46results about How to "Efficient query" patented technology

The invention discloses a large model knowledge base construction method based on multi-granularity retrieval. The method comprises the steps of obtaining a target text and analyzing a document structure, splitting and reorganizing text data according to three levels of titles, fragments and sentences, and constructing three levels of knowledge of the titles, the fragments and the sentences; using a large language model to construct a generative index as question-level knowledge according to the sentence-level knowledge; using a vector model to generate a first vector representing index keys of fragment-level knowledge and / or sentence-level knowledge, and a second vector representing index keys of title-level knowledge and / or question-level knowledge; and respectively storing the first vector and the second vector into a vector database, and storing the index values and the index types corresponding to the first vector and the second vector into a relational database. According to the method, multi-granularity document knowledge base construction is achieved, the expression modes of knowledge under different granularities are expanded, the accuracy of user query and knowledge matching is improved, and the problem that information is lost or incomplete in an existing method is solved.

The invention relates to the technical field of braid quality detection in industrial production, in particular to a defect data processing query method and system for braid visual inspection. The method comprises the steps of obtaining braid image data, performing enhancement processing on an image based on a dynamic illumination compensation algorithm, and generating a high-quality image in combination with material characteristics; inputting the enhanced image data into a deep learning defect detection model, detecting and classifying defect areas in the image, and updating the model weight based on defect feature parameters; performing multi-dimensional indexing processing on the detected defect feature data to generate a defect distribution database supporting real-time query; and the defect distribution database and the production process parameter sequence are combined, the causal relationship of defect occurrence is analyzed, process optimization parameters are generated and fed back to the detection module, and self-adaptive updating of model parameters is completed. According to the invention, high precision, high efficiency and closed-loop optimization of braid defect detection are realized, and intelligent support is provided for industrial production quality control.

The invention relates to a data mining method, a multi-modal data query method and a vertical domain knowledge question and answer method based on a knowledge graph. The mining method comprises the steps of generating a knowledge graph based on a first artificial intelligence model; inputting initial node information acquired by the knowledge graph into a second artificial intelligence model, wherein the second artificial intelligence model comprises a knowledge graph expansion unit, an abnormal node acquisition unit, a key node acquisition unit and a value mining unit; expanding expanded node information from the initial node information through a knowledge graph expanding unit, and respectively outputting the expanded node information to the abnormal node acquisition unit and the key node acquisition unit; and the abnormal node acquisition unit and the key node acquisition unit respectively output abnormal nodes and key nodes in the knowledge graph to the value mining unit, so that the value mining unit presents related information of the abnormal nodes and the key nodes.

The invention discloses an enterprise supply chain side evaluation method and system based on big data, and provides an innovative solution for the problems of low data processing efficiency, weak analysis and prediction ability, insufficient causal relationship analysis, decision support lag and the like in supply chain management. The method comprises the steps of integrating and processing real-time data, deeply analyzing the data by using an advanced analysis and prediction module in combination with a mathematical model and a machine learning algorithm, deeply understanding a causal relationship in a supply chain through a causal relationship analysis and optimization module, and finally accelerating a decision process through a visualization and decision support module. According to the system, through modular design and an advanced algorithm, the supply chain management efficiency and scientificity are remarkably improved, and comprehensive evaluation and optimization of the supply chain are achieved. The invention aims to solve the problem of improving the efficiency, accuracy and scientificity of enterprise supply chain management under the background of big data so as to adapt to rapidly changing market demands and a complex supply chain network.

The invention relates to the field of big data processing, and particularly discloses a message pushing processing method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: if a push message type of a to-be-executed message push task exists at current time, taking the current time as query ending time; for each message pushing task, if a historical task execution record of a pushing message type of the message pushing task is queried, determining the last execution end time and the message processing duration of the last execution process from the historical task execution record; determining query start time based on the last execution end time and the message processing duration to construct a message query interval which is continuous and not overlapped with a historical query interval of a last push task in the historical task execution record; and querying according to the message query interval to obtain message content and pushing the message content. By adopting the method, decoupling of the service interface and the message processing interface can be realized, and complete message content can be efficiently pushed.

