36 results about "Network analysis" patented technology

This invention discloses a method for constructing a natural-artificial water network model and analyzing its connectivity, including: collecting basic data; generalizing nodes and edges of the natural and artificial water networks and adding weights to the edges; constructing a natural-artificial water network model based on complex networks; constructing the degree distribution of structure and flow based on node degrees; and calculating the structural connectivity and flow connectivity of the natural-artificial water network based on the degree distribution. This invention combines complex network theory to model natural-artificial water networks and analyze their connectivity, solving the technical problem of lacking comprehensive modeling and connectivity assessment in existing water network analysis methods, and providing new analytical ideas and technical support for water resource management and water network structure optimization.

The application provides a transient ground potential rise induced coupling determination method through cable shielding layer, and belongs to the technical field of cable shielding layer.The application establishes a distributed parameter partial element equivalent circuit model of a grounding network, solves transient ground potential distribution by using a finite difference time domain method, obtains equivalent transfer impedance frequency characteristics of a braided shielding layer by using a four-port S parameter vector network analysis method and a variational asymptotic homogenization multi-scale algorithm, solves core line common mode voltage and differential mode voltage by establishing a multi-conductor transmission line equation group, constructs an artificial intelligence prediction model based on a topology perception graph neural network, solves a large-scale sparse admittance matrix by using a multilevel fast multipole method to obtain full network induced voltage distribution, and establishes a quantitative relationship model between ground potential rise and core line induced voltage, so that the technical problems that cable core line induced voltage caused by transient ground potential rise is difficult to accurately predict and effectively suppress are solved.

The application discloses a circuit pre-training method and device based on a graph neural network and electronic equipment, comprising the following steps: for a large-scale circuit, a circuit network graph is constructed, a random walk road is generated, and the road is used as a sample for model training; a node2vec model is trained using the road sample; a model with the minimum loss function value is selected as an optimal model; and the optimal model is loaded, and representation vectors of all nodes are output and saved. In the application, the node2vec pre-training model of the graph neural network is used, the information of a long-distance standard unit is fully absorbed to absorb local circuit structure features, deep representation of nodes is automatically learned from the circuit structure, and tedious manual feature engineering is avoided, thereby providing high-quality representation vectors for a downstream model. The node representation learned by the node2vec model is a task-independent general feature, can be flexibly applied to various downstream tasks, and provides support for subsequent circuit analysis and optimization design work.

The present application relates to the technical field of network analysis, and further relates to a network resilience index multi-dimensional quantitative evaluation method, which comprises the following steps: step 1: obtaining original topology data of a target network, and constructing a topology base resilience index of the network under the condition of no external impact; step 2: calculating a crisis exposure factor; step 3: calculating the intermediate centrality of each node; calculating the structural hole limit system of each node; combining the intermediate centrality and the information redundancy degree to generate an adaptation-recovery index for measuring the self-healing and regenerative capacity of the network; step 4: correcting the topology base resilience index and the crisis exposure factor to resist impact, then amplifying the index weight according to the adaptation-recovery index, and combining the stability correction of network resilience fluctuation to finally generate a multi-dimensional network resilience comprehensive index. The present application is helpful to realize network vulnerability identification and resilience strategy optimization based on structural attributes and dynamic historical response.

The application discloses a kind of live content auditing method and system based on AI, belong to network live content supervision technical field.The method extracts the multi-dimensional characteristics of anchor by cognitive consistency analysis model, calculates the deviation degree of feature correlation matrix to detect cognitive dissonance;Adopt optical flow tracking and LSTM network analysis microexpression infers implicit intent;Monitoring semantic trajectory drift identifies sensitive content;Construct audience group dynamic graph to analyze emotional transmission intensity;Through bayesian network, from audience abnormal reaction, deduce illegal behavior;Evaluate cognitive load to identify information overload cover;Calculate node centrality to implement transmission blocking;Fusion multi-source information outputs rule determination.System includes cognitive feature analysis, microexpression identification, semantic trajectory monitoring, emotional transmission analysis, reverse reasoning, cognitive load calculation, transmission blocking and decision output eight modules, work cooperatively through event-driven mechanism.The application breaks through the surface limit of traditional audit, can identify cognitive fraud, psychological manipulation and other hidden violations, realizes active defense.

