1660 results about "Tree based" patented technology

The invention provides a forest land tree height measurement and determination method and system based on laser radar point cloud data. Stress wave signals are collected based on a trunk base acoustic emission sensor array to generate an acoustic characteristic parameter set, the digital twin model is driven to complete forest stand structure topological optimization, and a three-dimensional growth vector model reflecting the internal mechanical state of a trunk is formed. And synchronously fusing high-precision slope point cloud data returned by the unmanned aerial vehicle laser radar in real time, correcting a terrain distortion error through a dynamic splicing algorithm in combination with stress distribution characteristics, and generating a crown segmentation boundary constrained by physical characteristics. And finally outputting a tree height parameter corrected by the abrupt slope topography through model iterative optimization and space vector analysis. According to the technical scheme, synchronous sensing of the three-dimensional shape and the mechanical state of the tree in the complex terrain environment is achieved, and the tree height measurement error is reduced.

The invention provides an RAG knowledge base construction method and system based on hierarchical semantic indexes. The method belongs to the cross technical field of artificial intelligence and information retrieval. The method comprises the following steps: performing multi-level semantic analysis on an input original document set to generate document semantic hierarchical structure data; constructing a hierarchical semantic index tree based on the document semantic hierarchical structure data; performing dynamic knowledge graph initialization according to the hierarchical semantic index tree to generate an initial dynamic cognitive graph; and collecting real-time interaction data through a user feedback interface and a new data access module, and performing incremental updating on the initial dynamic cognitive map to form a knowledge representation system supporting life cycle evolution. Through multi-level semantic analysis and construction of a hierarchical semantic index tree (HSIT), deep semantic analysis can be performed on an original document set, the context integrity of knowledge is ensured, structured storage is realized, the knowledge can be expressed and stored more accurately, and information loss or semantic ambiguity is avoided.

The invention relates to a tree neighbor context-based big language model RAG optimization method, which comprises the following steps of: reading a directory structure and content of a document, generating a corresponding directory tree, converting the directory tree into a Markdown format containing a title and a level, and automatically extracting according to a document template if no title exists; segmenting the document into knowledge blocks according to the priority; after the knowledge blocks are recalled, the context is expanded by using a tree adjacent context method, and a new knowledge block list is formed; grouping and sorting the expanded knowledge blocks according to document identifiers, splicing reference data based on different fields and confidence coefficients, and generating a character string set from the original document; and splicing prompt words by using the constructed reference data and the new knowledge block list, and sending the spliced prompt words to the large model for processing. According to the scheme, the performance and practicability of the large model in the information retrieval and answer generation process are comprehensively enhanced by optimizing context information, emphasizing key content, adapting to various document formats, improving user experience and the like.

The invention discloses a large model reasoning method and system based on tree diagram and knowledge graph retrieval enhancement, and the method comprises the steps: segmenting a document into text blocks, recognizing the entities, relationships and factual descriptions of the text blocks, and forming a knowledge graph of the text blocks; constructing a factual summary of the documents based on the knowledge graph of the text blocks, and performing clustering recursion on all the documents by using a Gaussian mixture model to generate a similarity tree structure graph; the method comprises the following steps: obtaining a user problem, selecting a reasoning path from a similarity tree structure diagram through a large language model debate iteration method, obtaining a corresponding document cluster, pruning the cluster based on the user problem and a confidence score of a document, selecting a plurality of text blocks from the pruned document, and finally obtaining a knowledge graph based on the selected text blocks. And generating a reasoning result. The invention relates to the technical field of natural language processing, can realize retrieval enhancement based on a tree diagram and a knowledge graph, and accurately queries related information when a large model answers a complex multi-hop question, so that the reasoning accuracy is effectively ensured.

A computing system assists in large language model system assisted investigations. The computing system includes network connection hardware configured to connect to a large language model and configured provide to investigation context and investigation goals to the large language model system. The network connection receives from the large language model system, an indication of suggested steps to perform in an investigation, including specific computer executable code to perform a skill in the first step, the skill comprising a supplemental access, analytic or enrichment function. The computing system includes a user interface with a tree interface that causes display of the indication of the suggested steps in a tree format. The computing system is configured to execute the computer executable code to cause the computer system to perform the supplemental access, analytic or enrichment function.

