31 results about "Node level" patented technology

The present application belongs to the technical field of wind tunnel test, and discloses a method and device for verifying the effect of hot deformation prediction of a flexible nozzle panel. The present application builds a complete verification closed loop of data acquisition-surface reconstruction-node level comparison-statistical determination, quantitatively evaluates the hot deformation prediction accuracy based on the maximum absolute error and statistical distribution characteristics, and clearly distinguishes between valid and invalid states, solving the problem of lack of standardized verification means in the prior art and providing a reliable accuracy evaluation basis for flexible wall nozzle surface control.

This application discloses a protocol migration method, apparatus, electronic device, and medium, relating to the field of database technology. The method includes: generating a flow control rule set based on a preset migration order and node information of cluster nodes in a target database that have enabled a dual-protocol stack listening mechanism; the target protocol address is generated by the cluster nodes based on a stateless address auto-configuration mechanism; distributing the flow control rule set to network devices connected to the cluster nodes, enabling the network devices to perform flow control on the cluster nodes according to the flow control rule set; and controlling the target database to update the address field of the cluster nodes in the cluster topology table from the original protocol address to the target protocol address, so that the cluster nodes switch node communication from the original protocol to the target protocol based on the updated cluster topology table. This application achieves full-process automation of protocol migration, precise flow control at the node level, and seamless and smooth decommissioning of old protocols without any service interruption.

The application discloses a kind of topological optimization method, device, medium and equipment based on CutFEM and SIMP, method includes: definition design domain, discrete design domain into background grid unit, with node density as design variable;Node density is converted into node level value;According to node level value, unit is divided into entity, blank and cutting unit;Subgrid division is carried out to cutting unit;Boundary is identified as inner boundary and outer boundary;Stiffness matrix assembly is carried out to the material area unit of entity unit and cutting unit, obtains node displacement;Solving topological optimization formula, calculating sensitivity updates design variable, until optimal structure is obtained.The application combines CutFEM and SIMP, can solve the problem of insufficient calculation accuracy and efficiency of existing SIMP method under complex geometry and boundary conditions.

The application relates to the technical field of smart grid, in particular to a power distribution network construction method and system based on a standard digital model. The method comprises the following steps: collecting position information, voltage and power of line nodes; screening a local line node set of each line node based on the position information of the line nodes, and calculating a neighboring node density based on the same; determining a weighted power of each line node based on the distance between the line nodes and the power, and combining the power of the line node and its neighboring line nodes and the neighboring node density to obtain a power influence degree of the line node; obtaining a fragile attention degree of the line node based on the difference between a voltage peak factor of each line node in a preset time period and a standard voltage peak factor and the power influence degree; determining an important attention degree based on the fragile attention degree and a node degree; and marking and constructing a node level based on the important attention degree. The application more accurately evaluates the importance of nodes.

The application discloses a kind of capacity limited vehicle path problem solving method based on timing coding and attention mechanism, first construct the initial feasible solution satisfying constraint condition, and current solution is expressed as containing node level, journey level and solution level hierarchical feature structure;By timing modeling to node sequence in journey and aggregation, journey level feature is obtained, and then the feature set of multiple journeys is modeled by attention, to generate solution embedding vector representing the overall structure of solution;The solution embedding vector is fused with environmental state features and input into the policy decision network, and the selection result of local optimization operator is output, and the solution is iteratively updated according to the selection result until the termination condition is met.The application can enhance the modeling capability of node order change and inter-journey correlation, and improve the stability and generalization performance of the algorithm under different scales.

This invention relates to a computing power network construction and coding scheduling method for satellite-to-ground semantic communication, comprising the following steps: S1: Constructing a computing power network composed of LEO satellites, cloud servers, edge devices, and terminal devices; uniformly abstracting and modeling the heterogeneous computing, communication, and storage resources of nodes in the computing power network; S2: Encoding the adaptive joint source channel with dual-awareness of channel and computing power at the node level of the computing power network; realizing dynamic adaptive adjustment of the node-level semantic transmission rate according to channel conditions and computing power status; S3: Scheduling system-level resources of the computing power network to realize distributed, adaptive scheduling and resource coordination of system-level semantic tasks in the computing power network. This invention proposes adaptive joint source channel coding with dual-awareness of channel and computing power, realizing dynamic adaptive adjustment of semantic feature transmission volume by introducing a dual-awareness mechanism of channel state and device computing power.

