2055 results about "Network configuration" patented technology

The invention discloses a building crack early prediction and restoration method based on a machine learning algorithm, and the method comprises the following steps: collecting stress, displacement, temperature and image data through a self-adaptive sensor network, and enabling a sensor to dynamically adjust the collection frequency and position; preprocessing the collected multi-source data, including de-noising, data completion and image enhancement, and extracting crack features; performing cross-scale multi-dimensional feature extraction based on the preprocessed data, and generating high-dimensional features for crack prediction; inputting the high-dimensional features into a fusion quantum Bose-Einstein condensation model and a long-short term memory network model, and performing dynamic space-time prediction of the crack; according to the prediction result, generating a repair suggestion by using an intelligent optimization algorithm; after the repair plan is implemented, the repair effect is continuously monitored through the sensor network; the sensor network configuration is adjusted in real time, and the monitoring and prediction accuracy is improved. According to the invention, early prediction and effective repair of the building crack are realized.

Systems and methods for synchronizing data structures in computer networks and distributed computing environments are disclosed. A system can provide a network resource to a client device corresponding to a network profile, establish a network communication session with the client device, and transmit instructions for network application formatting during the network communication session. The system can receive a second request for a network exchange during the network communication session. The system can determine that a path for an object of the network communication session satisfies at least one intersection criterion, the at least one intersection criterion associated with at least one second transmission value. The system can update a second data structure of the network profile.

A system and method, the method including determining, by a centralized user configuration function based on a core network packet delay budget (CN PDB) and a buffer duration, an allowed maximum latency of a time-sensitive network (TSN) stream transmitted between an access network device and a user plane network element, wherein the maximum latency does not exceed a difference obtained by subtracting the buffer duration from the CN PDB, sending, by the centralized user configuration function, first latency information to a centralized network configuration function, wherein the first latency information indicates the maximum latency, receiving, by the centralized user configuration function, first configuration information, wherein the first configuration information indicates a packet transmission time of the transmit end of the TSN stream, and the packet transmission time is associated with the maximum latency, and sending the first configuration information to the transmit end of the TSN stream.

Systems and methods are described for dynamic execution of artificial intelligence (“AI”) agents. A server can receive, from a client device, an input associated with an AI agent. Based on a manifest file or user profile, the server can identify a management policy that applies to the AI agent. The server then dynamically configures access to the agent objects based on applying the management policy. The management policy is applied to a device status of the client device, a user profile of a user of the client device, and / or a network configuration of the client device. The server then executes a modified workflow based on the dynamically configured access, wherein the modified workflow bypasses or changes operation of at least one of the agent objects. Based on the modified workflow, the server transmits an output to the client device.

The invention discloses an information physical security defense method, system and device based on a distribution network digital twin simulation platform and a medium, and belongs to the technical field of information security and control defense of the power distribution Internet of Things, and the method comprises the steps: constructing a three-dimensional channel for interaction of a physical power grid, an information model and simulation data; on the basis of a three-dimensional channel, a three-state dynamic conversion model among a steady state, a transient state and a recovery state is constructed, and multi-state automatic switching simulation is achieved through sub-region division and parallel computing; a multi-level risk modeling system oriented to various risks is constructed based on simulation results, complex attack scenes are identified, and mapping of risk types and response paths is achieved; security risk assessment and defense strategy generation verification are completed, and intelligent collaboration and continuous learning of cross-domain defense strategies are achieved through collaborative optimization. According to the method, the construction efficiency of a complex risk scene is improved, quantitative analysis of cross-domain risks such as circuit breaker mis-tripping caused by network attacks is realized, and the limitation of traditional single-domain risk analysis is broken through.

The embodiment of the invention provides a network fault diagnosis method, a network fault diagnosis system, electronic equipment and a computer readable storage medium, and the method comprises the steps: obtaining multi-dimensional data of network equipment, the multi-dimensional data comprises equipment configuration information, network topology information, performance index data and historical fault records; constructing a knowledge graph according to the multi-dimensional data, wherein the knowledge graph comprises nodes representing the network equipment, equipment links, network events and equipment configuration items, and edges representing a physical connection relationship, a logic dependency relationship, an equipment dependency relationship, network configuration information and a causal relationship among the nodes; performing map reasoning based on the knowledge map to obtain a map reasoning result; and generating diagnosis information for a target fault according to the map reasoning result. According to the embodiment of the invention, through multi-dimensional data integration, knowledge graph construction and automatic reasoning, the diagnosis efficiency, accuracy and adaptability are remarkably improved.