The invention discloses a multi-dimensional query analysis method and system based on coal mine production operation data integration, and relates to the technical field of data query analysis, and the method comprises the steps: collecting and preprocessing coal mine production data of different data sources, fusing the preprocessed data, and generating a coal mine data set; obtaining a distinguishing feature vector and a target variable of each type of data in the coal mine data set, and carrying out modeling according to the relevance of the distinguishing feature vector and the target variable to obtain a data query model; obtaining a business data demand of a user, determining a data attribute dimension according to the business data demand by using the data query model, and determining to-be-queried data based on the data attribute dimension; and extracting to-be-queried data from the coal mine data set, and analyzing a service decision and an optimization process according to a data change trend and a service development state. According to the method, the multi-source coal mine production data are integrated, the intelligent query model is established, efficient multi-dimensional data analysis is realized, and the data sharing and query efficiency is improved.

This invention relates to the field of model simulation calculation, and particularly to a real-time rendering system for 3D simulation analysis results of dams. The system server, through a simulation model management module, transmits a 3D finite element mesh model, obtains calculation conditions from the system client, performs simulation based on these conditions, outputs calculation results, and transmits the calculation result data to the system client after processing it using an 8-bit compression method. A three-level indexing system is constructed. The calculation result management module manages the calculation results. The system client renders a multi-dimensional physical field cloud map. During precise queries, the system server returns lossless calculation results to the system client based on the three-level indexing system. This invention leverages the long-connection characteristics of WebSocket to achieve on-demand incremental transmission of fragmented data, resolving network congestion caused by full transmission. Through the synergy of data compression and progressive rendering, network utilization is optimized while ensuring the real-time performance and stability of the front-end visualization effects.

The invention discloses a blast furnace incoming iron management data processing system and method. Comprising a data display module, a query module, an export module and a data operation module. The data display module is provided with a converter molten steel receiving display unit, a molten steel receiving team statistical display unit, a blast furnace incoming iron scrap display unit and a blast furnace incoming iron team statistical display unit; and the converter molten steel receiving and displaying unit is used for displaying detailed data received by the converter, wherein the detailed data comprises converter heat, blast furnace heat, time, ladle number, molten iron components and operation information. According to the invention, by integrating blast furnace incoming iron related data and intensively displaying various types of data on different pages, unified management of the data is realized. Meanwhile, convenient data entry, modification and deletion operation and efficient query and export functions are achieved, the time and labor cost of data management are greatly saved, and the data management efficiency is improved.

The invention relates to an electronic certificate relation storage and query method. The method comprises the following steps: collecting an existing electronic certificate relation log of each service; according to the electronic certificate relationship of each service, allocating a link tracking ID and a hierarchy counting ID to each electronic certificate of each service to form an electronic certificate relationship storage structure; designing a query interface based on the electronic certificate relation storage structure of each service; calling the query interface in an actual business scene, and querying the electronic certificate through the interface; the storage method of the complex electronic certificate relationship can be realized, and efficient query is guaranteed to meet business requirements.

The embodiment of the invention provides a multi-network integration Internet of Things card fee query method, system and device and a storage medium, and belongs to the technical field of computers. According to the method, a first cost query request of a multi-network integration Internet of Things card is obtained, the first cost query request is converted into a second cost query request of a target network operator through an API pipeline model, and then a cost query service system of a corresponding network operator is accessed according to the second cost query request of each target network operator. And obtaining a cost query result of the multi-network integration Internet of Things card. According to the method, the external interface is unified by using the API pipeline model, and after the first cost query request of the user is received, the first cost query request is converted into the second cost query request conforming to the cost query service system interface of the network operator, so that efficient query of the multi-network integration Internet of Things card cost is realized, and the user experience is improved. And the charging convenience of the multi-network integration Internet of Things card is improved.

The invention discloses a mixed data calling method and device oriented to the field of electromagnetic scattering, and belongs to the field of data storage. The method comprises the following steps: classifying acquired data of an acquired moving target; the classification result is subjected to indexing and query optimization and then stored in a composite database; and calling all data associated with the to-be-queried target in the compound database according to the query instruction of the uniform interface. According to the invention, efficient storage, query and management of electromagnetic scattering data can be realized, and the processing capability of complex data is improved.

This application provides a method and system for processing spacecraft manufacturing process data. The method includes: constructing a query data index; performing hierarchical desensitization processing on spacecraft process-sensitive data according to multi-level desensitization rules; using the query data index as an anchor point, determining the model identifier, process parameters, component number, material batch, and multimodal identifier associated with the same process, and establishing a mapping table between the desensitized data and the spacecraft process-sensitive data; and performing a query on the current client's process query interface based on the input query data index to return the matching process manufacturing data to the process query interface. This application enables more efficient querying of process manufacturing data, hierarchical desensitization processing of spacecraft process-sensitive data, and obtains more secure and reliable desensitized data and data transmission.

