259 results about "Span tree" patented technology

The invention discloses a cross-institution financial data federated learning modeling system and a privacy compliance verification method, and relates to the technical field of financial data processing, the system comprises a federated aggregation module used for a server to align financial time sequence characteristics of each institution through a timestamp hash alignment strategy, and a privacy verification module used for verifying the privacy compliance of each institution; aggregating the aligned financial time sequence characteristics by using a federated time convolutional network, and generating time sequence model parameters for capturing cross-mechanism global time sequence dependence; the federation reasoning module is used for generating a minimum spanning tree representation of a global enterprise association relationship based on a security multi-party computing strategy by the server side on the basis of a local sub-graph of the enterprise association relationship constructed by each institution client side; the server performs cross-mechanism graph reasoning by using a federated graph attention network and an aggregation graph embedding vector and combining minimum spanning tree representation, and constructs graph model parameters for identifying enterprise associated risks; and the model joint training module is used for the server to fuse the time sequence model parameters and the graph model parameters so as to determine global model parameters.

The invention provides a pile-soil-structure dynamic interaction analysis method, which belongs to the technical field of civil engineering, and obtains system data through three-scale physical model experiments: the first scale pays attention to microscopic soil behaviors, the second scale and the third scale are determined based on a multiphase fluid-solid coupling equation, and the third scale is determined based on a multiphase fluid-solid coupling equation; and respectively paying attention to the mesoscopic interface action and the macroscopic overall response. A pile-soil interface control equation and a pile structure coupling equation are established based on experimental data to form a basic equation set, a domain decomposition method is adopted to divide a calculation area into a fine grid near field and a rough grid far field, and a minimum spanning tree algorithm is applied to optimize grid division. Pile body stress distribution and a soil body deformation field are obtained through numerical solution, a pile foundation transverse displacement function is obtained through analysis solution, finally the pile body stress distribution and the soil body deformation field are combined to form a complete pile-soil-structure dynamic interaction model, and the technical problem that the pile-soil-structure dynamic interaction cross-scale effect is difficult to accurately simulate is solved.

The invention is suitable for the technical field of intelligent power grids, and relates to a G3-PLC communication characteristic-based power distribution network area physical topology identification method, which comprises the following steps of: S10, constructing a power distribution network area physical topological graph model; s20, determining an edge weight in the physical topological graph model of the distribution network area; s30, improving and constraining a minimum spanning tree (MST) based on a Prim algorithm of G3-PLC communication characteristics, and improving a Prim algorithm flow; and S40, identifying the physical topological structure of the power distribution network area. The method is simple in process and convenient to operate, on the basis of not adding extra hardware equipment and any manual operation, the weighted graph is constructed through G3-PLC communication data, the minimum spanning tree (MST) is generated through the Prim algorithm, the physical topological structure of the power distribution network area is recognized, and the recognition accuracy is high.

The invention provides an intelligent fault diagnosis method and system for a photovoltaic system. The method comprises the following steps: collecting multi-source heterogeneous operation parameter data of the photovoltaic system based on an intelligent sensor network and carrying out standardized preprocessing; local feature extraction is carried out on edge nodes, a frequency moment is calculated, data summary aggregation is carried out through a frequency moment optimization algorithm, and a fusion key feature vector set is constructed by using a multi-modal data fusion model; performing anomaly detection based on the normal behavior mode baseline, and generating an abnormal state alarm signal and a preliminary anomaly type indication; constructing a weighted graph model based on a system topological structure, constructing a fault association sub-graph by using an approximate spanning tree algorithm, accurately positioning a fault unit and diagnosing a fault type; and generating and executing a self-healing operation scheme according to the fault diagnosis conclusion. Through the distributed multi-modal data fusion and approximate spanning tree fault positioning technology, rapid and accurate diagnosis and autonomous recovery of the photovoltaic system fault are realized, and the system reliability and the operation efficiency are improved.