An example system and method that can provide integrity and privacy-preserving communication and integrated operation in smart factory and other IOT applications using smart contracts in blockchain and Merkle Tree-based key management operations. The exemplary Merkle tree-based key management can ensure all communication, control operations, and shared models (e.g., Federated Learning models) are encrypted prior to transmission and sharing with other nodes in the network, with keys being split into parts to each of multiple recipients and later assembled to allow blocking consensus / validation to be performed.

The invention discloses a crowded automatic warehouse multi-AGV path planning method based on a conflict search algorithm. The method comprises the following steps: constructing a grid map model of an environment where AGVs are located; at the bottom layer of the conflict search algorithm, AGV environment information is obtained according to the grid map model, and a path solution of the AGV and conflict information carried by the path are obtained by using an A * algorithm; according to the top layer of the conflict search algorithm, an improved constraint tree is constructed according to the obtained AGV path solution and conflict information, a node with the minimum loss is selected in the constraint tree for conflict detection, planning succeeds if no conflict exists, corresponding constraints are applied to conflicting AGVs if conflicts exist, and the whole process is circulated till planning succeeds. According to the method, the searching process of corridor conflicts is simplified, the driving direction allowed by the corridor is adaptively determined through searching, the planning process is accelerated by introducing the conflict priority and bypassing the conflicts, the planning time and the quality of a path solution can be considered as much as possible, and the working efficiency of the AGV is effectively improved.

The invention discloses a forest carbon reserve and carbon sink monitoring and evaluating method based on a multi-source remote sensing technology. The method comprises the following steps: multi-source remote sensing data acquisition: respectively acquiring optical remote sensing data and radar remote sensing data; tree species classification and identification: carrying out tree species classification on the forest in the research area to realize tree species scale space distribution information extraction; for different tree species, biomass model parameters obtained through field investigation are combined, a biomass estimation model based on the tree species is established, model input parameters are biomass model parameters, and vegetation biomass is output; calculating the carbon reserve: calculating the vegetation carbon reserve by utilizing the inverted vegetation biomass and combining the carbon content coefficients of different tree species; estimating the soil carbon reserve, and finally obtaining the total carbon reserve of the forest ecosystem: calculating the carbon reserve variation of the forest ecosystem at different time points based on the multi-source remote sensing data of the long-term sequence. According to the invention, large-range, high-precision and continuous forest carbon reserve and carbon sink monitoring and evaluation considering tree species difference is realized.

The embodiment of the invention provides an information mapping method for intelligent perception information in a virtual space, perception data is acquired by deploying a multi-sensor array, data features are extracted based on a multi-scale feature pyramid and an attention mechanism, and a space mapping relation is established by using self-supervised learning and geometric constraints. Local data blocks are organized by adopting a hierarchical index tree based on a union search set, an adaptive calculation flow graph is constructed to realize efficient mapping, and data transmission is optimized in combination with predictive caching and a differential updating strategy. And meanwhile, parallel processing of incremental mapping is realized through a pipeline data channel, and the data synchronization efficiency is ensured by a dynamic scheduling mechanism based on load prediction. The method effectively solves the problem of performance bottleneck when a traditional mapping scheme processes large-scale multi-source sensing data.

The invention relates to the technical field of artificial intelligence, and provides a webpage action execution method and device, electronic equipment and a storage medium, and the method comprises the following steps: determining a function node tree based on a page function structured analysis result, and carrying out semantic matching on a task target vector corresponding to a task text and a function description vector to obtain a candidate operation path; executing a webpage action based on the candidate operation path and the matching degree sequence corresponding to the candidate operation path, when a state verification result corresponding to the webpage action is that verification is not passed, performing path backtracking on the function node tree to obtain an operation path, executing the webpage action based on the operation path, and when an execution result corresponding to the webpage action is that verification is passed, performing path backtracking on the function node tree to obtain the operation path. And displaying the execution result of the webpage action. The function node tree is determined based on the page function structured analysis result, complex hierarchical operation is effectively processed, the operation path is obtained based on semantic matching of the task target vector and the function description vector, and the accuracy of page state tracking corresponding to the operation path is improved.