The present invention relates to the field of site selection optimization technology, and in particular to a site selection optimization method, system, device and medium for tourist attractions, including: obtaining candidate site selection information of rural tourist attractions, and using a geographic information system to perform spatial analysis on the candidate site selection information to obtain the geographical environment characteristics of the candidate points; constructing a Thiessen polygon optimization grid according to the geographical environment characteristics of the candidate points, and using a quadtree to divide the Thiessen polygon optimization grid to obtain site selection sub-areas; expressing the geographical environment characteristics of the candidate points in each site selection sub-area as a spatial entity to construct a graph structure; using a graph attention neural network algorithm to learn the graph structure to predict the optimal spatial coordinates of the site selection of the tourist attraction. The present invention realizes a method for optimizing the site selection of the tourist attraction by combining the characteristics of the quadtree and the graph structure, and can more accurately analyze the spatial connections such as cultural resources between the site selection of the tourist attraction, and provide more accurate and effective support for the planning and management of tourist attractions.

The invention relates to the technical field of finance, in particular to dynamic pre-loan repayment trial calculation software and an implementation method thereof, and the dynamic pre-loan repayment trial calculation software comprises a user interface module, a data storage module, a calculation engine module and a result display module. And the user interface module allows the user to input parameters such as loan amount, repayment time limit and interest rate, and selects a repayment mode. The data storage module maintains a database and stores basic information and repayment rules of loan products, including a user table, a loan product table and a trial record table. And the calculation engine module selects a proper repayment formula (such as equal-amount essential information or equal-amount principal) for calculation according to loan parameters input by the user, and generates a detailed repayment plan. The result display module visually displays the calculation result in the form of a table or a chart, and provides detailed information of monthly repayment. According to the invention, the user can conveniently and quickly carry out loan repayment trial calculation, understand a detailed repayment plan and make a more intelligent loan decision.

The invention discloses a power grid fault plan knowledge extraction method and system based on a large model. The method comprises the following steps: extracting key knowledge from a power grid dispatching procedure, and converting the key knowledge into a structured object; classifying structured objects of regulation into different fault scenes according to accident types, designing a prompt template for each fault scene, converting accident names into vectors by using a pre-training model, and storing the vectors in a vector database; performing content analysis on the fault plan to determine information needing to be extracted and identify a compilation and a unit; analyzing the fault plan document to extract key attributes, reading plan contents according to segments, associating table information with document contexts, and performing plan content objectification according to a document analysis result; and triple knowledge in the plan is extracted by using a large model, and the knowledge is stored in a graph database after rule checking of a business expert. Knowledge extraction is carried out by means of a large model, a corpus is not needed, and generalization is high.

The invention discloses a knowledge graph-based algorithm model operation driving engine construction method, which comprises the following steps of: respectively configuring a data source, an algorithm and a model to form a data source library, an algorithm library and a model library, selecting the required data source, algorithm and model from the libraries, and arranging according to a model operation rule to obtain an algorithm model operation rule graph. And analyzing the algorithm model operation rule map into triple text data, converting the triple text data into formalized language text, verifying by using multi-model interaction behaviors, and returning error prompt information through an interaction interface if the rule is unqualified. And if the rule text is qualified, inputting the rule text into a task engine generator, and generating an algorithm model driving engine by the generator according to the rule text. According to the method, the problems of difficulty in arrangement of algorithm and model operation modes, tedious management of operation rules, low execution efficiency and the like in a manufacturing environment are solved, so that the production efficiency and the product quality are improved.

The application discloses a permission data query method and device, a storage medium and an electronic device, and relates to the technical field of smart homes. The method comprises the following steps: determining a target identifier corresponding to a target object using a permission management system; determining one or more role identifiers from a pre-defined first relationship set based on the target identifier, and determining one or more resource identifiers from a pre-defined second relationship set and the pre-defined first relationship set based on the target identifier; in the case that it is determined that a management object has entered a query condition in the permission management system, inputting the role identifier, the resource identifier and the query condition into a pre-configured permission model in the permission management system to obtain a permission rule of the target object, and analyzing the permission rule to determine a query result of permission data corresponding to the target object, thereby solving the problem of querying permission data in addition to authorization requests.