The invention provides a method for determining the influence of a straw returning mode on tobacco-rice rotation soil carbon emission, and belongs to the technical field of soil carbon emission. The method comprises the steps that test plots are divided, and different straw returning treatment groups are arranged; installing a static gas tank measuring system and regularly collecting a gas sample; measuring the emission of CO2 and N2O and the concentration of CH4 by using a gas chromatographic method, and calculating the carbon emission flux of the soil; analyzing a straw decomposition process by applying a soil microorganism kinetic equation; analyzing the dynamic change of a soil carbon library based on a carbon recurrent neural network model; constructing a carbon flow network topological structure by using a minimum spanning tree algorithm and identifying key nodes; according to the method, comprehensive influences of environmental factors, crop growth parameters and microbial community structures on carbon emission are integrated through a multi-head cross attention mechanism, accurate quantification and prediction of straw returning carbon emission are achieved, and a scientific basis is provided for optimizing a farmland carbon management strategy and promoting conversion from a farmland carbon source to a carbon sink.

The invention discloses a microscopic image scanning and parallel efficient splicing method based on a spanning tree, which considers the characteristic that the scanning visual angle of a microscope is distortionless and the characteristic that the corresponding relation between the physical scale and the pixel scale of a microscope platform is unchanged, and has the advantages of an image matching algorithm based on a template. Automatically dividing an overlapping region range for a template matching algorithm, fully considering the matching result credibility of the pictures on the surrounding adjacent sides, and calculating a global splicing point location by using a spanning tree algorithm; picture splicing types are divided through rows and columns, the problem of memory access conflicts is avoided, the computing power improvement brought by multiple threads is fully utilized, and the picture splicing efficiency is improved. According to the method, adjacent image matching, high-precision matching of global splicing point locations based on the spanning tree and a multi-thread high-speed image splicing technology are realized.

The invention discloses a root system point cloud skeleton extraction method, system and device, and the method comprises the steps: obtaining a plant root system point cloud, carrying out the point cloud division of the plant root system point cloud, and forming a root system voxel grid set; a root system voxel graph is constructed, connection is performed based on the spatial position of the current root system voxel grid and the spatial position of the adjacent root system voxel grid to obtain the edge of the root system voxel graph, and the weight of the root system voxel graph is obtained by constructing a point cloud search space and obtaining the point cloud density in the point cloud search space; based on the root system voxel graph, constructing a root system voxel spanning tree, judging noise in the root system voxel graph according to the root system voxel spanning tree, and filtering to obtain an initial root system skeleton graph; acquiring root system connection data of the current root system voxel grid, and filtering the root system voxel grid corresponding to the burrs through judgment to obtain a root system skeleton diagram. According to the method, skeleton extraction is performed from the point cloud data, skeleton misjudgment is reduced, and the problems of smear, noisy points, burrs and the like on the surface of a root system are solved.

The invention belongs to the technical field of optical engineering, and discloses a tree real skeleton point extraction method and system based on a deep neural network and a minimum spanning tree algorithm, a terminal and a storage medium, and the method comprises the steps: obtaining original point cloud data; predicting the original point cloud data based on a deep neural network, and obtaining the vector, radius and category information of each point cloud; performing centralization processing on the original point cloud data according to the vector, radius and category information of each point cloud, and performing initial skeleton extraction by using a minimum spanning tree algorithm to obtain initial skeleton points; simplifying and smoothing the initial skeleton point, and updating to obtain a real skeleton point based on a real skeleton point updating method of Euclidean clustering; and outputting the real skeleton point. The tree real skeleton point extraction precision is improved, and the reconstruction precision of the tree model is improved.

The invention relates to the technical field of big data management, in particular to a data tracing method based on big data mining, which comprises the following steps of: acquiring an unstructured operation log, analyzing the unstructured operation log into a structured event record, and associating to generate a heterogeneous operation session set; performing access mode association analysis on the session set to extract a read-write path mode, and combining association strength and a time decay factor to determine a dependency weight and construct a blood relationship map; eliminating a loop of the graph to generate a directed acyclic graph, constructing a spanning tree serving as a retrieval trunk and a node index coding interval, and mapping a cross-branch associated edge to a bitmap index to generate a probability skeleton tree index; and positioning a trunk path by using the interval, calling a bitmap to perform multi-path verification, and outputting a traceability path and confidence. A probability consanguinity map and a probability skeleton tree index are constructed through mining logs, and data consanguinity reconstruction and large-scale node low-delay retrieval in the heterogeneous black box environment are achieved.

