The invention discloses a lithium battery full life cycle quality tracing system based on digital twinning, and relates to the technical field of lithium battery quality tracing, and the system comprises a physical entity layer which integrates multiple types of sensors and detection equipment to collect full-link data; the digital twinning modeling layer is used for constructing a multi-scale model to map a battery state; the data acquisition and transmission layer is used for realizing data real-time transmission preprocessing through an edge gateway and an encryption protocol; the data storage and management layer is used for establishing a data warehouse by using a distributed database and performing backup; the intelligent analysis and decision-making layer integrates an algorithm to realize anomaly detection, performance prediction and tracing; the visualization and interaction layer is used for providing a multi-terminal visualization and interaction function; and the block chain evidence storage layer constructs an alliance chain to ensure that the data cannot be tampered. According to the invention, full-life-cycle data connection and credible tracing of the lithium battery are realized, the quality problem positioning efficiency is improved, intelligent early warning and optimization capabilities are provided, the operation threshold is reduced, and industrial quality control and green development are facilitated.

The invention relates to the technical field of ultra-far offshore data transmission, and discloses an ultra-far offshore distance real-time data stable transmission method and system. The method comprises the following steps: acquiring target transmission link data, and extracting dynamic fluctuation characteristics containing signal strength distribution information and a delay jitter relationship from the target transmission link data; calling the trained channel estimation network to carry out signal positioning processing on transmission link data, and generating a signal transmission path set containing a channel type identifier and phase code mapping relation; based on the set, calling a waveform analysis network to perform multi-modal feature fusion on the signal intensity distribution information to obtain a fusion result containing time-frequency domain features and modulation mode features; and inputting a fusion result into a transmission strategy model to perform dynamic path selection, and outputting a real-time data transmission element containing a control instruction generated based on a signal transmission sequence and a phase self-calibration parameter. According to the method, stable transmission of real-time data under the ultra-far offshore distance can be realized.

A tallying data processing method and system for an intelligent port, a medium and a product relate to the field of electric digital data processing, and the method comprises the following steps: obtaining a ship loading and unloading plan, tallying operation records and cost accounting data according to a preset period, and generating standard tallying data; extracting feature data in a pre-time window from the standard tallying data; inputting the feature data into a prediction calculation model, and generating a plurality of groups of loading and unloading plan change prediction scenes according to a historical operation mode; performing parallel calculation on the multiple groups of prediction scenes to obtain scene prediction data; comparing the real-time tallying data acquired at the port site with the scene prediction data, and calculating to obtain a data goodness of fit; selecting the most matched prediction scene as a current execution scene based on the data goodness of fit, and storing other prediction scenes into a standby scene library; and generating a tallying operation instruction and expense settlement data according to the current execution scene. By implementing the application, the efficiency of port multi-link data processing can be improved.

The invention discloses an agricultural product supply chain abnormal event tracing method and system based on a knowledge graph, and relates to the technical field of agricultural product supply chain management, and the method comprises the steps: constructing a supply chain knowledge graph, and enabling graph nodes to cover agricultural product batches, production subjects, processing equipment, transport vehicles, storage warehouses and other entities; when an anomaly is detected, performing reverse traversal from an abnormal node based on a graph neural network to determine a candidate propagation path; calculating an abnormal source probability score by integrating the historical abnormal record, the time window goodness of fit and the association strength, and outputting a responsibility subject sequence; the method supports hypothetical reasoning to predict the downstream influence range, and solves the problems that a traditional traceability scheme is difficult to efficiently associate and analyze cross-link data and lacks abnormal path intelligent reasoning ability.

The invention relates to a method and system for encrypting and isolating storage data of a credential mobile terminal, and belongs to the technical field of information. The method comprises the following steps: encrypting and partitioning the whole storage area, and setting an access strategy according to user permission; when a user requests to access, executing multi-factor authentication containing a password and an external hardware certificate, and adding biological characteristic authentication; after the authentication is passed, an encryption key is taken from the domestic security chip; and encrypting and decrypting data by using the secret key, and opening corresponding partition access according to authority. The system comprises a storage partition module, an identity authentication module, a key management module, an encryption and decryption module and an authority control module and is used for executing the method. The method also comprises the steps of equipment startup trusted boot and firmware upgrade verification, is based on a custom curing system, and is compatible with Android 10 +. The problems of poor hardware controllability and positioning security risk of the creative mobile terminal are solved, and full-link data security protection is realized.