The invention provides a medical big data ES wide table generation method and device based on efficient dynamic data configuration, and belongs to the technical field of medical data processing, and the method comprises the steps: carrying out dynamic data configuration based on a built ES distributed cluster; according to dynamic data configuration, performing personnel main table query in the dimension of people and source table query in the dimension of doctor seeing from a specified table of a data source through multiple threads, and collecting data of required fields; converting the collected data into a unified ES field structure type according to a data type so as to obtain standardized data; and carrying out data assembly according to the dimensions of people and doctor seeing based on the standardized data, generating ES personnel wide table data and ES doctor seeing wide table data, and updating the two pieces of ES wide table data to an ES distributed cluster in real time. According to the invention, large-scale medical data can be efficiently integrated and managed, powerful data retrieval and analysis capabilities are provided, and the capabilities of cross-mechanism data sharing, rapid query and accurate analysis are improved.

The invention provides an automatic query method and device for substation elements based on substation drawings. The method comprises the following steps: in response to a query instruction of a user, displaying a visual model of a transformer substation drawing indicated by the query instruction on an interface; wherein the query instruction is used for indicating to query a visual model of the transformer substation drawing; the visual model comprises at least one relation model, and the relation model indicates a connection relation and / or a position relation between transformer substation elements in the transformer substation drawing; the relation model is generated based on a transformer substation drawing; in response to a trigger operation of a user, displaying transformer substation element information associated with a transformer substation element indicated by the trigger operation on the interface; wherein the trigger operation is used for indicating the substation elements in the relation model. According to the method, the efficiency and impression of querying the substation elements based on the substation drawings are improved.

The embodiment of the invention provides a data storage method and device, a data query method and device, equipment, a medium and a product. The data storage method comprises the steps that service data of multiple service objects and attribute information of the multiple service objects are obtained; based on the business data and the attribute information of each business object, generating a business data table containing the business data of the plurality of business objects and the attribute information of the plurality of business objects; according to a preset division rule, performing table division and partition processing on the service data table to obtain a plurality of service data sub-tables and partition results of the plurality of service data sub-tables; and storing the business data in a target database based on the plurality of business data sub-tables and the partitioning result of the plurality of business data sub-tables. Through the embodiment of the invention, the flexibility of data management is improved, the resource consumption during query is reduced, and the data query efficiency and the flexibility of the query process are improved.

The invention discloses a bee knowledge intelligent question-answering method and system, and belongs to the technical field of intelligent question-answering. Comprising the following steps: acquiring and preprocessing bee knowledge data, and constructing a bee knowledge graph and bee knowledge granules according to the bee knowledge data; obtaining a target problem, and calculating a key entity, an intention category and an intention confidence coefficient of the target problem; assigning a credible label or an uncredible label to the target question; if the target question is endowed with the untrusted label, obtaining a target concern of the target question; obtaining target text data corresponding to the target concern according to the bee knowledge particle ball, and performing knowledge enhancement processing on the target question according to the target text data to obtain an enhanced question; recognizing the reinforcement problem according to a second recognition model to obtain a reinforcement intention category; retrieving the key entities and the intensified intention categories through a bee knowledge graph to generate answers; by enhancing the target question, the recognition rate can be improved, and more comprehensive answers can be given.

This invention discloses a method and system for completing spatial relationships based on a BIM model. The method includes: S1, extracting geometric data from a JSON file as raw data and preprocessing the raw data; S2, using an octree data structure to perform collision detection and spatial relationship calculation for BIM components; S3, using existing collision detection results and spatial relationship data to predict undetected potential spatial relationships between BIM components and complete the missing relationships to improve the overall spatial layout information. This invention, through three-level geometric detection working in conjunction with R-GCN, simultaneously captures physical-level contact relationships, orientation relationships, and semantic-level associations, significantly improving the completeness of spatial relationship recognition, greatly shortening data processing time and reducing implementation costs, while improving design efficiency and construction quality.

The present invention discloses a personalized path planning method that is sensitive to urban points of interest. The present invention divides the urban area into grids in advance, and then constructs a grid connectivity relationship based on the actual road network, connects each area, and models it into a graph. The path planning problem is modeled as: planning a shortest path that starts from a given starting point, visits multiple locations of different points of interest (POI) types in a user-specified order, and finally arrives at a user-specified destination. The path planning solution is divided into three stages: the first is the node spacing calculation stage, the second is the POI-prioritized greedy search stage, and the third is the dynamic planning stage based on the upper bound of the distance. Through the pre-processed shortest distance, based on the idea of ​​the dynamic programming algorithm, a shortest path that can meet the user's needs to sequentially visit candidate nodes of a specified type is found quickly and accurately.