The present application relates to the technical field of biological information data processing, in particular to a kind of arthritis data processing method and system based on ceRNA-network analysis, comprising the following steps: obtaining arthritis sample RNA data and target annotation, extract shared element screening regulation pair, by pathological pathway enrichment and function verification, measure correlation to determine priority, integrate ceRNA network structure to evaluate regulatory influence, parse node role to adjust centrality, generate specific core hub node identification atlas.In the present application, by introducing dynamic transcription consistency pattern recognition and transcription correlation and target co-annotation relationship joint comparison, the accuracy of arthritis data analysis is improved, the evaluation of candidate regulatory pair is strengthened, the result reliability and regulatory confidence level are improved, combined with ceRNA network node regulatory influence evaluation, the identification ability of key node is enhanced, effectively solve the blind spot of traditional method, ensure the accurate identification of arthritis specific core hub node.

The application provides a control system of an LCD attaching device, and belongs to the technical field of control of LCD panel manufacturing equipment. The control system comprises the following modules: a vision module, which acquires a substrate pose and constructs a nonlinear target function, and realizes accurate alignment through ant colony algorithm optimization; a pressure acquisition module, which acquires pressure data and constructs a continuous pressure cloud chart; an extraction and calculation module, which analyzes the cloud chart, extracts a characteristic region, and constructs a risk index; a network analysis module, which outputs a speed adjustment amount and a pressure compensation amount through a fuzzy neural network; and a correction and determination module, which realizes micro-control correction of the attaching speed and pressure. The application realizes high-precision pose alignment and pressure acquisition, quantifies the attaching risk, dynamically regulates and controls the attaching parameters, effectively corrects local deformation of the substrate, and improves the LCD attaching yield.

The application discloses a kind of GaN HEMT equivalent circuit model parameter self-adapting extraction method and system, comprising: extracting parasitic parameter value by small signal equivalent circuit parasitic parameter extraction method, establishes initial population;Stripping parasitic parameter in initial population obtains each bias eigenvalue by network analysis, and simulation equivalent circuit S parameter data is obtained by calculation;Judgment is calculated according to S parameter data individual fitness;New individual is generated to replace singular individual in population until population is non-singular;According to the search range of adjustment algorithm of non-singular population;According to the individual selection, crossover, variation rule set to the individual in initial population is carried out genetic calculation, and new genetic individual is obtained;Whether the preset target is satisfied is judged, and the element parameter corresponding to optimal individual is output as the final parameter of small signal model;I-V model is optimized by genetic algorithm, and the weight matrix of fitness function is updated according to model error, and optimization is carried out again to meet the preset target, and the small signal model parameter is combined to establish large signal equivalent circuit model.The application greatly improves the modeling speed of small signal model and the accuracy of large signal model without sacrificing accuracy, which provides key technical support for reliable design of high-power, high-frequency microwave circuit.

According to various embodiments, a network analysis component of a mobile communication network is described for providing network analysis and / or prediction information about network segment instances of the mobile communication network, comprising a communication interface configured to obtain, for each of a plurality of network segment instances, information about which communication network components are part of the network segment instance from one or more mobile communication network segment management information storage components, receive a request for network analysis and / or prediction information about a network segment instance from the plurality of network segment instances, and obtain, in response to receiving the request, information for analyzing the state of the network segment instance.of at least one of the communication network components that are part of the network segment instance and a network analyzer configured to generate network analysis and / or prediction information about the network segment instance using the information obtained for the analysis of the state of the network segment instance, where the communication interface is further configured to provide the generated network analysis and / or prediction information in response to the request.

This invention relates to the field of enzyme network analysis technology, specifically a robust system for analyzing the functional balance of a multifunctional enzyme regulatory network. The system includes a network topology analysis module, a graph generation module, a flux balance analysis module, a functional simulation module, a robustness curve fitting module, and a report generation module. It identifies key nodes and vulnerable paths in the target regulatory network; constructs a structural feature association graph; performs flux balance analysis on the target regulatory network to obtain functional flux distribution data; simulates the functional operation of the target regulatory network and quantifies the output efficiency of the simulation results to obtain the core function maintenance degree; fits the perturbation trend of the core function maintenance degree to obtain a functional balance robustness curve; and analyzes the decay mode of the functional balance robustness curve to generate a robustness analysis report of the target regulatory network. This invention can improve the efficiency of functional balance robustness analysis of a multifunctional enzyme regulatory network.

This application relates to the field of urban pipeline network analysis technology, and particularly to a pipeline network connectivity assessment method, device, and related equipment based on DS-PIGNN. The method includes: acquiring pipeline network data, constructing a macroscopic topology map, and collecting the axial microscopic physical field sequence of each pipeline; extracting the features of the microscopic sequence of each pipeline using a one-dimensional residual convolutional neural network, and obtaining a microscopic health state vector through global max pooling; injecting this vector into the edge features of the macroscopic topology map to drive a graph neural network trained with a physical constraint loss function (including Kirchhoff flow conservation), which dynamically calculates the attention weights between nodes based on the hydraulic features of the nodes and the microscopic health state vector; and performing information aggregation based on this dynamic weight, simultaneously outputting the pipeline failure probability and node connectivity reliability. This application achieves dynamic and coupled analysis of microscopic physical damage details and macroscopic network cascade failures, and ensures the physical reliability of the assessment results while maintaining computational efficiency.