This invention belongs to the field of greenhouse environmental monitoring technology, specifically involving a distributed environmental data fusion and anomaly diagnosis method, system, equipment, and medium for greenhouse clusters. Edge computing modules are deployed at each monitoring node in the greenhouse cluster, and after local processing, valid data is transmitted to a regional edge server. The regional edge server models and classifies node levels, generating regularized regional data that is transmitted to the central platform. The central platform constructs a node similarity network to diagnose abnormal nodes, combines multiple types of data to construct an environmental field transmission network, generates global environmental field distribution data, stores it in a time-series database, trains and updates a global collaborative diagnostic model, inputs the current global environmental field data into the model, outputs anomaly identification results, and correlates these with node diagnostic results to generate a final diagnostic result. The diagnosis effectively distinguishes between real environmental anomalies and equipment malfunctions, improving the accuracy of greenhouse environmental monitoring.

The application provides a NUMA-aware optimization system and method for an NVM key-value database, comprising a proxy module: creating a proxy thread pool for each node of the NUMA; the thread pool converts data operation requests sent from each node to the local node into local access through a proxy mode; a monitoring module: monitoring the running state of the system and collecting running data; the running data comprises running data at the proxy thread level, running data at the proxy node level and running data at the system level; a scheduling module: scheduling the proxy threads in the proxy module. The application proposes a node multi-proxy mode, which can convert any node access request to the local NVM into local access through a certain number of proxy threads, thereby solving the performance decline problem of NVM database cross-end access and high concurrency access under the NUMA architecture.

The application belongs to the field of power dispatching system automation, and discloses a power grid dispatching control system reliability evaluation method and system based on a multi-dimensional state dependency graph. The application collects node states, slice group states, service call chains, system resource usage, and primary-backup consistency check results and other operation monitoring data, constructs a multi-dimensional state dependency graph (MDDG), and unifies the deployment relationship between nodes and slice groups, the cross-node data access relationship between nodes, the call relationship between services, the system resource competition relationship, and the primary-backup data consistency relationship into a dependency relationship structure, so as to reflect the dependency strength between various operation entities in the distributed dispatching control system, extend the system reliability evaluation from the traditional single-component or single-node level to the system overall structure level, and improve the expression capability for complex distributed architectures.

The application discloses a kind of wind power layered dynamic optimization scheduling methods based on high reliability guidance, belong to power grid dispatching technical field.The method includes:1. constructing node power prediction benchmark, and introducing frequency domain feature analysis module, the predictability and reliability index of each level prediction result is quantified in real time by discrete fourier transform;2. construct dynamic hybrid coordination mechanism, according to the relative strength of system level and node level reliability, dynamically switch from bottom to top aggregation and from top to bottom decomposition coordination path;3. in from top to bottom decomposition path, introduce physical constraint neural network, reconstruct node power under the premise of strictly meeting power balance equation constraint and line capacity, node voltage and other physical constraints.The application can effectively break the limitation of single coordination direction, significantly reduce voltage deviation and network loss under the premise of guaranteeing system power balance and physical safety, improve new energy consumption efficiency.

This application discloses a directory generation method, apparatus, electronic device, and storage medium. The directory generation method quickly determines the target parent node corresponding to the target directory node from the target mapping information based on the target node level, thereby obtaining a directory tree list of the target webpage. Based on the determination of the target parent node, the target directory node is added to the directory tree list. The target directory of the target webpage is then generated based on the directory tree list after adding the target directory nodes. This process eliminates the need for string matching, effectively improving the efficiency of directory generation and reducing device memory usage. Furthermore, by updating the target mapping information according to the target directory node in each traversal round, the hierarchical relationship between different target directory nodes can be quickly determined when generating the target directory, thereby improving the granularity of directory generation and maintaining its accuracy. This method can be widely applied in the field of cloud technology.

This invention discloses a dynamic computing power routing calculation method and system oriented towards business needs, relating to the field of computing power network technology. The method includes: receiving user business requests and extracting computing power type requirements, computing power size requirements, memory requirements, maximum tolerable latency, and minimum bandwidth requirements as business demand information; at the central controller, based on the computing power status information and computing power prediction information of the computing power scheduling area, combined with the business demand information, performing area adaptation evaluation to determine the suitable computing power scheduling area and suitable edge processor; at the adapted edge processor, based on the node status information of multiple computing power nodes within the adapted computing power scheduling area, performing computing power node matching analysis to determine the optimal computing power node; and scheduling the business request to the optimal computing power node for processing. This invention achieves precise matching and load balancing of computing power resources through two-level collaborative scheduling at the area and node levels, improving the overall resource utilization of the computing power network.