The invention relates to the technical field of ship unloader linkage, in particular to a port ship unloader full-automatic multi-machine linkage system and a method thereof.The port ship unloader full-automatic multi-machine linkage system comprises a distributed intelligent scheduling module, the distributed intelligent scheduling module is in coupling connection with a full-link data middle station, and the full-link data middle station is in coupling connection with a self-adaptive edge computer unit; the self-adaptive edge computer unit is in coupling connection with a three-dimensional perception safety monitoring network, the three-dimensional perception safety monitoring network is in coupling connection with a man-machine collaborative interaction platform, and the man-machine collaborative interaction platform is in coupling connection with a production management module. The port ship unloader full-automatic multi-machine linkage system and the method thereof solve the problems that in the prior art, a ship unloader full-automatic multi-machine linkage system is mostly controlled in a centralized mode in the actual using process, depends on a fixed algorithm and is difficult to dynamically deal with complex operation scenes (such as ship position deviation and uneven cargo distribution), and the working efficiency is high. And equipment conflict or idle waiting is caused.

The invention relates to the field of data processing, and provides an intelligent prediction recommendation method and system based on full-link data of a supply chain. The method comprises the steps of collecting multi-source heterogeneous supply chain data and performing standardization processing to obtain a standardized data set; according to the standardized data set, performing quantitative modeling on the supply chain state features to obtain a supply chain state feature vector; on the basis of the supply chain state feature vector, performing supply chain entity relationship modeling through a heterogeneous graph neural network to obtain a graph embedding vector; according to the graph embedding vector, performing dynamic generation on a candidate set through a multi-objective optimization algorithm to obtain a dynamic candidate set; and performing personalized matching of user requirements based on the dynamic candidate set to obtain a recommendation result. According to the invention, intelligent recommendation of the supply chain is realized, the decision-making efficiency is improved, and the operation cost is reduced.

The invention discloses a multi-link fusion service adaptive dynamic selection method based on link state prediction. The method comprises the following steps: acquiring link data of a multi-source heterogeneous communication link through a distributed probe; inputting the link data into a multi-factor arbitration engine to obtain a link discrimination result; wherein the multi-factor arbitration engine comprises a factor weight interlayer and a prediction model module; the factor weight interlayer is used for calculating a link score of a corresponding link when the multi-source heterogeneous communication link is in a stationary state; the prediction model module is used for outputting a quality prediction result of the multi-source heterogeneous communication link when the multi-source heterogeneous communication link is in a fluctuation state; the link discrimination result is obtained according to a link score or a quality prediction result; and selecting a communication link for transmission according to the link discrimination result. The method has better compatibility, ensures instant acquisition and analysis of link state data, reduces information lag, and is more fit for service transmission characteristics, and the quality prediction result can reserve sufficient time for switching links.

The invention discloses an order logistics timeliness management system, and relates to the technical field of logistics intelligence, and the system comprises a risk prediction module which collects order logistics full-link data, carries out the preprocessing of the data, calculates the logistics node delay risk probability through a virtual intervention scene and a causal graph model, and obtains a delay risk prediction result; the visualization module is used for performing overlay analysis on the delay risk prediction result and the preprocessed order logistics full-link data to generate a delay risk thermodynamic diagram; the destroy-resistant module is used for carrying out vulnerability evaluation on the delay risk thermodynamic diagram to generate a vulnerability analysis report, and carrying out multi-objective optimization evaluation through a k-shortest path algorithm to generate a destroy-resistant strategy table; the scheduling module is used for carrying out transport capacity resource matching and scheduling scheme selection by utilizing a multi-target resource optimization model based on the survivability strategy table to obtain a scheduling instruction set; according to the invention, causal traceability and probability quantification of logistics delay risks are realized by constructing a collaborative prediction mechanism of a virtual intervention scene and a causal graph model.

The invention provides a low-orbit navigation constellation autonomous orbit determination method and system under a weak inter-satellite topological structure, and relates to the technical field of satellite orbit determination, and the method comprises the steps: obtaining various observation data of an inter-satellite link on a predetermined orbit, and carrying out the preprocessing of the various observation data; establishing a synchronous observation equation of orbit and clock correction parameters by adopting a segmented linear polynomial satellite clock correction modeling method, generating orbit, clock correction and related error parameters combining satellite-borne GNSS and inter-satellite link data, and forecasting; based on an error analysis result, multiple key features are extracted from the generated orbit, clock error and related error parameters to serve as input of a parameter prediction model, and a parameter time sequence of four types of prediction including relative weight, inter-satellite link hardware delay, low-orbit satellite clock error and unmodeled error is obtained through output; and uploading the predicted parameter time sequence and the broadcast ephemeris to a main satellite together, and transmitting to each sub-satellite by the main satellite through an inter-satellite link to realize distributed autonomous orbit determination of the sub-satellites.