A method includes extracting, by one or more processors, tags from free-text sequence of operations information for a building controller, identifying, by the one or more processors, nodes of a selection tree based on the extracted tags, selecting, using the selection tree and based on the nodes, a plurality of controller code modules, installing, on a building controller, a control application comprising the plurality of controller code modules, and controlling, by the building controller, building equipment using the control application.

The invention provides a sparse matrix distributed solution method, computer equipment and a storage medium, which are used for simulation of a circuit and an electromagnetic field, and the method comprises the following steps: generating a super node based on an elimination tree of a matrix generated in a simulation process; constructing an assembly tree according to the elimination tree and the super nodes; constructing a wavefront matrix according to the rows and columns of the matrix corresponding to the super nodes; traversing the assembly tree layer by layer, and carrying out parallel calculation on complete assembly blocks and incomplete assembly blocks of the wavefront matrix on the same layer of the assembly tree; according to the incomplete assembly blocks of each layer, the complete assembly blocks of the next layer of the assembly tree are updated until the last layer of the assembly tree is reached; and ending the traversal of the assembly tree, and solving an equation LUx = b by using the complete assembly blocks of all the wavefront matrixes. According to the scheme, the solving speed can be greatly improved, memory occupation is reduced, and simulation of a circuit and an electromagnetic field is facilitated.

The invention provides a script preservation method which can be applied to the technical field of artificial intelligence. The script preservation method comprises the following steps: carrying out semantic understanding on demand related files by utilizing a large model, extracting core elements, and generating a structured demand change list; analyzing to obtain an abstract syntax tree of an existing script code, and constructing a mapping relationship between the software automation test element and a script code block; dynamically comparing the structured demand change list with an existing script code structure tree based on a mapping relation between software automation test elements and script code blocks, identifying a script range influenced by demand change, and outputting a change influence matrix; and based on the change influence matrix, generating an automatic script code snippet needing to be updated, and realizing preservation of the automatic script. The invention further provides a script preservation device and equipment, a storage medium and a program product.

The invention relates to an optimization method and device for large-scale graph data visual rendering and a storage medium, and the method comprises the steps: obtaining to-be-rendered graph data, constructing an R-tree spatial index according to the to-be-rendered graph data, and constructing a self-adaptive fragmentation model based on an R-tree data structure; monitoring interaction data of a user in real time, performing viewport prediction according to the interaction data, and determining a to-be-loaded sub-graph according to a prediction result and the adaptive fragmentation model; the method comprises the following steps: acquiring system data of client equipment, analyzing the performance of the client equipment according to the system data, and determining a rendering strategy according to a performance analysis result; and performing off-screen rendering on the to-be-loaded sub-graph according to the rendering strategy, and displaying an off-screen rendering result on the client device after detecting that the user completes the corresponding operation. According to the method, the rendering granularity is dynamically adjusted through the adaptive fragmentation model, and the rendering quality and performance consumption are balanced; the user interaction intention is pre-judged through a viewport prediction algorithm, and window smooth switching is achieved in combination with off-screen rendering.

The invention discloses an AI-based intrusion protection response data processing method and a server, which can analyze a code of an SQL (Structured Query Language) instruction by collecting the code of the SQL instruction and utilizing a data processing and semantic comprehension algorithm based on artificial intelligence and deep learning. According to the method, abstract syntax tree semantic embedding representation of SQL instruction codes is captured and depicted, filtering is carried out on the basis of association information between node embedding semantics in the embedding representation, and node embedding semantics with higher semantic expression quality are purified to replace original nodes. Then, SQL code semantic coding based on a tree-shaped long-short-term memory network is carried out on the semantic embedded representation of the abstract syntax tree subjected to filtering and purification processing, so that accurate recognition and detection of SQL injection vulnerabilities are achieved by enhancing the structured dependency relationship among words in SQL instruction codes. Therefore, intrusion protection response data processing can be performed more intelligently, and automatic identification and detection of SQL injection attacks are facilitated, so that the problem of horse hanging is solved from the source, and the security of a website is enhanced.