The invention provides a distributed formation control method driven by a recursive balance network under a communication attack, and relates to the technical field of cooperative control of a multi-agent system, and the method comprises the steps: constructing a distributed multi-agent system model, and constructing an RBN controller heterogeneous communication network architecture and a DoS attack model; the RBN controller design is optimized, the distributed RBN controller architecture is realized, the stability of the RBN controller is analyzed based on the shrinkage mapping theory, and the exponential convergence of the system state difference is proved by constructing a Lyapunov function; training the optimized RBN controller by adopting a difficulty priority confrontation training strategy, designing a multi-objective loss function, and dynamically adjusting the training weight of each difficulty level; and simulating the distributed multi-agent system optimized by the above steps, testing the robustness of the distributed multi-agent system under incremental DoS attack intensity, and performing comparative analysis of heterogeneous and isomorphic communication network configuration and comprehensive performance comparison of an RBN controller and a traditional MPC method.

A method and apparatus for determining optimized network configuration includes receiving, at a performance analysis server (PAS), a plurality of performance parameters for each of the plurality of nodes, and a plurality of network parameters. The method includes generating, using an artificial intelligence and / or machine learning (AI) engine, based on the plurality of performance parameters, a network status for the plurality of nodes. The network status includes a performance state determined based on the performance parameters, a network state determined based on the network parameters, and at least one performance parameter or at least network parameter causing the performance state or the network state respectively. The method includes determining a configuration change based on performance parameters or the network parameters.

The invention relates to a TSN network configuration automatic generation method and system based on an anti-Agent. The system is composed of a network state perception and intention reflection module, a YANG model configuration parameter and structure decision module and a YANG model intelligent generation module. The network state sensing and intention reflecting module is responsible for structurally sensing the network state and resource information, the YANG model configuration parameter and structure decision module fuses multi-source knowledge and context information, intelligently generates deployable TSN scheduling parameters and a YANG configuration structure for service requirements, and sends the TSN scheduling parameters and the YANG configuration structure to the network state sensing and intention reflecting module. And the YANG model intelligent generation module automatically generates a corresponding YANG configuration model according to an optimized result, and issues the YANG configuration model to target equipment after completing grammar and semantic verification, so that automatic deployment of network configuration is realized. According to the method, the intellectualization level of TSN network configuration and the deployment automation capability are remarkably improved by introducing the reflection reasoning and feedback optimization technology.

Systems and methods are described for dynamic execution of artificial intelligence (“AI”) agents. A server can receive, from a client device, an input associated with an AI agent. Based on a manifest file or user profile, the server can identify a management policy that applies to the AI agent. The server then dynamically configures access to the agent objects based on applying the management policy. The management policy is applied to a device status of the client device, a user profile of a user of the client device, and / or a network configuration of the client device. The server then executes a modified workflow based on the dynamically configured access, wherein the modified workflow bypasses or changes operation of at least one of the agent objects. Based on the modified workflow, the server transmits an output to the client device.

In a system including a plurality of in-vehicle networks, information regarding the network configuration of function units connected to different types of transmission paths can be easily used. A relay device includes: an acquisition unit configured to acquire second function unit information of the function unit connected to the second transmission path, the second function unit information being function unit information that includes information regarding a network configuration of a layer of a lower order than an application layer; and a conversion unit configured to perform a conversion process of converting the second function unit information acquired by the acquisition unit into information that is able to be registered into a database of one or a plurality of pieces of first function unit information being function unit information of one or a plurality of the function units each connected to a corresponding first transmission path.

The invention relates to the technical field of computer hardware and network communication, in particular to a high-speed I / O (input / output) virtualization server based on an FPGA (field programmable gate array) and a remote forwarding method.The high-speed I / O virtualization server comprises an FPGA chip, a network processing unit, an I / O protocol processing unit, a protocol conversion and scheduling unit, a time sequence and transaction management unit and a data buffering and flow control unit are integrated in the FPGA chip; the optical fiber Ethernet interface module comprises a physical layer interface and an MAC layer processing and network configuration interface; the local I / O interface module comprises a USB interface circuit, a serial port interface circuit, a PCIe interface circuit and an interface expansion connector; the power supply and monitoring module comprises a multi-path power supply management system, a state monitoring and diagnosis system and an LED indication system; according to the self-adaptive Baud rate detection circuit, the Baud rate can be accurately locked under the condition that data with less than two characters is received, the number of data bits, the type of a check bit and the length of a stop bit are automatically identified, and compared with a traditional microcontroller scheme, the self-adaptive Baud rate detection circuit has higher precision and higher detection speed.