The invention belongs to the technical field of information, and particularly relates to a material set state early warning model based on spatio-temporal characteristics and an attention mechanism, and the model comprises a multi-source data collection and preprocessing module which is used for integrating plan-inventory-supply chain-transportation-production full-link data; the Transform prediction module is responsible for outputting a prediction result; the dynamic optimization module is used for dynamically adjusting parameters such as an early warning threshold value, a time window length and a feature weight through a reinforcement learning mechanism, and forming a'prediction-optimization-re-prediction 'closed-loop feedback mechanism; and the grading early warning output module is used for generating grading early warning grades according to the prediction result and the optimization parameters. According to the model, dynamic early warning of the complete set of states of complex product materials is achieved by accurately capturing the spatial and temporal change rule of the material states, the problems of evaluation lag, data island and static model stiffness of a traditional method are solved, and the prediction accuracy and timeliness are remarkably improved.

The invention discloses a new energy automobile battery health state monitoring system and an implementation method, and relates to the field of new energy automobile intelligent monitoring. According to the system, in order to solve the problems that new energy automobile battery health state monitoring precision is insufficient, abnormal response lags behind and multi-dimensional data fusion efficiency is low, full-type battery compatibility and multi-physical-quantity accurate sensing are achieved through a battery data acquisition module; the data processing and analysis module is used for completing multi-modal data feature decoupling and depth modeling; by means of a battery state monitoring module, a display and interaction module and a communication module, millisecond-level abnormity early warning, health state visualization and full-link data intercommunication are realized; and finally, under a complex working condition, the intelligence and precision level of new energy automobile battery health state monitoring is remarkably improved.

The invention discloses a multi-platform-based advertisement creativity and putting strategy intelligent generation system, equipment and medium, multi-source data are integrated through a cross-platform creativity intelligent generation module to generate creativity materials adaptive to different platforms, and a cross-platform collaborative strategy optimization module is used for quantifying a platform collaborative effect and dynamically allocating budget. An advertisement creative life cycle is managed by means of a real-time dynamic optimization module, a strategy is adjusted based on multi-dimensional feedback, and finally, output of each module is fused through a unified decision engine to form a unified decision. The system realizes full-process intelligentization of advertisement originality and putting strategies, quantifies a cross-platform synergistic effect to improve budget distribution efficiency, constructs an advertisement originality life cycle dynamic management mechanism, realizes strategy real-time evolution through multi-dimensional feedback, and visualizes full-link data in combination with a unified decision engine, so that the advertisement putting return on investment is remarkably improved, and the advertisement putting efficiency is improved. The creative manufacturing cost is reduced, the strategy adjustment efficiency is improved, and an efficient and accurate multi-platform putting solution is provided for advertisers.

The invention relates to the technical field of group meal food traceability, and particularly provides a group meal food whole-course traceability method and system, and the method comprises the steps: carrying out the traversing of a pre-constructed traceability map according to a food traceability request when the food traceability request is received; based on a first preset evaluation dimension, performing confidence evaluation on each candidate traceability chain path to obtain a plurality of first confidence evaluation results, and screening out a target traceability chain path from all the candidate traceability chain paths according to all the first confidence evaluation results; analyzing whether the target traceability chain path is broken, if yes, repairing the target traceability chain path according to the auxiliary information set and outputting the repaired target traceability chain path, and if not, directly outputting the target traceability chain path; according to the method, the problem that the generated tracing chain is incomplete or inaccurate due to data missing or cross-link data association errors existing in the acquired tracing data can be effectively solved.

The invention provides a cable quality inspection tool management interaction method, system and device and a medium, and relates to the technical field of intelligent quality inspection. According to the method, batch number input, tool recommendation, AR guidance and traceability report generation controls are integrated through a main interface; specifically, after batch numbers are input, a cable quality inspection database is automatically associated, an optimal tool combination is dynamically recommended based on a multi-source data fusion algorithm, and precise positioning and taking are achieved through intelligent tool rack linkage. In the aspect of AR guidance, an adaptive teaching video and an operation layer are pushed in combination with a context awareness engine, and a user is guided to operate normatively in real time; and integrating full-link data to generate a traceability report of a unique associated batch, wherein the traceability report covers tool use records, parameter configuration and quality inspection conclusions. According to the invention, cable quality inspection whole-process closed-loop management is realized, the detection efficiency and precision are effectively improved, and the operation verifiability and the quality inspection traceability are ensured at the same time.