The invention discloses a patent data analysis method based on a dynamic context window, which belongs to the technical field of text data analysis, and comprises the following steps: extracting domain features to obtain a query quantity q; sorting the patent documents d based on the similarity between the patent documents d and the query quantity q; splitting the patent document into minimum semantic units according to a sorting sequence by using a recursive partitioning algorithm, and keeping a document structure by using a local alignment algorithm and a hierarchical reduction algorithm; performing feature extraction; carrying out soft clustering in combination with the technical field feature weight and the technical relevancy; calculating and storing technical association probabilities among the fragments; establishing a quick retrieval tree based on the established serial numbers; and dynamically adjusting the size of a context window for the obtained core fragments according to the importance of the document, and expanding the context. According to the patent data analysis method based on the dynamic context window, the problem that the analysis effect is poor due to the fact that an existing patent data analysis mode is limited by an upper window and a lower window is solved.

The invention provides a distributed network data integrity verification method and device based on a block chain. The method comprises the steps that original data is divided into m data blocks, each data block comprises n data units, the initial hash value of each data block is calculated, and the initial hash value is uploaded to a block chain network; uploading the data block to be verified to the block chain network, and recalculating the hash value of the data block; preliminarily verifying the integrity of each data block according to the determined verification parameter and a preset threshold value, and judging whether the data block meets a preliminary integrity condition or not; for the data blocks meeting the preliminary integrity condition, constructing a ternary tree according to the hash value of each data unit; judging whether the data in the data block meets a complete condition or not; and when all the segmented data blocks meet a complete integrity condition, judging that the original data is complete. The problems that a traditional data integrity verification method is low in efficiency and prone to being attacked are effectively solved.

To automatically generate an FTA real-time dynamic tree based on a fault knowledge base.SOLUTION: In step 1, an FTA logic model is newly constructed by a method for generating an FTA real-time dynamic tree based on a fault knowledge base. In step 2, a fault knowledge base model is selected based on a logical device. In step 3, a fault library is constructed based on the FTA logic model to generate a logic rule for an FTA model, and the fault knowledge base model is processed to perform decomposition-mapping into an FTA logic fault tree model. In step 4, the fault diagnosis tool for the event node is set. In step 5, a formation of an FTA logic fault tree is completed. In step 6, the FTA logic model is published, and the FTA logic model is instantiated. In step 7, a scheduling task is configured. In step 8, the configured scheduling task performs a periodic fault diagnosis and issues a fault alarm.SELECTED DRAWING: Figure 1

The invention relates to the technical field of power systems, in particular to a power transmission line tree obstacle hidden danger detection method and system considering the wind deflection influence and a medium, and the method comprises the steps: carrying out the tree growth prediction according to an original multi-source data set, and obtaining a tree growth prediction result; performing three-dimensional windage yaw effect analysis based on the tree growth prediction result and the original multi-source data set to obtain a tree windage yaw quantification result; respectively calculating the risk time of the tree in the vertical direction, the horizontal direction and the inclined direction according to the tree windage yaw quantification result; evaluating a comprehensive risk index between the tree and the power transmission line according to the risk time to obtain a tree barrier hidden danger degree; and taking minimization of the total pruning amount and maximization of the safety margin as optimization objectives, generating a tree pruning strategy based on the hazard degree of the tree obstacle hidden danger, and pruning the risk trees of the power transmission line according to the tree pruning strategy. According to the method, tree growth prediction and windage yaw effect quantification are carried out by fusing multi-source data, and the power transmission line fault risk caused by tree obstacles is effectively reduced.

The invention relates to the technical field of electronic digital data processing, in particular to an operation state monitoring method and system for injection molding equipment, and the method comprises the steps: collecting a multi-dimensional operation parameter time sequence of the injection molding equipment at different moments, collecting parameters of the same dimension into data sets, and constructing an isolated tree based on each data set; after sorting tree nodes of the isolated tree according to a data average value, distributing a tree node sequence number for each item of data; the combination of the dimension parameters at the same moment is regarded as a data point, the distribution relation of any two data points on the isolated tree is compared, the same-group degree of the data points is calculated, and the data points with the same-group degree higher than a set threshold value are classified into the same group; calculating the abnormal degree of the data points; and if the abnormal degree exceeds a set threshold value, determining that the data point is an abnormal data point and giving an alarm at the same time. The problem that the accuracy and reliability of state detection are not high is solved.

A computer system and method for financial management and estate planning. The system provides data aggregation for both financial and non-financial assets to create a “virtual vault” from which the owner can view all information about his / her portfolio. In some embodiments, the system provides a tree visualization of the portfolio, which allows a structured organization that provides both a high level view and the ability to drill down to an in-depth analysis. In some cases, the system provides segmented permissions in which restricted access could be granted based on module and / or asset in the tree visualization.