The application discloses a data segmentation method, system, device and medium based on a streaming distributed splicing, which are corresponding solutions, in which three-dimensional body data is divided into multiple blocks, a wavefront ready queue is formed according to a topological dependency relationship between each block and a space predecessor block, data loading, reasoning, intra-block merging, inter-block merging and distributed label merging are performed, different processing stages of different blocks are interleaved and parallel in a cluster, cross-block label matching pairs are written into a distributed and hash set type label merging structure in real time, global label remapping is completed through batch root node query, local path compression and vectorization mapping, node level prefetch throttling, processing unit level post-processing throttling, object storage protection, task retry, atomic submission and breakpoint continuation mechanisms are further set, and therefore the throughput, stability and scalability of three-dimensional image segmentation and splicing are improved.

Automated scaling-related operations may be performed dynamically during execution of a spatial simulation. A spatial partition may be locally reassigned, based on application workload information, from a first application to a second application on the same worker. A quantity of applications on a worker may also be changed during execution of a spatial simulation. A parent spatial partition may be split into child spatial partitions, and child partitions may also be merged back into a common parent partition. Indications of partition splits and merges on each of a plurality of workers may be reported to the plurality of workers. A spatial partition may also be remotely reassigned from a first worker to a second worker, such as based on worker-level resource consumption information and partition information. A quantity of workers that are used to implement a spatial simulation may also be changed during execution of the spatial simulation.

The application discloses a chip testing method, device, medium and program product, and relates to the testing field.The chip testing method comprises the following steps: acquiring an IP level path mapping file and a debugging bus topology description file; splicing a common debugging path, an IP sub-path and a unified access path parsed from the IP level path mapping file to obtain an IP node path information set, and creating a debugging link description set based on an IP name parsed from the debugging bus topology description file; constructing a to-be-tested link according to a to-be-tested link name, the debugging link description set and the IP node path information set; and performing node level propagation detection on the to-be-tested link according to node level excitation. The technical scheme of the embodiment of the application can perform node level propagation verification on the automatically generated to-be-tested link.

This invention relates to a distributed target tracking method, system, and medium based on a Transformer interactive multi-model approach. The distributed target tracking method includes: acquiring observation data and constructing window features for a Transformer auxiliary model probabilistic network; establishing a multi-model IMM framework and performing parallel EKF sub-filtering; converting the local posterior estimates and covariance of nodes into information matrices and information vectors, setting initial values ​​for consistency iterations, and finally obtaining the node reliability in the 1st iteration; constructing symmetric edge scoring on edges, obtaining a double-random consistency weight matrix constructed using symmetric normalization; weighting and fusing neighborhood information according to the double-random consistency weight matrix, completing a preset number of information consistency iterations, and obtaining a fused posterior estimate. This invention improves the timeliness and stability of maneuver pattern discrimination at the node level and suppresses the spread of unreliable node information at the network level, achieving stable and robust distributed target state estimation in degraded scenarios.

A fault-tolerant method based on heterogeneous dual-computer dual-channel flight control computer redundancy architecture, by adopting the heterogeneous design of the host computer and the backup computer, using different architecture processors respectively, and through four-channel data redundancy to realize system redundancy, the main control channel and the monitoring channel complete data sampling and health analysis by the FPGA module. Through the health evaluation mechanism, each control channel is dynamically weighted, and the health channel is optimally selected to participate in decision-making. The invention innovatively realizes a hierarchical fault-tolerant mechanism: when a single channel data failure occurs, the channel dynamic isolation and automatic recovery are executed, realizing data level fault tolerance; when the host node level serious failure occurs, the master-slave smooth switching strategy based on data latch is triggered, and the backup computer takes over seamlessly. The invention effectively avoids the control quantity mutation during master-slave switching, significantly improves the system self-healing ability and flight stability in complex environment, and is especially suitable for unmanned aerial vehicles, helicopters and other aviation platforms with extremely high requirements for flight safety.