The embodiment of the invention provides a transmission instance generation method, communication equipment, a communication system, a computer storage medium and a computer program product. The transmission instance generation method comprises the following steps: determining assigned nodes and non-assigned nodes in a leaf node set of the current depth of a first random number spanning tree, and when the current depth is expanded to the next depth, assigning all child nodes of the assigned nodes, at least one random value, corresponding to the second random number generation tree, of the next depth is adopted to carry out value assignment on part of child nodes in the non-assigned nodes, and the first random number generation tree and the second random number generation tree have the same fork tree structure; updating the leaf node set of the next depth to the leaf node set of the current depth; and when the current depth reaches the preset depth of the first random number generation tree, outputting a corresponding random value from the assigned node in the leaf node set of the current depth as decoding information of the transmission instance.

The invention discloses a topological communication coverage path planning method and system of an unmanned ship cluster for wide-area target search and detection, and belongs to the technical field of multi-agent collaborative path planning. According to the method, turning frequency optimization is converted into a minimum rectangular coverage problem, an integer programming model is established, a layered relaxation integer programming acceleration strategy based on maximum extension candidates is proposed, and the bottleneck of model expansion and calculation efficiency caused by candidate solution space explosion in a large-scale scene is broken through; then, constructing a rectangular topological connected graph, designing an improved spectral clustering algorithm fusing load balancing constraint and subgraph connectivity guarantee, realizing efficient and balanced distribution of regions in a complex environment, and ensuring internal connectivity of subregions; and finally, providing a dynamic pruning optimization method for the minimum corner spanning tree based on strong and weak connection characteristics, iteratively evaluating the corner cost and removing redundant edges, and finally generating a coverage path spanning tree with the minimum corner cost, thereby providing an accurate and efficient full-coverage operation path for scenes such as regional exploration and environment monitoring.

The invention belongs to the technical field of intelligent power distribution networks, distributed energy management and energy internet, and particularly relates to a transformer area micro-grid mutual aid regulation and control operation method and system considering a flexible interconnection device and topology flexibility. Acquiring basic data; constructing a node power flow balance model containing a flexible interconnection device, taking energy storage of each transformer area as an independent regulation and control unit, and establishing an energy storage operation model in combination with charge state constraint, capacity limitation, charge and discharge mutual exclusion and life constraint; virtual commodity flow constraints and spanning tree structure constraints are introduced, and a radiation type topology model capable of being dynamically switched is constructed; constructing a comprehensive optimization model, and solving by utilizing power flow-topology-energy storage coupling constraint to obtain a multi-transformer-area global optimal scheduling scheme; and outputting an optimal topological structure, a flexible interconnection device power instruction and an energy storage charging and discharging scheme. According to the invention, a traditional fixed topology and isolated energy storage scheduling mode is broken through, a unified optimization mechanism of power flow-topology-energy storage linkage is established, and active and flexible operation of the power distribution network is realized.

The invention discloses a whole wind network wind volume deduction method based on limited actual measurement wind volume and a topological structure, and relates to the technical field of wind volume deduction. The relation between the spanning tree air volume and the residual tree string air volume is obtained; the ratio of the number of independent loops to the number of total branches in the mine ventilation network is 1 / 3; establishing a maximum air volume residual tree string model and a minimum air volume residual tree string model; a corresponding minimum air volume spanning tree and a corresponding maximum air volume spanning tree are obtained; respectively putting known air volumes into the maximum remainder tree string, the minimum remainder tree string or the maximum spanning tree and the minimum spanning tree to construct four air volume deduction models; and solving the deduction model by adopting an FLA optimization algorithm, and outputting the air volume of each branch of the whole wind network. According to the method, through air volume adjustment and global optimization deduction, the air volume of the whole mine ventilation network is deduced rapidly and accurately, the air volume monitoring defect in the prior art can be effectively overcome, and more accurate and timely mine air volume state sensing is provided.

The invention discloses a multi-level two-state content management method and system based on an unreal engine, and the method comprises the steps: defining a level identification rule, employing a point separator to represent the father-son relationship between levels, dynamically generating tree-shaped nodes based on the level identification, and enabling each node to have corresponding node information, the node information comprises a hierarchical identification character string or a GameTag identification state provided by an unreal engine, an activation state of a current node, a global state mark of a child node and a child node reference list; and generating or matching nodes step by step by recursively analyzing a hierarchical identification character string or a GameTag identification state provided by an unreal engine to form a complete tree hierarchical structure. According to the method and the system, efficient management and dynamic expansion of multi-level double-state contents are realized, cross-project multiplexing is supported, and the method and the system are suitable for digital twin application development in a complex service scene.

