75 results about "Merge algorithm" patented technology

The invention belongs to the technical field of geometric pretreatment in computer aided engineering (CAE), and particularly relates to a dirty geometry restoration method for a complex three-dimensional geometric model, which comprises a dirty geometry detection and restoration module based on heuristic rules and geometric topology analysis. By means of a multi-model collaborative alignment and bonding mechanism, high-precision assembly between parts is achieved through geometric feature matching and adjacent domain self-adaptive adsorption; acquiring material attributes provided by the simulation platform, and performing accurate cutting and boundary reconstruction on an intersection domain based on an intersection domain intelligent segmentation algorithm of the material attributes to ensure correct mapping of boundary conditions of a physical field; a geometric Boolean processing engine iterative learning mechanism of a general merging algorithm is integrated, and a high-quality model for simulating a grid is generated through multi-round iterative optimization. According to the method, double challenges of internal dirty geometry of a single model and derivative dirty geometry of intersection / adjacent areas among multiple bodies are solved, and key physical attributes and topological continuity of electromagnetic signal links are ensured and are completely reserved during repair.

The invention belongs to the technical field of data processing, and particularly discloses a GIS data intelligent conversion processing method and device, electronic equipment, a medium and a program product, and the method comprises the steps: receiving an SHP format data file, processing a file name code, and screening effective files; traversing the SHP file, converting the SHP file into a DWG format, and classifying and outputting the SHP file according to rules; processing the DWG file in batches based on a CAD filling algorithm of a transaction mechanism, generating a filling layer and executing entity filling; the DWG files are merged in batches through a file merging algorithm, and views are automatically adjusted; and compressing, packaging and returning the combined file. According to the method, the full-process automatic conversion from the SHP to the DWG is realized, the problems of coding disorder, incomplete data, complicated operation and the like in the traditional processing are solved, and the conversion efficiency and the result accuracy are improved.

The invention discloses a zero-configuration knowledge graph construction method, equipment and a medium, belongs to the technical field of knowledge graphs, and aims to solve the technical problem of how to overcome the hard coding defect in traditional knowledge graph construction, realize a more flexible construction mode with lower difficulty in use, further realize data source entity association and semantic fusion and improve the knowledge graph construction efficiency. According to the technical scheme, field name semantic analysis and data content analysis are conducted through a dynamic semantic analysis algorithm, and intelligent database deep analysis is achieved; the same entities in the multiple tables are automatically recognized and merged through a cross-table entity intelligent merging algorithm, and multi-table collaborative intelligent search is achieved; constructing an intelligent knowledge graph: automatically selecting an optimal construction strategy through a multi-strategy relation construction engine according to keyword role features, and independently constructing a local knowledge graph for each data table; and optimizing and intelligently exporting the knowledge graph.

The invention provides a multi-modal fusion universal document intelligent credible extraction method and system. The method comprises the following steps: firstly, obtaining an original document; analyzing scene information of the original document, and determining a target sub-model corresponding to the scene information; segmenting the original document by adopting an overlapping segmentation merging algorithm to obtain fragmented files; wherein segmentation parameters of the overlapping segmentation merging algorithm are adjusted according to document features and scene features; and finally, obtaining a document extraction result according to the fragmented files and the large model of the target sub-model of the universal document intelligent credible extraction method with multi-modal fusion. According to the method, through scene recognition, adaptive document and scene feature overlapping segmentation, long document information integrity guarantee of multi-scene document extraction is realized, scene adaptation flexibility is improved, and extraction result accuracy and verifiability are enhanced.