The application relates to a unit power generation plan determination method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring multi-source power operation data and a power system topology graph, constructing a graph structured data set, constructing a plurality of independent information flow channels based on the graph structured data set, performing space-time joint coding on each information flow channel to obtain node level feature representation of each information flow channel, performing weighted fusion on each node level feature representation through a preset gating fusion mechanism to obtain a node fusion embedding vector, coupling the node fusion embedding vector and a preset historical output baseline through a preset double-gating residual operator to generate a regional energy power generation power scheme, performing parallel level reasoning on the regional energy power generation power scheme to obtain a unit power generation plan, and performing feasibility checking on the unit power generation plan to obtain a target unit power generation plan to be executed. The method can obtain a more accurate and reliable unit power generation plan, which is beneficial to power dispatching.

The application discloses a kind of active distribution system non-simulation reliability evaluation methods considering flexible interconnection, comprising:1 constructs the active distribution system topological model including main power supply, backup power supply, feeder branch, sectionalizing switch, tie switch, flexible interconnection equipment and load node;2 in single-line fault scenario, three-way topological search is carried out along main power supply path, backup power supply path and flexible interconnection support path respectively, and recoverable power supply node set is obtained and recovery domain division is completed;3 establish the non-simulation calculation model of load node repair outage and switch switching outage;4 the variation of load node outage time before and after flexible interconnection access is unknown, and the equivalent linear equation set is established, and the node level and system level reliability index is solved.The application can depict the fault recovery relationship when flexible interconnection equipment participates in multi-path collaborative recovery, so as to improve the efficiency and accuracy of active distribution system reliability evaluation.

Approaches policy set feature guided node level partitioning for policy search tree optimization are disclosed. A set of policy bins is generated by creating equal-width bins on a given dimension. An original policy set is scanned to determine a number of policies falling into each policy bin in the set of policy bins. An original policy set characteristic is measured based on the number of policies falling into each policy bin. Parameters that represent relationships between the policy set and another policy set are determined based on a number of policies falling into each policy bin and the policy set characteristic. A new policy set is generated based on the parameters. A new policy search tree is generated based on a new policy set. The new policy search tree provides improved build cost or improved search cost as compared a search tree based on the original policy set.

The present disclosure relates to a method, device, equipment, storage medium and product for checking device connection relationship. The method comprises: obtaining a standard format netlist file; obtaining a node level matching checking program; using the program to perform node level matching checking on the standard format netlist file to obtain a node with an error level matching and a device with an error level connection relationship. The embodiment of the present disclosure can check the node with the error level connection relationship and the device in the chip design, solve the error level driving problem by modifying the design or adding a level conversion circuit, and thus can solve the problem of chip performance not meeting the expectation, chip yield reduction or chip long-term failure from the design source.

This application relates to the field of communication technology, providing a ring network identification method, apparatus, electronic device, storage medium, and computer program product. The method includes: determining the network information to be identified based on the network element information of each node in the packet transmission network to be identified, the correlation relationship between each node, and the distance information between each node; inputting the network information to be identified into a ring network identification model to obtain the ring network identification result output by the ring network identification model; the ring network identification model is obtained by training a target variational autoencoder based on the sample network information and labels of the sample packet transmission network; the labels are ring network or non-ring network; the target variational autoencoder is obtained by fusing a deep clustering algorithm, a node-level graph convolutional network, and a feature-level graph convolutional network on the basis of the variational autoencoder; the input data of the feature-level graph convolutional network is generated based on the input data of the node-level graph convolutional network. This application can improve the accuracy of ring graph identification for PTN.

This invention provides a hybrid cloud workflow task scheduling method based on topology analysis and privacy quantification. It calculates task allocation time, data transmission time, backup time, encryption time, and decryption time for a second set of tasks to be allocated to the public cloud, calculates the total cost of each particle, and outputs the optimal scheduling scheme with the goal of minimizing the total cost. The second set of tasks to be allocated to the public cloud includes tasks with encryption level allocation and proactive fault-tolerant backup. Highly sensitive tasks are allocated to the private cloud through privacy cost estimation. Based on breadth-first search to determine node levels and betweenness centrality to identify critical task nodes, proactive backup is implemented to cut off cascading fault propagation links. This invention obtains a globally optimal task scheduling scheme while satisfying privacy and reliability constraints, balancing resource consumption and data security, improving the reliability of task scheduling in a hybrid cloud environment, and reducing overall scheduling costs.