The invention provides an intelligent solitary policy processing method based on a neural network and machine learning, and relates to the field of data processing. According to the method, strategy byte codes and execution contexts are generated by extracting business rules, supervision calibers and field dependency relationships of the single insurance policy, discovery, repair and arbitration of field abnormity are achieved in combination with a dynamic data governance model, an account-falling confirmation receipt is output through a voting game and a compensation transaction, and a replayable trace and a rare mode index are generated. And a high-confidence label and an error correction prior increment are obtained in combination with triggering verification, and finally, full-link evidence is solidified through continuous distillation, chain type evidence storage and an auditable snapshot library, so that a traceable record of the single insurance policy is formed. By implementing the technical scheme provided by the invention, full-link data processing can be conveniently carried out on the single insurance policy, so that the processing efficiency is effectively improved.

The invention relates to the field of co-extrusion production control, and particularly discloses an efficient film bag feeding control system, which is applied to a multi-raw-material synchronous conveying device of a co-extrusion process, and comprises a full-link data acquisition module, a full-link data processing module and a full-link data processing module, the raw material characteristic parameters comprise a melting point T, a stacking density rho and a magnetic sensitive particle loading amount M; the instantaneous load pressure P of each raw material conveying channel, the temperature Tm of a co-extrusion die head melting area, the real-time thickness H of a co-extrusion film layer, stock bin liquid level data and motor rotating speed data are collected and integrated to obtain a full-link original data set; the single-drive linkage conveying mechanism comprises a main servo motor, a plurality of sets of electromagnetic clutches and a plurality of sets of spiral conveying assemblies, and the main servo motor drives a transmission shaft through a synchronous belt. According to the technical scheme, for the co-extrusion process, the multi-raw-material synchronous conveying precision can be matched, and the problems that parameter adjustment lags behind, adaptability is poor and a downstream process feedback closed loop is lacked are solved.

The invention provides a flow control method based on a software-defined network, which belongs to the technical field of data processing, and comprises the following steps of: 1, acquiring port data and link data of a switch in the software-defined network, and determining a network topology structure; 2, acquiring real-time flow data in the software defined network, and analyzing a network topology structure and the real-time flow data to determine adjustment path data; 3, determining a traffic adjustment strategy and a traffic forwarding rule based on the network topology structure and the adjustment path data; and step 4, executing the flow forwarding rule to realize the flow control of the software defined network. The method can deal with sudden flow fluctuation and link faults in the network and quickly respond, automatically optimize flow distribution and route selection, improve the bandwidth utilization rate and resource utilization rate of the network, reduce congestion and delay, adapt to a complex flow mode and a high-load and time-varying network environment, and improve the flexibility, reliability and efficiency of the network.

The invention relates to a configuration parameter optimization method and device based on a micro-service architecture, computer equipment, a readable storage medium and a program product. The method comprises the steps of obtaining calling link data of a to-be-optimized micro-service application in a micro-service architecture, determining a key path based on the calling link data, determining a key service which has the greatest influence on the overall performance from the key path, and further optimizing the overall performance of the to-be-optimized micro-service application through a Bayesian optimization algorithm. The multiple configuration parameters of the key service in the to-be-optimized micro-service application are subjected to collaborative optimization to determine the target values of the multiple configuration parameters, so that the multiple configuration parameters in the micro-service architecture are automatically adjusted, manual intervention is reduced, the optimization efficiency is improved, and the optimization efficiency is improved through the multi-parameter collaborative optimization mode. The optimal configuration can be found among multiple parameters, so that the overall performance is improved.

