132results about How to "Improve query speed" patented technology

The invention provides a multi-dimensional accounting data integration and analysis system, and belongs to the technical field of accounting information processing, the multi-dimensional accounting data integration and analysis system comprises a data acquisition system, a data source interface unit of the data acquisition system can be connected with a plurality of data sources, and an acquisition control unit manages acquisition; the data integration system comprises a preprocessing module (format conversion, data cleaning and fusion modules); the data analysis system is provided with an analysis dimension setting module, an algorithm execution module and a result visualization module; the data storage system comprises a storage architecture management and index module, solves the problems that a traditional method is difficult in data source integration and single in analysis dimension, can effectively integrate multi-dimensional accounting data, improves the comprehensive analysis capability, improves the data security and query performance, and visually presents an analysis result to facilitate decision making.

The invention discloses a memory space indexing system and method for power grid data, and the system comprises a variable-length prefix compression coding unit and a multi-level indexing unit. The variable-length prefix compression coding unit is used for storing index information to adapt to the real-time change of power grid data; the multi-level index unit is used for retaining data which are most frequently accessed in a rapid memory, storing data which are less accessed in an auxiliary memory which is slower but larger in capacity, monitoring the change of power grid data in real time, dynamically encoding new data, updating an index structure, dynamically adjusting the size and the structure of an index according to the data access frequency and the updating frequency, and storing the data which are most frequently accessed in the rapid memory and the auxiliary memory which is slower but larger in capacity. Index nodes are split or merged by using the flexibility of compression coding of prefixes with variable lengths so as to adapt to the change of data volume. According to the method, the size and the structure of the index can be dynamically adjusted, so that the memory occupation is reduced, and the indexing efficiency is improved.

The invention discloses a NeRF modeling method fusing a time dimension and a hierarchical sampling strategy. The NeRF modeling method comprises the following steps: constructing a data set; sampling M coarse sampling points for each ray of the RGB image in the data set; position coding is carried out on the coarse sampling points, and then the volume density and color of the coarse sampling points are output by the MLP; calculating the weight of the coarse sampling point, and accumulating the weight; n fine sampling points are generated based on the accumulated weight, and the volume density, the color, the opacity and the accumulated transmittance of the fine sampling points are calculated; calculating the color of the ray by combining the coarse sampling point and the fine sampling point; constructing a loss function L of the MLP; and training the MLP to obtain a three-dimensional scene modeling model. According to the method, the rendering efficiency is improved through a hierarchical sampling strategy, an explicit space structure is fused during coding to enhance the capturing capability of the model for complex geometry, and time coding is added to efficiently cope with dynamic changes in a scene, so that better performance and efficiency are achieved when large-scale, complex and dynamic three-dimensional scenes are processed.

The invention belongs to the technical field of network communication, and particularly relates to an IP message fragmentation and recombination method and system based on an FPGA. According to the method, the process of fragmenting and recombining the IP message is unloaded from the CPU to the FPGA to be executed, so that the load of the CPU is reduced; according to the method, storage and recombination of IP message fragments are divided into two asynchronous processes, the storage process is responsible for writing the IP message fragments and the states of the IP message fragments into various tables, the recombination process is responsible for obtaining the IP message fragments and the states of the IP message fragments from the various tables, and the IP message fragment recombination efficiency is improved through the two-stage assembly line structure. According to the method, the TCAM is adopted for matching the IP message fragments, so that the problem of hash value conflict caused by a common matching method based on hash operation is avoided; and meanwhile, a dynamic resource allocation and recovery mechanism is adopted, so that the resource utilization rate is improved.

The invention provides a data processing method, electronic equipment and a storage medium, and relates to the technical field of data processing. The method comprises the steps that on the basis of preset mapping relation information and multiple self-defined preset data processing statements, multiple alternative semantic trees corresponding to the preset data processing statements are constructed, and the preset mapping relation information is information representing the mapping relation between the preset data processing statements and execution statements in a database to be used; according to the obtained format of the to-be-processed data, matching with a plurality of alternative semantic trees, and determining a target semantic tree corresponding to the to-be-processed data; determining a query statement corresponding to the to-be-processed data according to a target semantic tree corresponding to the to-be-processed data; and querying the to-be-used database based on the query statement corresponding to the to-be-processed data to obtain a data query result. And the processing steps of the business data are simplified, so that the data query result reflects the change condition of the business data.