The invention provides a general electromechanical transient modeling method and system for a network-building converter, and relates to the technical field of electromechanical transient modeling, and the method comprises the steps: simplifying the electromagnetic transient models of network-building converters of different topologies into a grid-connected equivalent circuit of an electromechanical transient time scale; uniformly representing by using an internal potential series reactance model controlled by a power outer ring so as to establish an electromechanical transient general grid-connected interface model of the grid-forming converter; combining mathematical transformation of active power control with a reactive power control mode to form a general power outer loop control model of the network construction type converter; through a method based on internal potential reconstruction, reconstructing a new internal potential satisfying a current limiting constraint, and establishing a general current limiting model suitable for a network construction type electromechanical transient model; according to the method, various topological structures, various power outer loop control and various current limiting strategies can be simulated, flexible use of models in large-scale power system simulation is facilitated, and the complexity of model development and maintenance is reduced.

The invention relates to a method and device for configuring a Bluetooth Mesh network through Bluetooth broadcast. The method comprises the following steps: receiving Bluetooth distribution network broadcast information; according to a first matching result of the message label and the cache information, determining a processing state of the Bluetooth network distribution broadcast information by the equipment to be subjected to network distribution; if the first matching result shows that the broadcast information is not processed, determining a matching relationship between the to-be-distributed network equipment and the target to-be-distributed network equipment according to a second matching result of the target address information and the address information of the to-be-distributed network equipment; if the second matching result shows that the two are matched, accessing the to-be-distributed network equipment to the network based on the broadcast information; and if the second matching result shows that the two devices are not matched, updating the message forwarding mark to obtain the updated broadcast message and forwarding the updated broadcast message to the next device until the target device to be subjected to network configuration is obtained through matching within the dynamic message distance determined based on the message forwarding mark and is accessed to the network. By adopting the method, the network distribution efficiency can be improved, and the resource redundancy in the network distribution process can be reduced.

Aspects of the subject disclosure may include, for example, generating network configuration data for a network device according to device information of a vendor; providing the network configuration data to an Artificial Intelligence (AI) analysis platform that applies an AI model to the network configuration data based at least in part on topology data resulting in a configuration analysis, wherein the configuration analysis evaluates the network configuration data and generates at least one of rating information, adjustment information or a combination thereof. The rating information can include a security rating, a risk rating and / or an efficiency rating. The adjustment information can include a recommendation for changing at least a portion of the network configuration data for the network device.

The invention relates to the technical field of multi-sensor information fusion and intelligent manufacturing, and discloses a guide rail precision evaluation method and system based on multi-sensor fusion, and the method comprises the steps: constructing a multi-modal sensor value quantification model based on information entropy, calculating the contribution degree of sensor information and constructing a multi-sensor mutual information coupling model; constructing a self-optimization sensor network configuration system, abstracting a multi-modal sensor system into a graph structure, and generating optimal sensor combination configuration by applying a graph reinforcement learning algorithm; constructing a multi-time scale optimization framework and realizing adaptive data compression based on Huffman coding; constructing a dynamic Bayesian network model to fuse heterogeneous sensor data; constructing a self-evolution evaluation strategy system, and continuously improving an evaluation strategy through historical performance data; through information entropy-driven resource allocation, resources can be dynamically allocated according to the information value of the sensor.

An embodiment establishes a virtual representation of a network configuration, wherein the virtual representation of the network configuration comprises a plurality of layers corresponding to the network configuration. The embodiment generates a plurality of workloads to simulate with the virtual representation. The embodiment generates a plurality of workload statuses to simulate with the virtual representation. The embodiment simulates the plurality of workloads. The embodiment simulates the plurality of workloads statuses. The embodiment receives simulation results responsive to simulating the plurality of workloads and from simulating the plurality of workload statuses.

Methods and apparatus for biometric data maintenance, access and distribution across two or more experiential and / or network domains. In one embodiment, a 5G NR-based network architecture is provided which allows ultra-low latency and effectively user-imperceptible biometric data use for e.g., authentication and maintenance of user state across multiple domains via multiple constituent user devices (e.g., UEs). The network architecture includes both (i) a distributed biometric database (BDB) model wherein relevant biometric data for individuals / UEs is intelligently cached in various portions of the distributed database, and (ii) centralized and local BAEs (biometric analytics entities) which manage the aforementioned intelligent caching, as well as network configuration using one or both of 5G NR network “slicing” and CU / DU split options to optimize end-user biometric-related applications such as those providing identification / authentication, AR functions, VR functions or yet others.