The invention relates to an input data quality evaluation method for photoetching process window analysis. The method comprises the following steps: S1, obtaining standardized data; s2, adopting an RANSAC regression algorithm to obtain a robust regression residual analysis confidence coefficient; s3, obtaining the confidence of the isolation tree based on the abnormal score of the isolation tree; s4, adopting a local outlier factor method to obtain local outlier factor confidence; s5, integrating the isolation tree confidence coefficient and the local outlier factor confidence coefficient to obtain an unsupervised confidence coefficient; s6, obtaining a Gaussian confidence coefficient; and S7, integrating the robust regression residual analysis confidence coefficient, the unsupervised confidence coefficient and the Gaussian confidence coefficient to obtain a comprehensive confidence coefficient, and obtaining an input data quality evaluation result for photoetching process window analysis. Compared with the prior art, the method has the advantages of improving the input data quality of photoetching process window analysis and the like.

The invention discloses an operation and maintenance fault processing method and device based on a large model and a knowledge graph, equipment and a medium, and relates to the field of operation and maintenance fault diagnosis processing, and the method comprises the steps: constructing an operation and maintenance fault processing domain ontology, and inputting historical operation and maintenance fault information and the operation and maintenance fault processing domain ontology into a preset large model to obtain a target triple, obtaining an operation and maintenance fault processing knowledge graph based on the target triple; performing dependency syntactic analysis on the historical operation and maintenance fault information to obtain a dependency syntactic tree, processing the dependency syntactic tree based on the operation and maintenance fault processing knowledge graph to obtain a first dependency syntactic tree, and obtaining a fault processing question and answer template library by using the first dependency syntactic tree; determining a second dependency syntax tree based on the operation and maintenance fault information to be processed, determining a question and answer template corresponding to the second dependency syntax tree from a question and answer template library, and instantiating the question and answer template to obtain a semantic query graph; and determining a target sub-graph corresponding to the semantic query graph from the knowledge graph, and obtaining an operation and maintenance fault processing result based on the target sub-graph.

The invention discloses a policy service recommendation method and system based on a large language model, and relates to the field of policy information, and the method comprises the steps: analyzing a policy file, extracting policy terms with a numbering structure, building a unique identifier, and forming a term node set; identifying explicit or implicit reference behaviors in terms, constructing a reference path, and generating a reference directed graph; constructing a clause mapping tree based on the target clauses; mapping tree nodes are extracted to form structured prompt information, and the structured prompt information is embedded into large language model input; generating a policy report paragraph containing clause reference content; and outputting the structured policy text with clause reference chain closure and recommending the structured policy text to the user. According to the method, the clear reference context combined with the user information can be provided for the large language model, the large language model is guided to generate a text with a reasonable structure and complete terms for recommendation, and the problem of inaccurate generation when an existing model processes a complex reference structure is solved.

The invention provides a single tree segmentation-biological parameter estimation method based on a vehicle-mounted LiDAR point cloud, and belongs to the technical field of urban landscaping intelligent monitoring. The point cloud individual tree segmentation algorithm based on tree geometric feature constraint is designed for solving the problem that individual tree segmentation is difficult due to crown overlapping in an urban scene, and the method takes a tree geometric structure as a constraint, combines point cloud reflection intensity information, a clustering algorithm, a main direction index and other means, and obtains the individual tree segmentation algorithm based on the tree geometric feature constraint. And accurate extraction of trunks and crowns in the scene point cloud is realized. Aiming at the problems of high feature redundancy, poor model interpretability and the like in an existing estimation method, a random forest model is taken as a basis, an adaptive feature selection algorithm is introduced to improve variable screening efficiency, hyper-parameters are dynamically adjusted by utilizing pigeon inspired optimization, and generalization and stability of the model are enhanced; an estimation model used for estimating biological parameters such as leaf area index, biomass and carbon reserve is designed.