The invention discloses a weaponry damage simulation method, equipment, a medium and a product, and relates to the technical field of weaponry collision detection, and the method comprises the steps: building and hierarchically binding independent collision models (a collision surrounding body and an equivalent geometry) of weaponry functional parts, integrating physical attributes in the independent collision models, and carrying out the simulation of the damage of the weaponry. Therefore, collision detection and hit detection are carried out, and a local damage effect and an overall function failure effect are generated through a predefined hit effect spanning tree. According to the method, collision detection is refined to a functional component level, differential simulation of an internal damage effect is supported, physical attributes are integrated into simulation logic, and simulation authenticity is improved; penetration simulation of a complex multi-layer structure is supported, and the credibility of virtual battlefield training and experiments is improved; the damage effect is dynamically generated through the tree-shaped structure, linkage simulation of local details and overall performance is achieved, and therefore high-precision damage simulation of the weapon equipment component level is achieved.

The invention discloses a heterogeneous unmanned ship cooperative coverage path planning method based on obstacle density, and the method comprises the steps: introducing a spanning tree multi-constraint dynamic coupling weight function, comprehensively considering the maximum speed of each unmanned ship in a path planning process, and associating the maximum speed with the turning frequency and the density of surrounding obstacles. According to the method, the collaboration efficiency can be improved, the task completion time is shortened, and resource waste is avoided.

The invention discloses a radial power distribution network topology identification method, system and device and a medium. The method comprises the following steps: acquiring node voltage amplitude measurement data; calculating a sample covariance matrix based on the voltage amplitude measurement data to obtain the covariance of the voltage amplitude between the nodes; estimating a precision matrix of the covariance matrix through a graph lasso model; calculating a partial correlation matrix based on the precision matrix, wherein the partial correlation matrix is used for representing a direct correlation coefficient between nodes in the radial power distribution network; and deriving an adjacent matrix through a maximum spanning tree based on the partial correlation matrix to obtain a radial power distribution network topological structure. According to the method, sparse learning and partial correlation analysis are combined to deal with the problem of limited data volume; the key condition dependency relationship between the nodes can be quickly and accurately identified only through voltage amplitude measurement data without a large number of samples and phase angle information, and the identification precision is high.

The invention provides a clustering method and system based on complex entropy and a complex information hierarchy construction method, and the method comprises the steps: initializing the features of elements in a first category, calculating the centroid of the category based on the initialized elements, and calculating the similarity based on the centroid of the first category to obtain a first combined category, if the number of the first merging categories is larger than or equal to a first preset value, a first entropy value is calculated through complex entropy, the first entropy value is obtained through similarity difference calculation, clustering results are generated based on the first entropy value, the clustering results at least comprise a first clustering result and a second clustering result, and the clustering results are of a tree structure. According to the method, a tree-shaped clustering result is generated according to complex entropy calculation, and similar questions are aggregated, so that the problem of low accuracy of answering complex questions is solved.

The invention discloses a global optimization defect skeleton extraction system and method based on an energy function, and the system comprises a refining module, a node and branch extraction module, an energy calculation module, a graph construction and maximum spanning tree pruning module, and a skeleton reconstruction module. A morphological refinement algorithm is applied to the binary region to generate a preliminary skeleton, and the node and branch extraction module is used for calculating 8-neighborhood connectivity of each pixel on the skeleton; the energy calculation module calculates normalized features of each branch; the graph construction and maximum spanning tree pruning module obtains a global optimal skeleton structure based on the normalized features; and the skeleton reconstruction module generates a final pruning skeleton according to edges reserved in the global optimal skeleton structure, so that the trunk trend of the defect area can be reserved, pseudo branches can be effectively removed, and the accuracy and stability of skeleton extraction can be improved.