The invention discloses a network architecture based on multi-core transmission, and relates to the field of integrated circuits. The network-on-chip module comprises at least one node ring consisting of M pipeline cascade routing nodes; adjacent routing nodes in adjacent node rings are cascaded according to a longitudinal depth pipeline to form a node matrix; n sending buffers and N receiving buffers are respectively arranged on the node ring on the outermost layer of the node matrix, and each sending buffer and each receiving buffer are respectively connected with the corresponding IP core through directly connected routing nodes; a routing algorithm based on a node matrix is built in the network configuration unit, a target IP core is determined according to data sent into the sending buffer by source IP core data, a node matrix is controlled to plan and generate a data transmission path, and data transmission is executed. The data buffer is added in the network-on-chip architecture, so that the data transmission path is shortened, the feedback is more timely, and the network bandwidth is larger; a routing node adds a data replication realization function to realize multicast and broadcast modes; and the interface complexity of the whole node matrix is reduced.

The invention discloses a customer demand analysis method based on AI artificial intelligence CRM system data, and the method comprises the following steps: S1, collecting multi-source heterogeneous customer data, executing the preprocessing, and carrying out the fusion; s2, customer behavior features are extracted and fused to form feature vector representation, feature importance evaluation is carried out, and high-correlation feature subsets are screened; s3, inputting the high-correlation feature subset into a swarm intelligence optimization module, and outputting initial network configuration parameters; s4, constructing and initializing a customer demand prediction model according to the initial network configuration parameters; s5, training the customer demand prediction model, and dynamically adjusting the structure of the customer demand prediction model; s6, continuing to iteratively train the customer demand prediction model; and S7, generating a customer demand prediction result. According to the method, intelligent swarm optimization and deep learning methods are fused, accurate prediction of customer demands is realized, and the method has the advantages of high adaptability, accurate prediction and fast response.

The invention relates to the technical field of monitoring and intelligent decision analysis, and discloses a monitoring and intelligent decision system for the influence of holographic blasting vibration on slope stability, and the system comprises a data collection module, a data processing module, an intelligent decision module, and a feedback control module. The method comprises the following steps: dynamically deploying a three-dimensional vibration sensor array based on topographic features; collecting and preprocessing blasting vibration signals and geological data; fusing the physical model and the data driving model to predict vibration propagation; calculating a dynamic safety coefficient and generating a multi-objective optimization scheme; and outputting an early warning instruction and feeding back and adjusting the sensor network configuration. Through a three-dimensional dynamic monitoring network, real-time data processing, a hybrid drive prediction model, multi-target quantitative evaluation and hierarchical early warning regulation and control, the problems of incomplete sensor coverage, early warning delay, prediction deviation, evaluation deficiency and poor scene adaptability are solved, and accurate monitoring and intelligent decision making of blasting vibration influence are realized.

The invention discloses an unmanned aerial vehicle distribution network construction quality monitoring and evaluation system. The system comprises at least two unmanned aerial vehicles, a path planning module, a data acquisition module, an interaction module and a quality evaluation module. The path planning module is used for planning flight paths of the at least two unmanned aerial vehicles to form a flight route, and controlling the at least two unmanned aerial vehicles to inspect a construction area according to the flight route; the data acquisition module is loaded on the unmanned aerial vehicle and is used for acquiring quality monitoring data of the construction area; the quality evaluation module is used for evaluating the construction quality according to the quality monitoring data, and the evaluation of the construction quality comprises the step of obtaining a quality evaluation index according to the construction progress, the abnormal density and the data point deviation of the construction area; and the interaction module is used for interactively prompting the evaluation result of the construction quality to a manager.

A method (700) by a user equipment, UE (112), includes receiving (702), from a network node (110), at least one network configuration identifier, NW configuration ID. Based on the at least one NW configuration ID, the UE predicts (704) a channel quality for a transmission resource.

The invention relates to the technical field of computer information security, in particular to a method and a system for compliance check based on a windows operating system, comprising the following steps: a preparation stage: identifying applicable laws and regulations and industry / internal security standards, selecting check tools, and formulating project plans; in the data acquisition stage, an operating system version, a patch, a user permission, network configuration and log information are acquired through WMI or PowerShell; the beneficial effects are that through the automatic compliance inspection process, the manual inspection time is greatly reduced, and the working efficiency is improved; and monitoring a plurality of dimensions, such as configuration, application, permission, patches and the like, of the Windows operating system to ensure that various configurations of the operating system meet security standards.