The application discloses a method and device for determining node influence, relates to the technical field of network analysis, and is used for improving the accuracy of determining user influence, so as to improve the efficiency of resource allocation and the efficiency of information transmission in a network. The method comprises the following steps: acquiring access information of a plurality of nodes in the network; wherein the access information is information of accessing the network; determining a second node adjacent to a first node and a third node connected to the first node in the network according to the similarity between the access information of the plurality of nodes; wherein the plurality of nodes comprise the first node, the second node and the third node; determining local influence of the first node according to the similarity between the access information of the first node and the access information of the second node; determining global influence of the first node according to the similarity between the access information of the first node and the access information of the third node; and determining influence of the first node in the network according to the local influence and the global influence.

A system for network analysis is provided. The system includes a computer device in communication with a computer network. The computer device programmed to: a) analyze a plurality of devices and a plurality of connections between the plurality of devices on the computer network; b) determine values for each of the plurality of connections between the plurality of devices, wherein the plurality of values are determined based on a security posture of two devices of the plurality of devices on ends of the corresponding connection; c) determine a plurality of paths between a first device of the plurality of devices and a second device of the plurality of devices; d) calculate a security value for each of the plurality of paths; and e) determine at least one secure path of the plurality of paths based on a comparison of the plurality of security values for the plurality of paths.

The application discloses a kind of automatic identification MOS tube gate circuit logic method, device and electronic equipment, the method includes the following steps: S1, check the source-drain sequence of all MOS devices in circuit, and adjust to flip the MOS device that does not comply with connection sequence therein;S2, check whether all pin attributes in circuit are correct, the pin attribute is divided into power supply / ground input pin, signal input pin, signal output pin;S3, calculate circuit diagram truth table: according to the switching characteristic of MOS tube, automatically calculate circuit diagram truth table;S4, truth table is converted into operation logic: call truth table conversion model, and truth table is converted into and or formula logic expression.The application automatically identifies the gate circuit logic formed by MOS tube under integrated circuit reverse analysis, by simulating the analysis logic of experienced engineer, quickly generates truth table to a large number of gate circuits and analyzes, reduces the time of manual analysis, reduces cost, improves the accuracy of circuit analysis.

A business rule hot update method based on quantitative analysis and dynamic arbitration, relating to the field of distributed computing, is disclosed. The method includes: quantifying the impact of data changes on business metrics through rule impact strength network analysis, triggering incremental recalculation only for high-impact changes; routing recalculation tasks to a fixed subset of arbitration nodes using consistent hashing, ensuring strong consistency of results through multi-node parallel computing and load-aware arbitration; storing both arbitration and old versions of the results, and dynamically adjusting the canary release ratio based on a PID feedback controller according to real-time risk indicators to achieve adaptive risk control and second-level automatic rollback. This invention solves the problems of service interruption, data inconsistency, and high release risk in traditional solutions, achieving minute-level, accurate, and secure hot updates of business rules, making it particularly suitable for high-requirement scenarios such as e-commerce and finance.

Various embodiments of the present disclosure relate to the detection of floating gates within analog circuits via analog circuit analysis. In one example embodiment, a technique for performing analog circuit analysis is provided. The technique first includes generating a netlist for each device gate of an analog circuit, such that generating the netlist includes determining a type and a directionality of each device gate of the analog circuit. Next the technique includes generating a circuit model for the analog circuit based on the netlist. Once generated, the technique includes supplying the circuit model and the netlist as input to an analysis engine configured to perform analog circuit analysis. For example, the analysis engine may be configured to execute a formal verification process by outputting a warning for when a floating gate is detected within the circuit model.

This disclosure provides a method, apparatus, electronic device, and storage medium for root cause analysis of user complaints. The method includes: creating an MCP session based on a user complaint work order and initializing the MCP context corresponding to the MCP session; based on the initialized MCP context, calling an NLP-to-SQL agent through the MCP protocol to convert the natural language description of the user complaint into a structured query statement for an O-domain database, executing the structured query statement, and writing the query results into the MCP context in a standard data format; based on the query results in the MCP context, calling a multi-dimensional network analysis agent in parallel to perform specialized diagnosis and writing the specialized diagnosis results into the MCP context; and summarizing the specialized diagnosis results in the MCP context through a root cause reasoning agent to perform comprehensive judgment and root cause localization. Embodiments of this disclosure can significantly improve the objectivity and accuracy of root cause analysis results and greatly enhance the overall collaborative capability of the system.