The invention discloses a fluid-solid-sound coupling calculation method based on time domain analysis of an OpenFOAM platform. The fluid-solid-sound coupling calculation method comprises the following steps: decomposing a compressible fluid variable into an incompressible fluid variable and an acoustic pulsation quantity; deducing an acoustic control equation of a flow sound decomposition method under the dynamic grid; discretizing the acoustic control equation by adopting a finite volume method; applying an incompressible flow field boundary condition and an acoustic boundary condition; adopting an OpenFOAM dynamic grid technology to obtain grid information topological information and motion information; a PISO-SIMPLE merging algorithm is adopted to decouple the acoustic control equation; and solving the decoupled acoustic control equation to obtain sound pressure distribution so as to realize fluid-structure interaction vibration noise characteristic analysis. According to the method, the technologies of variable decomposition, fluid-solid coupling and dynamic grids are utilized, far-field linear hypothesis is avoided, acoustic forecasting of far and near fields is guaranteed, meanwhile, the calculation cost is saved, and the analysis efficiency is improved.

The invention discloses an intelligent patent retrieval method and system based on a large language model reordering technology, objects processed by the method comprise a variety of input data including patent public numbers, free texts and text files, key information is extracted, query texts are constructed, retrieval recall is executed, sparse and dense vector retrieval technologies are combined, and the retrieval efficiency is improved. And results are fused through a min sum merge algorithm. The de-noising step uses a sliding window strategy and vector coding to extract information fragments related to the query text. And finally, by training a reordering model and finely adjusting a recommendation list, the ranking of retrieval results is optimized, and the accuracy and correlation of retrieval are improved. According to the intelligent retrieval method, the patent retrieval efficiency and accuracy are improved.

The invention discloses a large-scale three-dimensional scene reconstruction method capable of simultaneously training scene RGB and semantics, and relates to the field of three-dimensional computer vision and graphics, in particular to a three-dimensional scene multi-modal reconstruction method based on block training and hierarchical Gaussian distribution. The method comprises the steps that an RGB image of a target scene is input, a tool is used for decomposing the scene into a three-dimensional Gaussian model containing appearance, semantics, depth and other information, rough optimization and block training are conducted on the target scene, and finally a multi-modal result containing the scene, semantics and depth information is obtained through a hierarchical merging algorithm. According to the method, multi-modal information such as geometric reconstruction and semantic segmentation can be efficiently integrated, and the real-time rendering performance is remarkably improved; the method is suitable for large-scale scene modeling, virtual reality content generation and automatic driving environment perception.

The invention relates to the technical field of art product design, in particular to an Internet-based art product design system. The system comprises a material acquisition management unit which obtains art product materials from a material platform through an internet interface protocol and generates a standardized material package; the semantic drive design generation unit converts user input into structured scene data based on a cross-modal semantic analysis technology, and constructs a semantic mapping matrix and an element confidence distribution mechanism to match the structured scene data with the standardized material package; the collaborative version fusion unit monitors and solves multi-version conflicts by using a timestamp consistency branch merging algorithm, and generates final art product work data; the cross-platform publishing rendering unit carries out adaptation processing on the final art product work data according to the requirements of the target publishing platform; according to the method, generation and release of an art product scene are realized in combination with a high-precision scene generation and timestamp consistency branch merging algorithm driven by cross-modal semantic analysis.

The invention provides a measuring point selection method and system based on a 3D radar level gauge, and relates to the technical field of measurement, and the method comprises the steps: obtaining original 3D radar point cloud data of a measurement scene, carrying out the adaptive space division of the measurement scene through employing an improved octree algorithm, obtaining a three-dimensional reconstruction result of the measurement scene, and carrying out the calculation of the three-dimensional reconstruction result. Performing normal vector calculation and region clustering, and determining a plurality of key regions in the three-dimensional reconstruction result in combination with a region growing and merging algorithm; and taking maximization of the coverage degree of the measurement points to the key area as a first target, taking minimization of the geometric distribution difference degree between the measurement points as a second target, solving the single-target optimization problem through an improved differential evolution algorithm, and selecting a solution with an optimal comprehensive evaluation index as a final 3D radar level gauge measurement point optimization arrangement scheme.