The invention provides a method, system and equipment for querying asset depreciation data and a medium, and the method comprises the steps: creating a depreciation data table corresponding to a year according to the year, and storing the depreciation data of assets over the years in the corresponding depreciation data table; compressing the depreciation data of the assets over the years; carrying out depreciation data partitioning on the database by taking the financial division as a partitioning key; establishing data query entries over the years, and querying the asset depreciation data in the database by calling the query entries of the corresponding years; according to the method, the problem that a user cannot obtain a response in a reasonable corresponding time when querying reports such as general ledger or unit depreciation details or performing counting and depreciation operation is solved, and the speed of querying and updating asset depreciation data is increased.

The invention relates to the technical field of construction of genome databases, in particular to a construction method of a pathogenic microorganism genome database. The method comprises the following steps: carrying out pathogen characteristic point location analysis on a pathogen microorganism genome sequence to obtain pathogen characteristic point location data; carrying out physiological and biochemical characteristic analysis on a pathogenic microorganism genome sequence according to the pathogenic characteristic point data, carrying out genome evolution relation simulation, and then carrying out prepositive relation linkage identification to obtain prepositive relation linkage data; performing relation nested structure analysis on the prepositive relation linkage data, and performing relation coding index construction to obtain a linkage relation coding index; and carrying out dynamic retrieval condition matching on the linkage relationship coding index, and carrying out genome database construction to obtain the pathogenic microorganism genome database. The construction technology of the genome database is improved, so that the construction technology of the genome database is more perfect.

The invention provides an enterprise information query method and device and electronic equipment, and the method comprises the steps: responding to a configuration operation of a query condition group and an operation mode for at least one target enterprise information dimension, and aiming at each query condition in the query condition group under each dimension, obtaining a query result of the at least one target enterprise information dimension; judging whether enterprise ID data corresponding to the query condition exists in a memory or not; if yes, acquiring data corresponding to the query condition from the memory; if not, obtaining through a request server; for each dimension, according to the enterprise ID data of each query condition under the dimension and the corresponding operation mode, calculating to obtain data under the dimension; calculating an intersection between the data corresponding to the plurality of dimensions to obtain the data under the plurality of dimensions; and in response to an information display request of a user, obtaining enterprise information corresponding to the data in the multiple dimensions from the server, and displaying the enterprise information. The enterprise information query efficiency and the information response speed can be greatly improved.

The invention discloses an SA-CNN-BiLSTM-based intelligent substation virtual loop automatic generation method, which comprises the following steps: in an SCD file, extracting IED equipment information of historical IED equipment and virtual terminal information contained in the historical IED equipment, and storing the IED equipment information and the virtual terminal information in a historical SCD database; forming a semantic similarity model; and based on the semantic similarity model, finding a final historical IED equipment association pair corresponding to the to-be-designed IED equipment association pair, and instantiating the to-be-designed IED equipment association pair based on the final historical IED equipment association pair. According to the method, the virtual terminator information contained in the historical SCD file is rapidly extracted in a DOM mode and stored in the database in a classified mode, and the query and matching speed is remarkably increased. The semantic similarity model can effectively extract semantic features and endow the semantic features with higher weights, the semantic recognition success rate is high, and the method has a good effect in intelligent substation virtual connection automatic design.

The invention relates to a visual data processing method and device, computer equipment and a storage medium. The method comprises the steps that financial data are acquired and loaded to a pre-generated data form, and the data form is generated based on a data display demand; creating an associated view based on the asset structure information between the financial data, and extracting data from the data form by adopting the associated view; processing the extracted data to obtain to-be-displayed data; and loading the to-be-displayed data to a target data warehouse for display. By adopting the method, massive financial data can be quickly converted into display data meeting requirements according to user requirements, and a display result with high processing speed and high accuracy is provided for a user.

The present invention discloses a method for extracting and storing table contents with merged cells, S1, extracting table titles and table contents in a standard table by using a regular expression matching method; S2, defining cell attributes; S3, generating a tree structure of row titles and column titles according to the table title area; S4, marking the parent-child relationship between each node as a connection relationship between a parent node and a child node; marking the parent-child relationship between each node as a connection relationship between a parent node and a child node; S5, generating edge connections connecting row title nodes and column title nodes one by one according to row title nodes and column title nodes corresponding to their positions; S6, using a leaf node list of a row title tree structure and a leaf node list of a column title tree structure as row and column dimensions of a final graphic structure respectively; S7, storing the generated graphic structure in a data storage system. The present invention can make more valuable use of the data in the table by extracting the table in the standard specification.