This disclosure is generally directed to wireless communication systems and methods and relates particularly to a mechanism for implementing an artificial intelligence framework for adaptively configure the over-the-air communication interfaces of the wireless communication systems. AI network configuration functions may be provided as services for AI-assisted network configuration (AI configuration services, or AICS). Such AICS may be requested and configured via various messaging and signaling mechanisms. The AI model life cycle management including training, delivery, activation, inference, deactivation, switching, performance evaluation, and the like may be configured, triggered, and otherwise provisioned via control and data messages and signaling communicated between the various network elements in the wireless communication system.

The invention provides an automatic generation method for a large language model network script generated based on graph retrieval enhancement, and belongs to the field of communication technologies and artificial intelligence. The automatic generation method comprises a configuration script generation step and a configuration verification step, the configuration script generation step comprises the steps of carrying out knowledge mapping on a current network topology and a user manual, carrying out data processing and then constructing graph retrieval enhancement generation, and according to a network intention of a user, carrying out configuration verification on the graph retrieval enhancement generation; related equipment in the network topology is retrieved through the graph retrieval enhancement generation technology, and network information is returned. Generating a configuration script by utilizing the reasoning ability of the large language model through a prompt project; in the configuration verification step, a test case with intention validity is generated through a large language model, whether the generated configuration script conforms to the intention of a user or not is verified, in the process, graph retrieval enhancement generation and test case generation improve the accuracy of the network script, and the network operation efficiency is guaranteed.

The invention belongs to the field of stability analysis of a grid-connected system of a grid-building converter, and particularly relates to a grid-building converter grid-connected resonance risk analysis method considering virtual impedance, which comprises the following steps: S1, establishing a three-phase time domain differential equation and simplifying the equation into a single-phase equivalent time domain model; converting into a harmonic state space model of the main circuit; s2, constructing a harmonic state space model of a control system comprising an active power control loop and a reactive power control loop; s3, introducing a virtual impedance control link, and correcting the voltage amplitude reference phasor output by the reactive power control loop; deriving an expression of a modulation signal disturbance phasor; s4, obtaining a complete frequency domain admittance model YGSC of the network construction converter considering the influence of the virtual impedance; an open loop gain TGFM of the grid converter grid-connected system is constructed; and S5, drawing a Nyquist curve based on TGFM, and carrying out resonance risk determination. According to the method, the interaction dynamic characteristics of the network building converter and the power grid under the influence of the virtual impedance can be accurately represented, and the resonance risk of the grid-connected system is evaluated.

The invention discloses a network configuration benchmark checking method based on depth features, which comprises the following steps: acquiring an operating system type of to-be-checked equipment, and configuring a target operating system type according to the operating system type of the to-be-checked equipment; entering a background of the to-be-detected equipment based on an identifier in the target operating system type, a command prefix and a command parameter when a baseline is executed in the target operating system type; obtaining description rules about the depth features of the inspection item types and the weight of each feature; establishing a general script management check folder and a specific version script check folder; aiming at each script in the general script management check folder and the specific version script check folder, carrying out check and security assessment, and generating a security assessment report of the to-be-checked equipment; and establishing a check log by using the security assessment report of the to-be-checked device, and judging the security risk of the check log. The management efficiency can be improved.

This application provides a network configuration method, an apparatus, and a device. In the method, a terminal device may receive a plurality of groups of DRX parameters, and related parameters such as DRX cycles in the plurality of groups of DRX parameters are configured differently, so that DRX configurations can better match features, such as data arrival time and data amount, of different data flows. In this way, the terminal device can wake up in time when data arrives, and monitors a PDCCH for a proper period of time, to ensure a service delay and user experience. In addition, monitoring time is not longer than time needed for the data amount, helping

Embodiments identify a station that rotates an over the air station address. As address rotation was not originally designed into wireless networks, the rotation can introduce communication challenges for the station. The embodiments derive that traffic referencing two different over the air station addresses are associated with a single common station. This is accomplished by determining a similarity between properties of two sets of traffic. A first set of traffic references the first over the air station address and a second set of traffic references the second over the air station address. If the properties common across the two sets of traffic indicate sufficient similarity, the embodiments determine that both sets of traffic are associated with a single device. Network configuration of the device is then adjusted based on the determination.