The invention provides a data synchronization method and device based on a distributed database and electronic equipment, which can be applied to the field of electric digital data processing. The method comprises the following steps: in response to a batch transaction processing request, reading a target batch transaction operation number corresponding to a current to-be-processed batch transaction from a batch transaction operation number queue; determining change data queues respectively corresponding to the L source data nodes; screening N target data updating records of which the transaction operation numbers are smaller than the transaction operation number of the target batch from the L change data queues, wherein the N target data updating records are associated with the M source data tables; based on a streaming merging algorithm, merging the target data updating records associated with the M source data tables in parallel by using M merging threads to obtain M data merging hash tables corresponding to the M source data tables; and synchronizing the merged data of the M source data tables into the target database in parallel by utilizing the M loading threads.

The invention discloses a sandstone slice image component identification method based on a GL-SLIC algorithm and semi-supervised learning. The method comprises the following steps: firstly, acquiring a sandstone slice image amplified by 200 times under single polarization, converting an RGB image into a CIE-Lab color space, and extracting a GLBP texture feature vector; then a GL-SLIC superpixel segmentation algorithm is constructed, and adaptive segmentation based on texture and color features is realized in combination with a Gabor filter and a local binary pattern; then implementing a region merging algorithm to generate complete mineral particles and pore fragments; finally, a classifier based on VGG16 and a discriminator based on ResNet18 are constructed, a semi-supervised self-training framework is adopted, a model is initialized by using about 6% of manual labeling samples, a high-confidence-coefficient pseudo-label extension training data set is generated through iteration, and automatic recognition of sandstone components such as quartz, pores, kaolinite, rock debris and a matrix is achieved. According to the method, the recognition accuracy of 96.3% on a test set is achieved, compared with a traditional method, the segmentation precision and the recognition accuracy are remarkably improved, the data labeling cost is greatly reduced, and an efficient technical scheme is provided for automatic analysis of geological images.

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.

Disclosed in the present application are a result generation optimization method, apparatus, device and system for a large language model. The method comprises: concurrently sending a preset prompt word to a plurality of preset large language models, so as to obtain a plurality of generation results; and performing comprehensive optimization processing on the plurality of generation results on the basis of a preset comparison selection algorithm or a preset merging algorithm, so as to obtain an optimization result, wherein the preset comparison selection algorithm is constructed on the basis of similar-distance analysis, and the preset merging algorithm is realized on the basis of merging the generation results. A plurality of preset large language models are used to simultaneously perform result generation on the basis of the same preset prompt word, and these generation results are then comprehensively optimized to obtain an optimized result; and during the process, optimization can be performed by means of selecting a preset comparison selection algorithm or a preset merging algorithm on the basis of the actual situations, so that it can be ensured that the optimized result is more accurate and reliable. In this way, the present application can solve the technical problem in the prior art of it not being possible to meet actual application requirements due to a result generated on the basis of a single large language model lacking accuracy and reliability.

The invention relates to the technical field of network data processing, in particular to a self-evolution online learning personalized recommendation method, which comprises the following steps of: acquiring behavior data of a learner during online learning in real time; constructing a simplified knowledge graph of the knowledge system of each subject by adopting a hierarchical decoupling method; a behavior continuity merging algorithm is adopted to obtain learning behaviors of the learner at each knowledge point based on behavior data mapping; fitting by adopting a time sequence capability vector fitting algorithm based on the behavior data to obtain the learning capability of the learner at each knowledge point; periodically determining a first recommended learning mode of each knowledge point based on the learning behavior and learning ability of the group learner at each knowledge point; the first recommendation learning mode of each knowledge point in the current period is corrected based on the learning behavior and learning ability of an individual learner to serve as a personalized recommendation result, so that'group efficiency + individual adaptation 'dual-drive recommendation is realized, meanwhile, dynamic standard correction and real-time response can be realized, and the consistency and accuracy of recommendation logic are improved.

The invention discloses a data processing method and device, electronic equipment and a readable storage medium, and the method comprises the steps: responding to the simultaneous editing operation of a plurality of editors on a to-be-edited logic arrangement instance, and based on the editing operation of each editor, determining the to-be-merged data of each editor for the to-be-edited logic arrangement instance; determining a target merging algorithm based on the number of editors of the plurality of editors and / or the merging complexity of merging the to-be-merged data of the plurality of editors; and merging the to-be-merged data of the plurality of editors according to the target merging algorithm to obtain data after editing the to-be-edited logic arrangement instance. According to the method provided by the invention, collaborative editing of the same to-be-edited logic arrangement instance by multiple editors is realized, and the editing efficiency of the to-be-edited logic arrangement instance is improved.