The application discloses an underground space protection evaluation system based on BIM and multi-source data fusion, which comprises a data input layer, an evaluation engine layer and a result output layer which are sequentially arranged for data transmission and processing, wherein the data input layer is configured to construct a three-dimensional BIM model, an attack mode and a damage path associated rule base based on a terrorist attack parameter base and real-time environment data flow fused by multi-source sensor data, wherein the three-dimensional BIM model is integrated with geological survey data, topographic mapping, structure parameters and civil air defense engineering data through a space topology modeling technology; the evaluation engine layer is configured to receive the three-dimensional BIM model, the associated rule base and the real-time environment data flow of the data input layer, generate key damage propagation simulation results and vulnerability analysis results through explosion dynamic response simulation and space topology network analysis; and the result output layer is configured to generate a three-dimensional space classification map, dynamic design adjustment suggestions and a model self-checking report based on the damage propagation simulation results and the vulnerability analysis results of the evaluation engine layer.

This invention relates to a mobile communication. A first network function (NF) manages ML models and provides one or more suitable ML models to a second network function (NF). According to the invention, the first NF is used to obtain model accuracy binding information from the second NF. The model accuracy binding information indicates the association between analysis information and ML model information. The analysis information indicates the association between an analysis ID and analysis filter information and / or an analysis target. The first NF obtains model accuracy information associated with model accuracy metadata from the second NF. The model accuracy metadata indicates the association between the ML model accuracy information and the analysis information. The first network function is used to determine whether to update the ML model information based on the model accuracy binding information and / or the model accuracy metadata.

A least-cost path selection system includes a computing device. Each of a plurality of travel paths connects any two nodes among a plurality of nodes. The least-cost path is a travel path having the smallest objective function value among the plurality of travel paths. The computing device selects the least-cost path among the plurality of travel paths. A link path is defined as a path connecting any two adjacent nodes among the plurality of nodes. A loop path is defined as a closed path connecting at least three nodes among the plurality of nodes. A loop variable is a variable corresponding to the loop path and having a value and a direction. A link variable is a variable whose direction is determined by loop variables adjacent to the link path. A link cost is a constant corresponding to the link path. The computing device modifies at least one of the plurality of loop variables based on at least one of Loop-wise Route Representation (LRR) and a circuit analysis method to calculate a plurality of reference link variables, each being a link variable with a determined direction. The circuit analysis method includes at least one of Mesh Current Method (MCM), Nodal Analysis, and Numerical Method. The computing device modifies the values of the plurality of loop variables within the range where the directions of the plurality of reference link variables remain unchanged. The computing device selects the least-cost path using a linear objective function.

Devices and methods are provided for enhanced wireless environment reporting. 802.11k reporting provides information that can have limited functionality because they do not provide extended details that can be beneficial to network infrastructure. Enhanced wireless environment reporting allows network devices and client devices to request wireless environment reporting (WER) based on several enhanced parameters. A device, such as a network device or a client device, generates a WER request including at least one of a condition, a peer-to-peer (P2P) specification, a non-IEEE 802.11 specification, or an element restriction, and sends the WER request to another device, such as a client station. The other device generates a WER with the requested enhanced information and sends it to the device. The information included in the WER report can be processed and used to perform network analysis, network management tasks, and other functions that are useful to network infrastructure.

The application discloses a kind of automatic drilling and riveting equipment processing performance prediction methods based on mixed weight distribution mechanism, including obtaining production data, and with processing quality to the production data is labeled label annotation;Based on the influence weight of the production data on processing quality calculated by the improved network analysis method of data sensitivity, and label, production data set and influence weight are composed of data set;Initial model is constructed and the data set is used for training to obtain the processing performance prediction model for predicting processing quality.The method provided by the application can solve the problems of the existing automatic drilling and riveting equipment processing performance prediction method, such as parameter weight depending on artificial experience, fixed weight being difficult to adapt to complex nonlinear and high coupling working condition change, and prediction accuracy and model stability being difficult to consider.

A communication method, a communication device and a communication system. The communication method comprises: a policy control network element sending a first message to a network analysis function network element, the first message being used to instruct the network analysis function network element to acquire state information of an application program running on at least one terminal device, the at least one terminal device being a terminal device used by at least one target user, and the first message comprising identification information of the at least one target user; the policy control network element acquiring recommended package information corresponding to the at least one target user, the recommended package information being determined according to the identification information and the state information of the at least one target user and a full package, and the full package comprising a plurality of different packages; and the policy control network element sending the corresponding recommended package information to the at least one terminal device. The communication method provided in the application can improve the accuracy of the recommended package, because the state information can reflect the real-time state of the application program used by the target user on the terminal device when running.

