12 results about "Multiple edges" patented technology

In some examples, a method of determining a shortest path between two locations includes: a first device receiving a first graph representing a graph network including a plurality of regions, each region including a plurality of vertices and a plurality of edges; identifying each of the plurality of regions and sending the first map to a mobile device; the first device partitions the first map based on the identified plurality of regions, thereby generating a set of partition maps, each region of the identified plurality of regions corresponding to a respective partition map of the set of partition maps; generating, by the first device, a second graph defining information including the set of partitioned graphs and defining connectivity between the set of partitioned graphs, and transmitting the second graph to a mobile device; traversing, by the mobile device, the second graph to determine an advanced path including a plurality of shortcuts representing a side of the plurality of sides of the first graph that connects a first vertex and a second vertex; the mobile device determines a shortest path between the first vertex and the second vertex, the shortest path being determined based on the advanced path, the shortest path comprising an edge connecting the first vertex and the second vertex in the plurality of edges of the first graph; and the mobile device outputs the shortest path.

This application discloses a lightweight preprocessing method for geometric components in 3D scene rendering, relating to the field of 3D rendering. The method includes: when there are multiple edge points in a triangular mesh model, performing component edge shape detection based on the position information of the multiple edge points to determine whether the component to be processed is a cylindrical component; when the component to be processed is determined to be a cylindrical component, performing circular fullness detection on the bottom surface to determine whether the cylindrical component is a cylindrical pipeline; converting the geometric features of each cylindrical pipeline into an instantiated reuse matrix; combining the view frustum parameters of the current viewpoint and the instantiated reuse matrix to perform view frustum culling and occlusion judgment to determine whether each cylindrical pipeline is visible; for cylindrical pipelines, collaborative optimization is achieved in three stages: recognition efficiency, lightweight transmission, and rendering visibility screening. Through the preprocessing mechanism in the early stage of rendering, the overall efficiency of subsequent rendering is effectively improved.

The application discloses an AI-enhanced knowledge graph quality anomaly tracing method based on industrial big data, obtains historical production data and real-time production data corresponding to multiple data sources in an industrial production line, the multiple data sources including a manufacturing execution system, an enterprise resource planning system, a sensor collection system and a quality detection system; the historical production data is preprocessed based on preset data cleaning rules and data alignment rules, an industrial big data set reflecting production elements in the whole life cycle of a product is constructed, the production elements including equipment parameters, process parameters, material properties, environmental conditions and operation specifications; multi-source heterogeneous data in the industrial big data set is subjected to feature extraction and entity alignment operations by using a deep graph attention network, and an initial quality knowledge graph containing multiple nodes and multiple edges is generated, wherein the nodes represent production entities, and the edges represent process correlation relationships and material flow direction relationships between the production entities.

The application discloses a retrieval enhancement generation method and related products, which comprises the following steps: obtaining a query vector; matching the query vector with a multi-dimensional feature graph to determine a target node; the multi-dimensional feature graph comprises multiple nodes and multiple edges; the node represents a node vector; the edge represents a relationship vector; there is an index relationship between the node vector and the relationship vector; the multiple nodes comprise the target node; performing feature extraction on the query vector to obtain a relationship feature corresponding to the query vector; performing dynamic graph walking in the multi-dimensional feature graph based on the target node and the relationship feature to obtain one or more effective paths; and obtaining a final answer based on the one or more effective paths. The application effectively avoids the "illusion" risk of a large model, ensures that the output content is compliant, reliable and auditable, improves the accuracy of the retrieval result in retrieval enhancement generation, and effectively breaks through the inherent limitations in semantic integrity, multi-hop reasoning capability and relationship intention understanding.

Generating transportation network solutions using graph neural networks, includes: generating, based on input data describing a product transportation network, a graph neural network representing the product transportation network, wherein the graph neural network comprises multiple edges, multiple source nodes, multiple destination nodes, and multiple intermediary nodes; performing a graph neural network prediction based on the graph neural network, wherein performing the graph neural network prediction comprises predicting inclusion in the transportation network solution for each edge and intermediary node; and generating a transportation network solution by performing a model optimization using an initial state based on the graph neural network prediction.

The application discloses an industrial internet remote monitoring operation and maintenance management system and method, and belongs to the technical field of industrial internet. The method comprises the following steps: in response to access requests of multiple edge nodes, collecting real-time running state parameters of each edge node and performing heterogeneous data graph construction to obtain a dynamic attribute graph structure; performing federated transfer learning on the multiple edge nodes based on the dynamic attribute graph structure to obtain a cross-domain joint inference model; constructing a dynamic reconfigurable digital twin corresponding to each edge node, and performing closed-loop dynamic reconfiguration on the digital twin by using real-time feedback data; performing multi-step simulation deduction based on the reconfigured digital twin to generate an adaptive operation and maintenance strategy; and decomposing the adaptive operation and maintenance strategy into an atomic control instruction sequence, and delivering the atomic control instruction sequence to an execution unit through an asynchronous message queue to realize remote collaborative control.