The application provides a distributed remote sensing interpretation vector post-processing method based on a grid DCEL topology. The method comprises: performing grid slicing on global grid data to obtain grid data of a plurality of grid units; constructing a bidirectional edge connection table topology based on the grid data of each grid unit respectively; performing elimination processing, thinning processing and smoothing processing on the topology of each grid unit respectively; merging the topology of each grid unit to obtain a global topology; and exporting the global topology as vector data. In this way, a high-performance grid topology engine based on a distributed architecture can be provided, a DCEL topology structure can be constructed from grid data, and distributed computing can be supported through a topology level merging algorithm; the grid is used to construct the topology, thereby reducing the steps of grid vectorization, and the grid-based topology construction method can naturally support distributed computing.

The invention is applicable to the field of mobile application development, and provides a ReactNative-based voice text dynamic highlighting and intelligent positioning component, which is characterized in that a timestamp-position mapping index is pre-calculated and established by initializing a layout, and fragmented contents are integrated by combining a semantic-driven text merging algorithm, so as to realize dynamic highlighting and intelligent positioning of a voice text. And a three-state interaction control model is constructed to realize state switching of automatic following and manual browsing. The component solves the problems of low real-time calculation performance, fragmented display visual interference, interaction logic conflict and the like in the existing scheme, is suitable for cross-platform mobile applications such as online education and voice notes, and improves the positioning efficiency, reading experience and operation convenience and reduces the multi-terminal development cost through pre-calculation optimization, intelligent combination and intelligent interaction.

Embodiments of the present disclosure disclose a central processor-based process interruption method, device, equipment and readable medium. A specific embodiment of the method comprises: obtaining a historical running data sequence of a target processor; performing data preprocessing on the historical running data sequence to generate a preprocessed historical running data sequence; performing segmentation processing on each preprocessed historical running data in the preprocessed historical running data sequence to generate a segmented historical data group set; determining a confidence interval corresponding to the segmented historical data group; for each determined confidence interval, performing an interval merging algorithm to generate at least one merged confidence interval as a utilization safety baseline set; and performing a process interruption operation on at least one process running on the target processor. The embodiment avoids data loss and the situation that the process carried by the processor cannot run, thereby reducing the waste of processor resources.

The invention relates to a method for recognizing objects in an overall image (6) comprising a plurality of individual images (8), wherein all objects in the overall image (6) belong to classes, wherein at least one recognition frame (10) with a respective confidence value is assigned to each object, wherein a first merging algorithm (14) is carried out for each individual image (8), wherein a second merging algorithm (15) is carried out for the overall image (6), wherein a first suppression algorithm (16) is carried out for the overall image (6), and wherein a second suppression algorithm (17) is carried out, in which a class agnostic (20) and a white list (22) are taken into account for all classes of the objects.

The present application relates to the technical field of network data processing, in particular to a self-evolving online learning personalized recommendation method, comprising: collecting behavior data of learners in real time during online learning; constructing a simplified knowledge graph of each subject knowledge system by using a hierarchical decoupling method; obtaining the learning behavior of learners at each knowledge point based on behavior data mapping by using a behavior continuity merging algorithm; fitting the learning ability of learners at each knowledge point based on behavior data by using a time sequence ability vector fitting algorithm; periodically determining the first recommended learning mode of each knowledge point based on the learning behavior and learning ability of group learners at each knowledge point; and correcting the first recommended learning mode of each knowledge point in the current period based on the learning behavior and learning ability of individual learners to serve as a personalized recommendation result, realizing double-driven recommendation of "group effectiveness + individual adaptation", and simultaneously realizing dynamic standard correction and real-time response, improving the logical coherence and accuracy of the recommendation.