The present application proposes an information acquisition method, device and electronic device. The information acquisition method includes: obtaining identification information of the information to be acquired; querying the information to be acquired in parallel in multiple sub-caches in the cache based on the identification information; in response to the existence of at least one candidate sub-cache storing the information to be acquired, obtaining the priority of the candidate sub-cache, determining the candidate sub-cache with the highest priority as the first target sub-cache, wherein the priority of the sub-cache is negatively correlated with the amount of information stored; and acquiring the information to be acquired from the first target sub-cache. Thus, the information to be acquired can be queried in parallel in multiple sub-caches based on the identification information of the information to be acquired, which effectively improves the query speed of the cache, and can acquire the information to be acquired from the candidate sub-cache with the least amount of stored information, which effectively shortens the information acquisition time and reduces the power consumption required for information acquisition.

The invention discloses a data security management method based on artificial intelligence, and belongs to the technical field of data processing, and the method comprises the following steps: S1, calculating a storage management demand for to-be-managed data according to a database for storing the to-be-managed data; s2, performing reading operation on the to-be-managed data, and generating a multi-dimensional data set for the to-be-managed data; s3, generating a security encryption key by using the storage management requirement of the to-be-managed data and the multi-dimensional data set; and S4, encrypting the to-be-managed data by using the security encryption key to complete security management. The encryption key is generated by combining the storage management requirement and the multi-dimensional data set, the complexity and the uniqueness of the key can be ensured, the generation strategy of the encryption key can be dynamically adjusted according to the change of the storage management requirement, and the flexibility and the expandability of safety management are considered.

The present invention discloses a log aggregation query method for massive data, including: log collection: collecting different types of log data from a server; processing the data fields in the log using a dynamic and static combination field to obtain processed data; analyzing the processed data using a cold-hot separation model to obtain cold and hot data, and shunting the cold and hot data into a database; first performing log query through a hot database, and then performing log query through a cold database. The present invention shuns log data by using dynamic and static combination field processing and a cold-hot separation model. When querying, the user directly queries from the hot data, which greatly reduces the query scope, reduces the magnitude, and improves the overall query speed.

The invention discloses a social network rumor suppression method and system based on a sphere domain index, and relates to the technical field of social network information processing. For the NP-hard characteristic of a rumor suppression problem under a competitive independent cascade model and the defect of high calculation cost of a traditional algorithm, efficient response under a multi-query scene is achieved through three-step progressive algorithm design. The method comprises the following steps: firstly, proposing an HMP-TC algorithm, replacing a forward sampling process in mixed sampling with typical cascade, and depicting a stable structure of rumor propagation; secondly, proposing an HMP-LB algorithm, constructing a landmark index structure based on point coverage, only maintaining influence ball domain information for index nodes, and correcting deviation through a probability weight; and finally, proposing a PTC-LB algorithm, introducing a protection sphere domain index formed by protection typical cascade and protection relation samples, and realizing non-sampling rapid optimization in a query stage. According to the method, on the premise of maintaining 90%-95% of rumor blocking effect, the single query speed is increased by 10-30 times, part of scenes can reach two orders of magnitude, and the quick response problem of rumor suppression in a large-scale social network is effectively solved.

The present application discloses an underwater noise processing method, device, equipment and medium. The method comprises: in response to an underwater noise processing request received in real time, converting the latitude and longitude coordinates of the noise source entity and the detection entity in the target sea area contained in the underwater noise processing request into simulated geographic grid coordinates respectively; calculating the grid standard distance corresponding to the noise source entity and the detection entity according to the simulated geographic grid coordinates; and determining the underwater noise value corresponding to the grid standard distance according to the grid standard distance. The embodiment provided by the present application maps the target entity to the simulated geographic grid, simplifies the calculation of the grid standard distance between the target entities, and then uses the grid standard distance to determine the underwater noise value corresponding thereto, avoiding multiple repeated calculations, saving a lot of calculation time, and thus improving the response speed of the system.

The invention relates to an atmospheric ocean data retrieval optimization method and device based on a column database. The method comprises the following steps: carrying out multi-dimensional on-demand cutting extraction and data decoding on historical atmospheric ocean data; in the element dimension, performing data storage and element dimension data retrieval optimization in a determinant database through a single element data table obtained by element segmentation; in the spatial dimension, data storage in a determinant database is extracted through metadata information, and spatial dimension data retrieval optimization is carried out based on constructed spatial codes; in the time dimension, time codes obtained through time discretization subdivision are subjected to data storage in a determinant database and time dimension data retrieval optimization; on the basis of atmospheric ocean data retrieval optimization of element dimensions, spatial dimensions and time dimensions, data storage is further carried out based on data blocks with fixed sizes. By adopting the method, the retrieval and access efficiency of massive historical atmospheric ocean data can be improved.