Generating transportation network solutions using graph neural networks, includes: generating, based on input data describing a product transportation network, a graph neural network representing the product transportation network, wherein the graph neural network comprises multiple edges, multiple source nodes, multiple destination nodes, and multiple intermediary nodes; performing a graph neural network prediction based on the graph neural network, wherein performing the graph neural network prediction comprises predicting inclusion in the transportation network solution for each edge and intermediary node; and generating a transportation network solution by performing a model optimization using an initial state based on the graph neural network prediction.

This invention provides an AI-based method, system, and platform for automatic multi-document parsing. The method includes: acquiring a candidate set of ghost references and performing cyclical sequential joint inference using a conditional random field to obtain a ghost reference set; acquiring four-dimensional feature vectors based on the ghost reference set and the original document, constructing a Bayesian network using these vectors, and obtaining the inference result through inference via the Bayesian network; creating a document heterogeneous graph based on the ghost reference set and the original document, generating aggregated text node vectors through attention aggregation based on multiple edge types, and obtaining community results using a community adversarial strategy; constructing a document dynamic graph based on the community results and temporal data, obtaining hidden states by processing the temporal and spatial dimensions of the document dynamic graph, and outputting the parsing result. This method uses ghost references as a unified analytical clue and central feature to construct a multi-dimensional joint evaluation intelligent parsing framework to improve the depth of document parsing.

This invention provides an image interference method, apparatus, device, storage medium, and program product, relating to the field of data processing technology. The method includes: acquiring an attribute graph of a first image, the attribute graph including multiple nodes, multiple edges, and a node feature matrix, the node feature matrix being used to characterize the features of different nodes among the multiple nodes; generating a first perturbation adjacency matrix based on the node feature matrix, the first perturbation adjacency matrix being used to characterize the structural perturbation of different nodes; generating a first node feature perturbation parameter corresponding to each of the multiple nodes based on the multiple edges; and perturbing each node based on the first node feature perturbation parameter corresponding to each node and the first perturbation adjacency matrix, respectively, to obtain an interference image, the interference image being used to train an image recognition model. This invention can improve the effect of image interference.

This application discloses an object representation method, apparatus, device, storage medium, and computer program product. The method includes: acquiring an object relationship topology graph, which includes multiple nodes and multiple edges; each node represents an object, and nodes corresponding to two objects with an association relationship are connected by at least one edge; using multiple object information sources, mining the node similarity between connected nodes in the object relationship topology graph to obtain a similarity matrix; based on the similarity matrix, performing characterization processing on each node in the object relationship topology graph to obtain a node characterization vector for each node; and using the node characterization vectors of each node as the object representation vectors of the corresponding objects. This application embodiment can effectively improve the accuracy of object representation.

This invention belongs to the field of information detection and provides a fast graph clustering detection method and system based on dual verification. This invention captures topological features through lazy random walk sampling and constructs a structurally similar graph to verify clustering properties. For each candidate cluster, multiple edges are uniformly and randomly sampled from the edge set corresponding to that cluster in the original graph. The label with the highest frequency among the sampled edges is counted, and its empirical proportion is calculated. Based on the comparison between the empirical proportion and a set threshold, it is determined whether the original graph satisfies label consistency. The entire process is completed within sublinear query complexity. This invention incorporates label consistency constraints into the clustering test, making the judgment criteria simultaneously cover topological cohesion and semantic homogeneity, thus improving the speed and accuracy of graph clustering detection.

This invention discloses an alarm tracing method, apparatus, and electronic device for a power dispatching system. The method includes: collecting multi-source heterogeneous alarm data from the power dispatching system within a predetermined time period; determining multiple alarm characteristic parameters based on the multi-source heterogeneous alarm data; constructing an initial causal graph based on the multiple alarm characteristic parameters; determining the correlation between the alarm events corresponding to the two nodes of each edge in the multiple edges; performing corresponding target operations on the multiple edges in the initial causal graph based on the correlation determination results for each edge, obtaining a target causal graph; and tracing the alarm sources in the power dispatching system based on the target causal graph to obtain the fault results. This invention solves the technical problem in related technologies where it is impossible to quickly determine fault results when there is a large amount of alarm data in the power dispatching system.