The present invention discloses a text content extraction and recognition method based on vertical merging of line text boxes. By using a finger to point at the question to be viewed under the device camera and uploading it to the server in the form of a picture, all the text related to this question can be selected with a rectangular box through a simple algorithm, achieving vertical merging of one line, and presenting the text in the rectangular box. According to the position information, semantic information, and finger coordinate information of the text box, the present invention uses a simple and efficient algorithm to realize the merging of multiple relevant text boxes, and outputs the content in the merged text box. This algorithm is simple and efficient, solving the problem of insufficient server resources. At the same time, the present invention uses object detection and hand detection recognition to find the coordinates of the finger key points. After using the existing model and subsequent training, the accuracy is improved and the speed becomes faster, which can better cooperate with the text box merging algorithm.

This invention discloses a real-time data synchronization method based on DAG orchestration and asynchronous zero-copy architecture, comprising: constructing a directed acyclic graph (DAG) based on timestamped data and its data lineage to obtain parallelizable task nodes; sending data using a zero-copy transmission method based on io_uring based on the parallelizable task nodes to obtain zero-copy transmitted data; grouping the received data according to the source IP address and storing it in the corresponding receiving queue to obtain grouped queue data; and sorting and merging the grouped queue data according to the global timestamp using a time window multi-path merge algorithm, and using an event barrier mechanism to handle the order of data definition language instructions and data manipulation language instructions to obtain a globally ordered event stream. This invention achieves dependency-aware parallel scheduling, zero-copy asynchronous transmission, and globally ordered merging of cross-source events.

The embodiment of the invention discloses a process interruption method and device based on a central processing unit, equipment and a readable medium. A specific embodiment of the method comprises the steps of obtaining a historical operation data sequence of a target processor; performing data preprocessing on the historical operation data sequence to generate a preprocessed historical operation data sequence; performing segmentation processing on each piece of preprocessed historical operation data in the preprocessed historical operation data sequence to generate a segmented historical data set; determining a confidence interval corresponding to the segmented historical data group; for each determined confidence interval, executing an interval merging algorithm to generate at least one merged confidence interval as a utilization rate safety baseline set; and performing process interruption operation on at least one process operated by the target processor. According to the embodiment, data loss is avoided, the situation that the process borne by the processor cannot run is avoided, and waste of processor resources is reduced.

The invention discloses a logical configuration unified analysis storage and lightweight conversion method and system, and the method comprises the following steps: carrying out the dynamic loading of a corresponding analysis plug-in according to the front-end display formats and label rule differences of the XML / HTML / SVG of logical configuration files of different brands of DCS (Distributed Control System), logic node information, connection relation information, parameter setting information and input and output node information are extracted; storing the extracted logic node, connection relation, parameter setting and input and output node information in a graph database in a graph data form to form an attribute graph model; according to the graph database logic configuration information, a complete logic chain is extracted through a recursive retrieval algorithm based on graph traversal and a hard wiring merging algorithm, and a lightweight file is generated according to a preset template. Uniform format management of DCS logic of subordinate power plants of a power generation group is realized. More importantly, an ideal data basis is provided for deep analysis of a language model (LLM) on DCS logic, and standardized and intelligent development of DCS management of a thermal power plant is promoted.

The invention relates to the technical field of database synchronization and distributed caching, in particular to a Redis cache management method and device, computer equipment and a storage medium, and the method comprises the steps that a database write operation is packaged into a domain event with a signature and is synchronized into an event bus; sequentially aggregating events into event blocks, writing the event blocks into a data lake, calculating a polynomial commitment, and copying the polynomial commitment to decentralized storage; the cache node replays an event after verifying a root commitment, writes the event into Redis according to a conflict free copy data type merging algorithm, and migrates fragments and refreshes a random challenge value according to key popularity; each node performs federal learning on a local training prediction model and homomorphic encryption gradient, then aggregates and updates the weight, generates a model hash and root commitment abstract, proves chain writing through zero knowledge and writes logs back, and realizes cache high consistency, low delay, verifiability and privacy security management.