The invention discloses a carbon emission abnormity traceability method and device, a medium and equipment, and belongs to the field of carbon emission, and the method comprises the steps: receiving a traceability request containing a to-be-verified data identifier, positioning target link data from a block chain storage, and executing signature verification and Hash consistency verification, thereby guaranteeing the authenticity and consistency of the data. And if the verification of the target link data is passed, verifying the inclusion relation of Merkle tree root hash of each link upwards layer by layer to confirm the integrity of the full-chain data. And if verification failure of any level is found, the feature data of the level is combined with an anomaly detection model based on an isolated forest algorithm, and an abnormal data node is positioned. And then, according to the signature information of the abnormal data node and the preset tracking secret key, a group signature verification and private key derivation process is applied, the responsibility participant is traced, and the tracing process of the carbon emission abnormity is completed, so that the problem that the carbon emission abnormal point cannot be accurately and efficiently traced in the prior art is effectively solved.

The invention discloses a cascade power station connectivity fish monitoring method and system, and the method comprises the steps: collecting the water flow speed, water temperature, dissolved oxygen and other hydrological parameters of a water area cross section, the fish activity frequency data, the gate dam opening and closing state, and the pump set operation parameters through a sensing assembly; dividing a potential migration area; abstracting a water area node as a graph theory vertex, abstracting a connected state as an edge weight, and constructing a model to calculate node connectivity; according to the pump set parameters and connectivity indexes, calculating water area node connectivity probabilities under different pump set operation conditions; the number, body type distribution and motion trail of fishes are obtained through an image and acoustic module and are associated and matched with a migration area and a connectivity probability; and integrating multi-link data to generate a connectivity and fish activity relevance monitoring result. Functional units are arranged in all links of the corresponding method of the system, all the units operate cooperatively, cascade power station water area connectivity and fish activity association monitoring precision are improved, and data support is provided for drainage basin ecological protection.

The invention relates to the technical field of data display, can be applied to business system platforms of financial science and technology, medical health and the like, and discloses a link monitoring large screen display method, device, equipment and medium, the method comprises the following steps: obtaining a plurality of visual components, performing component configuration on the plurality of visual components, and obtaining an initial configuration component library; obtaining component attributes of the initial configuration component library, and performing incremental updating on the component attributes to obtain component change attributes; obtaining an incremental component according to the component change attribute, performing component updating on the initial configuration component library by using the incremental component to obtain a target visual component library, and constructing a link monitoring large screen according to the target visual component library; obtaining link topology data, and performing link topology rendering on the link topology data to obtain target link data; and performing visual display on the target link data on the link monitoring large screen to obtain a data display result. According to the invention, high configurability and modularization of the link monitoring large screen can be realized.

The invention relates to an advanced early warning method, device and equipment for sensitive data leakage, and relates to the technical field of data secrecy, and the method, device and equipment consider a full-link data blood relationship and an upstream and downstream relationship through pre-constructing a sensitivity identification model; according to the method, from original data, when it is judged that a user queries sensitive data, interception judgment is carried out, so that the sensitivity level of to-be-queried content is recognized through a pre-constructed sensitivity recognition model, and when the user permission level is sensitive, a secret divulging strategy is executed, so that sensitive data divulging is avoided.

The invention provides a cloud-edge collaborative enterprise knowledge graph automatic construction method and system, electronic equipment and a storage medium, and relates to the technical field of computer and knowledge graph construction. Link data and inter-service communication monitoring data are called by collecting interface endpoints, and data are fused and associated by edge nodes; a dependency graph containing the service calling relation is generated; analyzing the time delay contribution degree and the error propagation probability, positioning a performance bottleneck link, measuring and calculating a service state in combination with a historical mode, adjusting flow distribution and isolating substandard instances; meanwhile, a multi-entity enterprise knowledge graph is constructed on the cloud based on dependency graph topology, performance attributes of service instances and interface endpoints and dependency relationship attributes among services are associated, and graph updating is automatically triggered when the attributes change. And finally, adaptive management strategies and configuration suggestions are generated through graph analysis, and automatic construction and application support of the enterprise knowledge graph can be realized.

A heterogeneous multi-hop wireless network is provided. The network consists of single-link data nodes, multi-link data nodes and data centers. The single-link data node supports one communication interface, the multi-link data node supports two communication interfaces and the data center is considered as multi-link node. The routes from all data nodes to data centers are given. The network is configured to schedule data transmissions from all data nodes to data centers without transmission interference and channel access delay. The routing link scheduling problem is formulated as an optimization problem with constraints. Due to the NP-Hard complexity of the formulated optimization problem, the scheduling policies are then parameterized for the application of graph neural network techniques. The parameterized optimization problem is solved using primal-dual approach with zero duality gap. A heterogeneous graph neural network (HetGNN) algorithm is provided to train the primal-dual problems.