The invention provides a ship pollution accident risk assessment method and system based on machine learning, and relates to the technical field of ship pollution control, and the method comprises the steps: extracting a ship pollution accident report, extracting potential impact factors, and dividing the ship pollution accident report into light, medium and heavy pollution levels; the potential influence factors comprise multi-dimensional factors of personnel, ships, environments and management; constructing a pollution level regression model, and screening out key influence factors; constructing a pollution level prediction model, constructing a maximum weight spanning tree through mutual information values to determine a dependency relationship between factors, determining conditional probability distribution based on a statistical method, and realizing prediction of the pollution level; based on a sensitivity analysis method, quantifying the global sensitivity index of each factor to the pollution level, and identifying a key influence factor with relatively high global sensitivity; based on the bidirectional reasoning capability of the Bayesian network, inputting key influence factors to predict pollution level probability distribution, and deducing a specified pollution level to obtain a key influence factor combination;

The invention provides a low-code and component intelligent collaborative application construction method based on a dual-drive architecture, and belongs to the technical field of computer programming. The method comprises the following steps: establishing a component dependency digraph, optimizing a component collaborative relationship by adopting topological sorting, graph coloring and a minimum spanning tree algorithm, collecting multi-dimensional performance indexes to establish a monitoring matrix, processing monitoring data by utilizing a collaborative optimization model containing a gating information propagation mechanism, and generating a dynamic scheduling decision vector; the load change of the system is judged through a change rate threshold equation, quick or slow response adjustment is executed, and finally, a low-code component library and a visual configuration interface are established to realize intelligent collaboration and dynamic resource allocation among components. The technical problems that the collaboration efficiency among low-code platform components is low and intelligent dynamic scheduling cannot be achieved according to system load changes are solved.

The invention discloses an analog integrated circuit wiring method and system, electronic equipment and a storage medium, and the method comprises the steps: obtaining a preset net, and generating a minimum spanning tree according to the preset net; wherein the minimum spanning tree comprises a plurality of preset pin areas; determining pin priority data corresponding to the preset pin area according to a preset sorting mechanism; wherein the preset sorting mechanism is determined through a Manhattan distance algorithm; performing wiring planning through a mode wiring algorithm according to the pin priority data and the minimum spanning tree to obtain preset wiring data; performing design rule inspection on the preset wiring data to obtain an inspection result; and when it is determined that the inspection result is passed, generating a target wiring file according to preset wiring data. According to the embodiment of the invention, the wiring efficiency and quality of the analog integrated circuit can be effectively improved, so that the performance and reliability of the analog integrated circuit are improved. The circuit can be widely applied to the technical field of integrated circuits.

A method for providing secure and hierarchical access to an object record includes generating a tree data record including a root node data record and a multiple dependent node data records. The method further include receiving a request to perform an action on the object record. The method further includes determining the first dependent node data record based on the user account being assigned to the first dependent node data record and determining the second dependent node data record based on the second dependent node data record depending from the first dependent node data record. The method further includes determining the at least one node tag of the object record is associated with at least one of the first dependent node data record or the second dependent node data record. The method further includes executing the action on the object record.

The rumor detection method based on the information propagation structure comprises the following steps: constructing a tweet propagation tree by social network data according to a forwarding relationship; converting the propagation tree into a user forwarding sub-graph through a node replacement strategy, and constructing a global user forwarding network through node merging and edge attribute fusion; respectively extracting local and global structure features of the user forwarding and pushing network by using a deep walk spanning tree algorithm and a WL algorithm, and splicing the local and global structure features to obtain a complete structure code; meanwhile, tweet content features are extracted through a pre-trained large language model to obtain content codes, position code information on a user forwarding and pushing network is calculated through algorithms such as a Laplacian matrix and intimacy sorting, and then the corresponding codes are spliced and input into a Graph Transform model to capture association between the features and the authenticity of propagation tweet. And finally, judging whether the tweet is a rumor or not by using an MLP classifier. And an efficient and reliable solution is provided for rumor detection in the social network.

The present invention is applicable to the field of smart grid technology and relates to a method for identifying the physical topology of distribution network substations based on G3-PLC communication characteristics, including: S10, constructing a physical topology model of the distribution network substation; S20, determining edge weights in the physical topology model of the distribution network substation; S30, improving the Prim algorithm based on the G3-PLC communication characteristics and constraining the minimum spanning tree (MST) to improve the Prim algorithm process; and S40, identifying the physical topology structure of the distribution network substation. This method has a simple process and is easy to operate. Without adding additional hardware equipment or any manual operation, it constructs a weighted graph using G3-PLC communication data, generates a minimum spanning tree (MST) using the Prim algorithm, and identifies the physical topology structure of the distribution network substation with high identification accuracy.