The present invention relates to a method and system for monitoring the assembly process of at least one component to be assembled into a device. This disclosure generally relates to a method (80) and system (10) for monitoring the assembly process of at least one component (12) to be assembled into a device (14). At least one video stream of the at least one component (12) to be assembled is recorded using at least one visual sensor (20). The recorded at least one video stream is analyzed by an evaluation circuit (38) utilizing artificial intelligence based on at least one artificial convolutional network (40) for a specified installation configuration (22) of the at least one component (12) to be assembled. Based on the analysis performed by the evaluation circuit (38), a notification is output via a human-machine interface (66). The notification depends at least on the actual installation configuration (24) of the at least one component (12) to be assembled and the specified installation configuration (22) of the at least one component (12) to be assembled.

The application discloses a kind of magnetoelectric characteristic capture wireless charging vehicle classification equipment and method, belong to vehicle classification technical field.It includes the following steps: setting up wireless charging vehicle dynamic classification platform, including hybrid electromagnetic induction unit, geomagnetic field induction unit, relay node and background data analysis unit;The circuit of hybrid electromagnetic induction unit is built;Analysis of the circuit coupling of hybrid electromagnetic induction unit, obtain the inductive resonant current information;Geomagnetic field induction unit captures the vehicle geomagnetic disturbance signal when vehicle passes and extracts vehicle shape feature information from it;Relay node receives inductive resonant current information and vehicle shape feature information, and outputs it;Background data analysis unit classifies wireless charging vehicle based on information from relay node.By hybrid electromagnetic induction unit cooperate with geomagnetic field induction unit, the reliability of wireless charging vehicle dynamic classification identification can be effectively improved, which is helpful for intelligent scheduling and management of highway traffic system.

The application provides a circuit direct current simulation step length determination method and device, and relates to the technical field of circuit analysis. The method comprises the following steps: inputting simulation information corresponding to a plurality of first Newton-Raphson (NR) iterations into a target model to obtain a simulation step length multiple output by the target model; and determining a second maximum simulation step length corresponding to a current NR iteration convergence according to the simulation step length multiple and a first maximum simulation step length corresponding to a last NR iteration convergence. The circuit direct current simulation step length determination method and device provided in the application embodiment can accelerate the direct current analysis speed in circuit simulation and improve the direct current analysis efficiency in circuit simulation.

Disclosed in the embodiments of the present disclosure are a model training method and apparatus, and a network function and a storage medium. The method comprises: a first network analysis function receiving first model information sent by a second network analysis function; on the basis of the first model information, performing calculation, aggregation or processing, so as to obtain second model information; and sending the second model information to the second network analysis function, wherein the second model information is used for the second network analysis function to update a local model, and the second network analysis function is provided in at least one of a user equipment (UE), a radio access network (RAN), a network function (NF), and an application function (AF).

A process includes prioritizing candidate network traffic flow profiles. The prioritization includes associating perception scores with respective candidate network traffic flow profiles. Each candidate network traffic flow profile is a member of a profile group of a plurality of profile groups. The process includes associating weights with respective profile groups of the plurality of categories. The process includes, responsive to a network traffic flow, identifying, by a traffic analysis engine, a first observed profile of the network traffic flow corresponding to a first candidate network traffic flow profile. The process includes, based on the perception score associated the first candidate network traffic flow profile and the weight associated with the profile group in which the first candidate network traffic flow profile is a member, determining a policy score; and selecting, by the network analysis engine, a policy to be applied to the network traffic flow based on the policy score.

This invention relates to the field of network analysis and discloses an urbanization spatial correlation network analysis system based on territorial spatial planning. The system includes standardizing multi-dimensional indicators reflecting scientific and educational innovation, urban and rural development, ecological livability, and livelihood security to form urbanization functional state vectors for each town; introducing population size, economic scale, and spatial distance constraint factors to construct an urbanization spatial interaction matrix and generate a spatial correlation network and record network structure parameters; calculating the overall network density, hierarchical characteristics, and node centrality parameters to generate a set of parameters influencing collaborative constraint factors; identifying the development stage of the urbanization spatial correlation network and generating a set of staged collaborative regulation strategies; and simulating and analyzing the resource allocation process between town nodes to output feasible cross-city resource allocation intervals that meet the requirements of network stability and collaborative efficiency. This invention has the advantages of improving scientific rigor and operability.