The invention provides a building instantiation segmentation method and device, a terminal and a storage medium, and relates to the technical field of three-dimensional point cloud processing, and the method comprises the steps: carrying out the plane segmentation of a building point cloud of a target building, and extracting a potential vertical plane point cluster from a building plane point cluster obtained through the segmentation; mapping all three-dimensional point clouds in the potential vertical plane point cluster to a two-dimensional feature space to obtain a two-dimensional point set, and processing the two-dimensional point set by using a preset dual-threshold judgment mechanism to extract a building vertical structure point cluster; generating a building distance map based on the building vertical structure point clusters, and generating instance anchor points on the distance map; extracting a multi-level contour in the distance map based on the instance anchor points, constructing a tree-shaped hierarchical relationship corresponding to the multi-level contour, and constructing a mark matrix based on the tree-shaped hierarchical relationship; and building two-dimensional instantiation segmentation is carried out on the distance map based on the mark matrix. Through the unsupervised hierarchical segmentation framework, the dependence on the annotated data can be eliminated, and the segmentation precision is improved.

The embodiment of the invention provides an air-sea cross-domain communication method and device. The method comprises the following steps: fusing a multi-system communication protocol into a cross-domain communication network protocol through a water surface wireless communication multi-band access technology, and carrying out adaptive networking; the method comprises the following steps: performing dictionary table mapping on original information sent by underwater subsurface buoy sensor equipment to obtain a translated character sequence, constructing a Huffman tree according to the occurrence frequency of each character in the translated character sequence, and generating a Huffman code corresponding to each character according to the Huffman tree; the method comprises the following steps: monitoring channel noise and a channel error rate of an underwater acoustic channel in real time, determining a real-time channel state, determining a channel coding parameter adjustment strategy matched with the real-time channel state through an adaptive algorithm, and dynamically adjusting a coding mode and coding parameters of the channel according to the channel coding parameter adjustment strategy. Uploading the Huffman code to a superior command center through a preset dual channel according to the dynamically adjusted coding mode and coding parameters; according to the invention, the air-sea cross-domain communication efficiency can be effectively improved.

The invention discloses an automatic driving model and method based on end-to-end joint optimization, and particularly relates to the field of visual automatic driving, and the method comprises the following steps: processing an input image and a point cloud, and constructing instance features; static and dynamic interaction scene representations based on sparse instances are constructed through query and attention mechanisms; constructing a parallel prediction-planning module based on the tree structure; extracting time sequence information of a historical track to construct a probability space; and modeling and predicting a time sequence dependency relationship of the trajectory through a gating loop unit, and screening an optimal future trajectory by using a confidence score. According to the method, the dynamic feasibility and safety of the planned trajectory can be improved, meanwhile, the calculation overhead is reduced, and an efficient and robust solution is provided for actual landing of the automatic driving technology.

The invention provides a social network hierarchical visualization method and system based on a structure entropy and a coding tree, and the method comprises the steps: obtaining graph data, building the coding tree based on the graph data with the minimized structure entropy, and enabling the coding tree to be used for capturing a hierarchical community structure of a graph; constructing a minimum entropy priority queue, adaptively selecting non-leaf nodes for division by adopting the minimum entropy priority queue, and distributing a current structure entropy value as a weight for a cross-community edge; force-oriented layout based on structure entropy and layout entropy is used, attraction is adjusted based on edge weight, standard repulsive force is kept, and a force model is established; solving a layout entropy maximization target for the force model to calculate a layout result; and for the calculated layout result, outputting and rendering a layout result with a clear community separation effect as a final visualization result.

The invention relates to the technical field of data processing, in particular to an efficient transmission method for electric energy meter acquired data, which comprises the following steps: acquiring multi-dimensional feature data of an electric energy meter at each moment, and obtaining multi-dimensional real-time feature data at the current moment and a multi-dimensional historical feature data sequence within a preset historical time period; using an isolated forest algorithm to randomly select sample points to form at least one sample subset, for any sample subset, obtaining the abnormal degree of each sample point in any sample subset under each feature, obtaining a segmentation condition under each feature according to the abnormal degree, and generating an isolated tree; obtaining a normal weight of each path in the isolated tree according to fluctuation features of sample points in a sample subset corresponding to the isolated tree and differences between the sample points and the multi-dimensional real-time feature data; and the final score is obtained by using the normal weight of each path in each isolated tree, and the adjustment frequency is obtained according to the final score, so that the interference of non-system abnormal data such as noise on frequency adjustment is effectively reduced.