The invention relates to the field of big data processing, and particularly discloses a test data processing method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: determining a plurality of database fragments indicated by a test data extraction instruction, and connecting each database fragment; determining a database fragment group needing to be subjected to test data joint query according to association levels among the data stored in the plurality of database fragments; taking each database fragment group as a single query object, and taking each database fragment which is not used for constructing the database fragment group as a single query object; a database query statement is obtained, after the database query statement is called, the database query statement is controlled to be executed circularly, data query is carried out on each query object in sequence, and database fragments to which test data obtained through query belong are identified respectively; and writing the identified test data into a test data storage document. By adopting the scheme, the test efficiency can be improved.

The invention relates to the technical field of software, and discloses a manufacturing industry task and resource matching method and system, and the method comprises the steps: obtaining tasks and resources, including time constraint information and resource demand information of the tasks; processing the available time of each resource, and converting the available time period of the resource into a double linked list structure formed by a plurality of time slice nodes; calculating a corresponding task priority field for each task object based on the time constraint information of the task, the resource demand information and a preset business rule, and sorting the task objects according to the task priority fields; and according to the sequence of the sorted task objects, performing resource matching processing on each task object in sequence, and generating a task and resource allocation result. The resource time slices are managed by using the double linked list, so that the query, insertion and deletion operations of the time window are very efficient, and the method is particularly suitable for a frequently and dynamically updated manufacturing environment.

The invention relates to the technical field of data processing, and particularly discloses a cloud architecture clustering management method for pet allergen detection result big data, which comprises an acquisition step, a generalized function set construction step, a neutral virtual pet model construction step, a clustering step and an output step. The method comprises the following steps: collecting pet allergen detection data and constructing a pet allergy responsivity function to form a generalized function set; using the neutral virtual pet function set as a reference, executing single-valued description and clustering analysis on the distance between different function sets, and obtaining a clustering interval and allergy judgment result concentration; and finally outputting a pet allergy judgment result and a corresponding confidence coefficient. The scheme can improve the assessment accuracy of the pet allergy risk, has both flexibility and expandability, is suitable for large-scale pet allergy detection and data management scenes, and can realize data sharing through a unified cloud architecture.

This specification provides a data query method, device and server. Based on the big data technology involved in this method, the target subject type is first determined according to the query subject carried in the received query request; then, according to the target subject type, a matching target field pool and target condition pool are determined from multiple preset field pools and multiple preset condition pools; and, a matching target source table is also determined from multiple preset source tables; further, according to the target field pool and target condition pool, the target field and the target data value related to the target field are obtained; then, according to the above target subject type, target field and target data value, the corresponding target query statement is automatically spliced ​​and generated; and then, the above target query statement can be used to perform data query operations only on the target source table in the preset source table, thereby simplifying user operations, efficiently querying and obtaining target data that meets the specific requirements of users, and improving the user experience.

The present invention discloses a method and system for implementing API call information statistics based on InfluxDB, belonging to the field of API calls; the specific steps of the method are as follows: S1 uses the gateway kong to save the published API call information to a cache database; S2 regularly saves the call information in the cache database to InfluxDB; S3 uses the interface of InfluxDB to query the call status of the API; S4 directly saves the processed standard data to InfluxDB in the plug-in; the present invention provides a method for implementing API call information statistics based on InfluxDB, wherein an API is created by an API management console, and the call information is saved to the cache database when the API is called, and then the call information is saved from the cache database to InfluxDB by a scheduled task; the preservation of API call information based on InfluxDB is simpler and more high-performance than that of msql, and InfluxDB supports sql-like syntax and index serialization, can be automatically aggregated, and is faster and more efficient in subsequent queries.

The embodiment of the invention provides an information obtaining method and device, electronic equipment and a storage medium, and relates to the technical field of network communication, and the specific scheme is as follows: in response to meeting an information analysis condition, analyzing lease information in a DHCP lease file to obtain a corresponding relationship among an analyzed IP address, an MAC address and a switch port identifier; on the basis of the obtained corresponding relationship, updating the locally stored corresponding relationship; and in response to receiving an information query request sent by a request end, querying a corresponding relationship matched with the information query request in the locally stored corresponding relationships, and sending a query result to the request end based on the queried corresponding relationship. By applying the scheme provided by the embodiment of the invention, the efficiency of obtaining the IP address of the terminal equipment can be improved, and the operation and maintenance efficiency is improved.