695 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 intelligent building management, in particular to an intelligent building operation and maintenance management system and method based on a BIM platform. The method comprises the following steps: performing equipment connection topology network construction according to acquired target BIM building model data, and generating equipment physical connection topology data; performing automatic logic conflict elimination on the equipment physical connection topological data to generate equipment connection topological data; performing fault influence link analysis on the equipment connection topological data to generate fault propagation link data; performing fault severity evaluation on the fault propagation link data to generate equipment fault severity data; and performing intelligent operation and maintenance path planning according to the equipment fault severity data to obtain intelligent equipment operation and maintenance path data. Through fine division of the operation and maintenance equipment management space and analysis of the equipment fault propagation link, intelligent scheduling of the fault operation and maintenance task is realized, and the operation and maintenance efficiency and the resource allocation precision are remarkably improved.

Embodiments of the present description provide a root cause location method, system and device. The root cause locating method comprises: acquiring historical link data corresponding to a microservice, and determining a target anomaly location model corresponding to the historical link data; determining link data sets to be processed corresponding to the microservice, clustering said link data sets, and determining cluster center link data on the basis of a clustering result; inputting the cluster center link data into the target anomaly location model to obtain abnormal link node information corresponding to the cluster center link data; and on the basis of the abnormal link node information, determining a target abnormal link corresponding to the microservice, and determining an abnormal link node in the target abnormal link. Model fine adjustment is carried out on the basis of an initial anomaly location model, so that the initial anomaly location model has wide applicability and high generalization ability. Cluster center link data is selected for root cause location, so that the root cause location speed of the microservice is increased.

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 discloses a software application performance optimization method based on big data analysis, and relates to the technical field of data analysis and mining, and the method comprises the following steps: tracking software application service call link data through a distributed tracking technology, collecting log data during software application operation through a log aggregation system, and monitoring the performance of software application through a performance monitoring tool. The method comprises the steps of collecting performance index data of a software application program, establishing a Prophet time sequence prediction model, predicting the performance trend of the software application, monitoring the performance data of the software application through an isolated forest algorithm, implementing real-time anomaly detection, and presenting an analysis result to a software application user through a visual tool. By means of the big data analysis technology, accurate prediction and real-time monitoring of software application performance are achieved, the efficiency and accuracy of performance optimization are effectively improved, meanwhile, the analysis result is visually presented, a user can visually understand the software performance condition, and stable operation and optimization upgrading of software application are promoted.

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.

A method is provided. The method includes receiving, from a base station, information associated with simultaneous physical uplink control channel (PUCCH) and physical uplink shared channel (PUSCH) transmission, identifying that a PUCCH with a first priority index and a PUSCH with a second priority index overlap in a time domain, and in case that the first priority index is different from the second priority index, transmitting, to the base station, uplink control information (UCI) via the PUCCH and uplink data via the PUSCH, based on the information associated with the simultaneous PUCCH and PUSCH transmission.

Some embodiments of this disclosure include apparatuses and methods for facilitating a transmission, retransmission, and hybrid automatic repeat request (HARQ) process using preconfigured uplink resources (PUR) in IDLE mode. In some embodiments, user equipment (UE) may establish a first PUR and a second PUR to use in IDLE mode. The UE may transmit uplink data using the first PUR using a HARQ process. The UE may start a PUR retransmission timer and monitor a control channel for an acknowledgement message. The UE may identify an expiration of the PUR retransmission timer prior to receiving the acknowledgement message, and in response, may retransmit the uplink data using the second PUR.

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 embodiment of the invention provides a root cause positioning method, system and device, and the method comprises the steps: obtaining historical link data corresponding to a micro-service business, and determining a target abnormity positioning model corresponding to the historical link data; determining a to-be-processed link data set corresponding to the micro-service business, clustering the to-be-processed link data set, and determining clustering center link data according to a clustering result; inputting the clustering center link data into a target abnormity positioning model to obtain abnormal link node information corresponding to the clustering center link data; and determining a target abnormal link corresponding to the micro-service based on the abnormal link node information, and determining an abnormal link node in the target abnormal link. Model fine tuning is carried out on the basis of the initial anomaly positioning model, so that the initial anomaly positioning model has relatively wide applicability and relatively strong generalization ability; and cluster center link data is selected to carry out root cause positioning, so that the root cause positioning speed of the micro-service business is improved.

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 discloses a multi-agent collaborative compatibility method based on a Copula thought, which is a multi-agent collaborative method based on full-link data driving, integrating priori knowledge, expert knowledge and mechanism knowledge, integrating a Copula function and tracking a target value. The method comprises the following steps: S1, establishing a multi-agent collaborative system; s2, the pre-combustion mixing agent, the combustion agent and the component detection agent respectively reinforce learning action decisions based on the Markov process; s3, putting a plurality of intelligent agents together to learn a copula-based strategy; and S4, through information interaction between the pre-combustion mixing intelligent agent and the combustion intelligent agent and between the combustion intelligent agent and the component detection intelligent agent, enabling the pre-combustion mixing intelligent agent to understand the hysteresis quality, the combustion condition and the detection condition, and making a compatibility decision. According to the invention, compatibility decision is carried out on the basis of the relationship between the agents of Copula, the traditional manual compatibility debugging method based on experience is broken through, the compatibility is controlled by adopting full-link data driving, and the compatibility effect is finer and more obvious.

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.

In some examples, a battery management system (BMS) includes a set of battery cells and a secondary network node coupled to the set of battery cells. The secondary network node is configured to, responsive to determination by the secondary network node of an exception event, wirelessly transmit a series of periodically repeating reverse wake up data frames to a primary network node. The secondary network node is also configured to, responsive to receipt of a synchronization frame from the primary network node after transmitting the series of reverse wake up data frames, transmit an uplink data frame to the primary network node.

The invention provides a link tracking method and system for a service cluster based on log burying points, and belongs to the technical field of distributed monitoring. According to the method, a link tracking ID is generated through a snowflake algorithm at a starting point of service calling, and service IDs are distributed to micro-service nodes participating in service calling; setting log burying points at the entrance, the exit and the key logic processing points of each service according to preset burying point logic; asynchronously recording link tracking information contained in the service node through the log burying point, and uploading the information to a storage system for storage; according to the link tracking ID and the service ID in the link tracking information, the link tracking information is connected in series, a complete calling link called by the service is restored, and meanwhile a service calling topological graph is generated. According to the method, real link information can be quickly and accurately tracked, and quick retrieval and analysis of a large amount of real-time link data can be supported.

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.

A multi-link data transmission method includes the following operations: transmitting a first data to an electronic device via a first link; transmitting a second data to the electronic device via a second link, wherein the first data and the second data have the same content; and receiving a first response corresponding to the first data from the electronic device via the first link, and stopping transmitting the second data according to the first response.