The invention discloses a heterogeneous multi-robot collaborative coverage method for a mine environment, and belongs to the technical field of robot path planning. According to the method, firstly, a mine roadway structure is abstracted into a directed graph with characteristic parameters, and a multi-layer virtual graph is constructed based on different robot capabilities; aiming at the characteristics of asymmetric traffic cost and empty driving demand in a mine, an improved enhancement-merging algorithm is designed, and an efficient service route meeting resource constraints is generated. And multi-graph polling and main task graph mapping are combined, and heterogeneous multi-robot collaborative coverage is realized through multi-round iterative planning. According to the method, the path planning efficiency and the task coverage quality are improved, and the method is suitable for heterogeneous multi-robot collaborative coverage under the catastrophe mine.

This application proposes a multi-classification-based text detection method and system, comprising: acquiring and organizing text box samples; segmenting the text box samples into text units; labeling the coordinates and flags of the text units; generating training and validation sets proportionally from the text box samples; assigning class labels to the flags of the text units; constructing a text unit detection network model; training the training set using the text unit detection network model until the loss converges; obtaining the output of the trained model, which is set B; constructing a text unit merging algorithm; dividing set B into multiple subsets based on the class labels of the flags; calculating the bounding rectangle of the point set cnt based on the current element and the elements in the subset to which the current element belongs; and inputting the validation set into the trained model to finally obtain all the text boxes. This method effectively solves various problems such as inaccurate text localization, missed detections, and false detections in natural scenes, and can also handle multi-angle text detection problems.

The invention discloses a terminal and network mass information aggregation analysis, deduplication and combination method, and belongs to the field of big data processing. Aiming at the problems of difficult redundancy elimination, heterogeneous data fusion bottleneck, insufficient real-time performance and the like of a traditional method, a terminal-edge-cloud three-level distributed architecture is constructed. The terminal layer extracts multi-modal features in a lightweight manner; the edge layer realizes space-time dual-domain de-duplication through a dynamic weight de-duplication algorithm, and aggregates cross-modal features; and the cloud end constructs a multi-modal knowledge graph based on an information entropy driving merging strategy. The core technology comprises cross-modal unified representation, dynamic weight removal and an incremental merging algorithm. Practice of a provincial power grid company shows that the storage cost is reduced by 57.8%, the event response delay is reduced to 1.7 seconds, the fault positioning accuracy is improved by 41%, and the mass information processing efficiency is effectively improved.

The invention discloses a file merging method based on data inclination. According to the method, optimization of disk files is achieved through a merged file selection strategy based on read heat, an internal merging strategy based on HyperLogLog and a disk file merging algorithm based on inert update. According to the method, the file merging method of the LSM tree is redesigned on the basis of the inclination of the workloads, and compared with previous work, data cold and hot degree information in the workloads is fully utilized, and a disk file merging strategy based on the hot degree is designed. On a disk, cold read files are preferentially selected to be merged to a lower layer through read heat information, and meanwhile, the write amplification problem caused by merging operation to a system is relieved through an inert merging algorithm of disk files.

The invention discloses a data distribution search method for a private cloud storage architecture, and particularly relates to the technical field of data retrieval, data is distributed to each storage node through a consistency hash algorithm, node loads are monitored, when the node load difference exceeds a preset value, virtual node adjustment is triggered, virtual nodes are reduced for nodes with high loads, and the efficiency of data retrieval is improved. The virtual nodes with low loads are added, so that load balance is promoted, the single-point fault risk is effectively reduced, and effective utilization of node resources is realized; according to the method, search results are matched with role data access permissions, if matching succeeds, comprehensive correlation coefficients of the search results and data search requests are calculated, the search results with the permissions successfully matched are ranked from high to low according to the calculated comprehensive correlation coefficients, and the first K search results are obtained through a Top-K merging algorithm and then returned to a user. The accuracy of data search is improved, and the jamming probability caused by returning of a large number of data search results is avoided.