5 results about "Adjacency list" patented technology

This application relates to the fields of power distribution network technology and deep learning technology. It discloses a method, apparatus, and device for generating power distribution network topology diagrams based on temporally explicit networks. The method includes: a power distribution network automation system generating an adjacency list for the current time; dividing multiple nodes in the adjacency list into multiple regions, selecting the bus node of each region as the traversal start node for each region, creating a corresponding worker thread for each region, and performing a breadth-first search traversal operation on each region starting from the traversal start node to obtain a connection tree for each region; merging the connection trees of each region to generate the connection tree of the power distribution network; converting the connection tree of the power distribution network into a topology matrix of the power distribution network; inputting the topology matrix of the power distribution network into a drawing tool; and having the drawing tool generate the topology diagram of the power distribution network at the current time. This application is beneficial for improving the efficiency of topology diagram generation.

This invention discloses a method for local feature transfer and fusion of a 3D model, belonging to the field of 3D reconstruction technology. The method includes: loading and parsing the original model and the target model; constructing and caching a mesh topology adjacency list to achieve O(1) complexity neighbor lookup; selecting the corresponding boundary control circle and performing centroid normalization; calculating the optimal rotation matrix through singular value decomposition of the covariance matrix, and constructing a rigid transformation matrix by combining an adaptive scaling factor; replacing the vertices of the local region of the transformed target model with those of the original model to generate a fused model; performing multi-level expansion of the splicing region based on the adjacency list, and applying Taubin forward and reverse smoothing iterations to eliminate seams. This invention ensures registration accuracy and global optimality through SVD decomposition, effectively prevents model volume shrinkage through Taubin bidirectional smoothing, and significantly improves computational efficiency through the adjacency list caching mechanism, achieving high-quality, high-efficiency, and automated local feature transfer and fusion of a 3D model.

The application discloses a local differential privacy graph data synthesis algorithm based on a neighborhood structure, and comprises the following steps: obtaining the disturbed node degree and the adjacency list of each user, and calculating a projection threshold value for constraining the sensitivity of triangle counting; using the projection threshold value and the disturbance mechanism to guide the user to calculate and report the core neighborhood structure information, and jointly optimizing the collected two neighborhood statistics of the degree and the triangle count value, correcting the structural inconsistency, and completing the generation of the target statistics; using the corrected target statistics to group all nodes, and sequentially executing an edge generation algorithm within and between groups, preferentially meeting the triangle count target, and then meeting the degree value requirement, and completing the construction of the synthesized graph meeting the local differential privacy protection. Under strict privacy protection, the application significantly improves the availability and fidelity of the synthesized graph data by maintaining the key neighborhood structure of the graph.

This invention discloses a storage optimization method and system for crowdsourced querying of knowledge graphs in the field of Traditional Chinese Medicine (TCM). The method includes: storing TCM RDF triple data in the form of an adjacency list; constructing an uncertain edge index based on a hash table and a definite edge index based on a B+ tree for different patterns in crowdsourced queries, where the known predicate is not the subject / object or the known subject / predicate / object combination, with index entries pointing to an inverted linked list storing entity ID sequences; supporting dynamic maintenance of the adjacency list and indexes during incremental data updates; for unknown nodes in the query graph, retrieving the candidate entity ID set for each edge using a hybrid index, and calculating and returning the top K candidate nodes with the minimum overall cost based on a preset crowdsourcing cost using a Top-K matching algorithm based on a max-heap. This invention effectively solves the problems of low storage efficiency, index mismatch, and poor update scalability in TCM knowledge graph crowdsourced query scenarios, achieving efficient storage, fast querying, and low-cost crowdsourcing.

The invention relates to methods, storage media, and vehicles for navigating an optimal path. Among other things, techniques are described for generating a collision-free path by connecting C-patches via cell decomposition. The environment is sampled at discrete headings of the vehicle to generate a configuration space (C-space) with one or more C-patches. A first C-patch is decomposed into one or more cells representing free space. A C-patch adjacency list is generated for the first C-patch. A super-adjacency list is derived that connects vertices of interest across one or more C-patches to form a super-adjacency graph. In embodiments, Dubins paths are used to connect vertices of interest within and across C-patches to ensure kinematic feasibility of all searched paths. An optimal path is navigated, where the optimal path is the shortest path on the super-adjacency graph from a start pose to a goal pose.