The application discloses a positive sample selection enhancement method based on structural fingerprints and dynamic time warping, first constructs a multi-hop degree sequence as a structural fingerprint at a node level, calculates the structural distance of any two nodes by using hierarchical DTW, and aggregates the structural distance into a structural similarity matrix; then performs row Top-k sparsification on the similarity matrix to determine a node-level positive sample set with consistent roles; maps the node-level positive sample to a cluster level based on a hard assignment matrix obtained by graph partitioning, and performs contrastive learning on cluster features without message passing. Compared with the existing positive sample construction method which depends on random augmentation, the application can significantly reduce "false positive / false negative" noise, and still maintain stable and consistent semantic alignment on graphs with low homomorphism and many noise edges; meanwhile, with the help of a cluster-level training path, the training complexity is reduced from the edge scale to the node and cluster scale, realizing an efficient, reproducible and deterministic graph contrastive learning process.

This disclosure provides a resistor string digital-to-analog converter (DAC) and its design method. The DAC includes segmented resistor strings, each comprising a high-order resistor string and a low-order resistor string. The connection method between the segmented resistor strings is controlled by segmented data. The connection method includes series and parallel connections. The segmented data is obtained by segmenting the input data, which includes high-order input data and low-order input data. The high-order input data corresponds to the high-order resistor string, and the low-order input data corresponds to the low-order resistor string. The first end of the high-order resistor string is coupled to the input reference voltage terminal, and the second end is grounded. The low-order resistor string is connected in parallel to the two ends of the resistors in the high-order resistor string via a high-order parallel switch group. The output level of the DAC is obtained from the node levels in the low-order resistor string via the low-order switch group. This disclosure solves the problem of low accuracy in resistor string DACs in related technologies.

The present application relates to the field of recommendation system, and discloses a point of interest recommendation method based on tree representation trajectory and multi-granularity contrast learning, comprising: obtaining user historical check-in data set and preprocessing; dividing user check-in into day level, time period level and original check-in level node according to check-in time, and constructing multi-time granularity trajectory tree structure; constructing a recommendation model integrating global enhancement and contrast learning, training and testing the model using the data set, and obtaining the prediction result. In feature extraction, a global graph is introduced for the trajectory tree structure, and graph convolution network is used to initialize the features of leaf nodes, so as to strengthen the model's ability to capture global dependency; contrast learning strategy is introduced at each granularity node level, and the model is guided to learn semantic consistent trajectory representation through positive and negative sample constraints. The present application balances local spatio-temporal constraints and global transfer rules while mining user multi-time granularity preferences, and significantly improves the accuracy and personalization of point of interest recommendation.

The application provides a configuration information verification method and device of a network device, and a storage medium. The method constructs a search tree corresponding to an actual configuration file of a target network device, and constructs a search expression group corresponding to an expected configuration record of the target network device. For each search expression, a first node at a corresponding node level is found according to a search level, and when an expected configuration instruction of the search expression is different from an actual configuration instruction of the first node in semantics, a next sibling node is jumped to for verification according to a line number of the next sibling node indicated by a node index of the first node, a semantic verification result is obtained, and then each semantic verification result is summarized to obtain a consistency verification result. The embodiment of the application can reduce the search time complexity.

The application discloses a kind of multimodal procedure automatic repair method, system, equipment and storage medium, method includes: by existing tool, source code is converted into abstract syntax tree AST;Anonymity variable and coding node;Build program repair model, the program repair model;The program repair model is pre-trained, and the pre-training includes two training tasks, one is to cover language model MLM task, let program repair model focus on the information of AST node level;Two are node order judgment NOJ task;After obtaining the trained program repair model, the multimodal procedure to be repaired is repaired using the trained program repair model.The application adopts the technical scheme of fusing multimodal information, solves the technical problem that model cannot learn the semantic, structural information of code sufficiently, so as to achieve the technical effect of fully utilizing the auxiliary information of code and finally making model learn more abundant semantic, structural information.

The present application relates to the technical field of goaf measurement, in particular to a kind of mine goaf measurement data visualization method and system, the combination weight of direction vector and neighborhood edge tangent number value is constructed in node level, node elevation meets smoothness and position constraint in horizontal and vertical direction simultaneously, the elevation change of high difference mutation area obtains controllable interpolation in the range of multiple nodes, by using the numerical propagation characteristics of Laplacian in weight system, the coordinate adjustment quantity presents the change trend that is restricted by neighborhood direction consistency and local curvature boundary in space, the continuous form of wall node and local mutation position are synchronously expressed in the whole surface, the elevation segment generated by Gaussian process regression is written into node position record, and the reliability of through part identification, wall trend judgment and surrounding rock stability parameter reading is improved by constructing multi-scale node connection path combined with distance weight controlled by attenuation factor.