A network device of a virtual switch, which includes a second network device and operates on a unified control plane, is provided. During operation, the network device maintains a link between its first port and a second port of the second network device. Here, the first link can be distinct from a second link used for exchanging data traffic of the virtual switch. The network device operates a spanning tree protocol to place the first and second ports in respective port states, which include a forwarding state and a blocked state. If the second link becomes unavailable, the network device determines that the virtual switch has split into a first segment comprising the network device and a second segment comprising the second network device. If the first port state is in the blocked state, the network device suspends communication via a respective port of the first segment.

Techniques and architecture are described for a method that includes an in network compute (INC) manager receiving from switches of a fat tree configured network, arithmetic logic unit (ALU) capacity of the switches. Based at least in part on the ALU capacity of the switches and bandwidth, the INC manager determines one or more switches within each tier that are capable of supporting the processing units and based at least in part on the determining, the INC manager selects a first switch as a root, wherein the first switch is included within a tier of switches having intermediate tiers of switches located between the tier and the plurality of processing units within the fat tree configured network. The INC manager creates one or more paths of switches within each of the intermediate tiers from the root to the plurality of processing units to provide a constrained disjoint spanning tree of switches.

The invention relates to the technical field of rich text processing display, in particular to a method for processing rich text highlighting through list display under a Harmony Next App, which comprises the following steps of: firstly, obtaining rich text contents containing HTML (Hypertext Markup Language) format tags, analyzing the rich text through modes such as regular expression matching, generating node data of a tree structure, and introducing a dynamic weight distribution algorithm to optimize tag analysis priority; and reducing redundant data by using a node similarity merging algorithm. Based on node data, a Harmony OS native component is used for carrying out fine-grained rendering, according to business logic or keywords input by a user, font color attributes of a Span component are dynamically adjusted, highlight display is achieved, and a style and rendering logic are decoupled to flexibly configure a highlight strategy. According to the method, a pre-analysis and caching mechanism, lightweight rendering and other strategies are adopted to optimize the performance, and the method is suitable for various scenes such as rich text search keyword highlighting, specific field style emphasizing and multi-theme switching real-time style adaptation.

The invention provides a tree crown three-dimensional reconstruction method and system based on multi-scale feature fusion, and the method comprises the steps: firstly collecting a tree crown collection data set which comprises laser radar scanning point cloud data, multispectral image data and ambient light field distribution data, and then carrying out the multi-scale feature extraction of the tree crown collection data set; a tree crown point cloud local structure feature, a multispectral image spectral reflection feature and an ambient light field illumination attenuation feature are obtained, then a feature fusion network is used for carrying out dynamic weight distribution fusion on the features, and a tree crown multi-scale fusion feature is generated. Training a three-dimensional reconstruction model based on the features to generate a crown three-dimensional grid model, finally calling the crown three-dimensional grid model to perform three-dimensional reconstruction on real-time acquired data of a target crown, and outputting a dynamic three-dimensional model of the target crown and a structure parameter optimization suggestion, so as to obtain a dynamic three-dimensional model of the target crown through multi-scale feature fusion. And the three-dimensional reconstruction of the tree crown can be realized more accurately and optimization suggestions can be given.

The invention discloses a tree dynamic coding method and system based on high-precision positioning and visual analysis. The method comprises the following steps: acquiring pose data and an image; calculating geographic coordinates of the tree; preprocessing the image; extracting tree ontology features and environmental reference features, and establishing a corresponding relationship between the two features; determining whether the tree is a coded tree or not based on the geographic coordinates of the tree, the tree ontology characteristics and the environmental reference object characteristics; if not, an identity code of the tree is generated, and the identity code of the tree comprises a basic code and a dynamic extension code; the basic codes comprise codes corresponding to geographic coordinates and serial numbers; the dynamic extension code comprises a state code used for representing the current operation and maintenance state of the tree and a version code used for recording the number of updating times of the robust template. By implementing the method provided by the invention, the stable, unique and traceable digital identity of the single tree in the whole life cycle can be established, and the defects of the existing method in the aspects of reliability, uniqueness and long-term continuity are overcome.