The invention discloses a block chain transaction data acquisition method, which comprises the following steps that: a server initiates a data acquisition initial request to a block chain, when the server receives a response returned by the block chain, the server generates a transaction data item and a new data acquisition request and synchronizes the transaction data item and the new data acquisition request to synchronous middleware, and the synchronous middleware constructs a request tracking tree; the synchronization semaphore is calculated in the request tracking tree according to the completion condition of each data acquisition sub-request, so that the downstream processing unit can know the acquisition progress of the transaction data through the synchronization semaphore, the transaction data can be processed or stored after all the data in the block are acquired, and the response efficiency of the downstream processing unit is improved; according to the further embodiment, the invention further provides a scheme for performing path compression on the request tracking tree, the query speed is increased, and the storage memory of the request tracking tree is reduced.

The invention discloses an intelligent term data management system based on machine learning. The intelligent term data management system comprises the steps that multi-source data are collected through a data collection module, the data are preprocessed, the preprocessed data are subjected to related storage, and the data are orderly and effectively stored through a table structure in the storage process; the method comprises the following steps: receiving query requests from different users through a query request module, analyzing the query requests into query tasks, intelligently scheduling and optimizing the query tasks by using a query optimization algorithm through an intelligent query engine to obtain query results, and returning the query results to the users through a result feedback module. And receiving feedback data of the user, acquiring the feedback data and historical query data of the user through the learning module, and continuously training and updating the query model according to the feedback data and the historical query data of the user.

The invention relates to the field of knowledge graphs, and discloses a bitmap-based graph data storage and query method, system, device and medium, the method adopts a unified bitmap model to store graph data, converts graph structure data into a bitmap suitable for parallel computing, maps a graph query request into a bitmap operation expression tree, and stores the graph data in the bitmap operation expression tree; therefore, graph query is converted into bitmap operation, and the query performance of high-concurrency and complex graph query is remarkably improved; moreover, a reasonable computing resource scheduling decision is dynamically set according to an input graph query request, and for high-concurrency and complex graph query, thousands of cores of a large-scale parallel computing engine are used for parallel processing, so that the random access bottleneck and the CPU computing power bottleneck of traditional graph traversal are thoroughly avoided, the query speed of order of magnitude can be increased, and the query efficiency is improved. A plurality of complex atlas analysis queries can be processed at the same time, and the real-time requirement of complex atlas query can be met.

The invention discloses a time sequence database label management method which specifically comprises the following steps: S1, label definition: defining a plurality of labels for data in a time sequence database, each label comprising a label name and a label value; and S2, label storage: storing the defined labels in a label table of a time sequence database, wherein the label table comprises fields of label names, label values, data pointers, creation time and update time. According to the time sequence database label management method, labels are defined and updated according to actual requirements, service changes are adapted, a label table contains rich fields, the full life cycle of the labels is convenient to manage, data and label association modes are diversified, data classification is clearer, meanwhile, a flexible query interface is provided, a user can perform multi-dimensional query, and the user experience is improved. The data pointers are used for quickly positioning the data, the query efficiency is improved, the management strategy can be optimized through tag statistics, and the database performance is improved.

The invention discloses a historical data archiving implementation method and device and a medium. The method comprises the following steps: creating a system architecture and a table; under the condition that table creation is completed, archiving conditions are configured; under the condition that the archiving condition configuration is completed, the archiving task is executed regularly; and aiming at the execution process of the archiving task, the query function is optimized. The method has the beneficial effects that the comprehensive functions of reducing the data volume of the table, improving the query performance, supporting flexible condition configuration, reducing the storage space occupied by the table, avoiding associated data migration, querying archived historical data, querying archived and unarchived total data and periodically deleting useless data through configuration are realized.

The invention belongs to the technical field of deep learning, and discloses a Visual-Transform network-based small object feature extraction method, which comprises the steps of 1, performing global feature extraction based on a self-attention mechanism, fusing self-attention feature learning into 3D feature extraction network construction, and effectively combining the self-attention feature learning with a convolutional neural network to obtain a 3D feature extraction model; more detailed target information is reserved in the shallow network, and peripheral features outside the center of the target are filtered out; 2, based on a key point sampling model of prior information, dividing an original point cloud space into four equal parts, carrying out parallel calculation on the position of each point in a candidate region, directly discarding points outside the candidate region, and only calculating the characteristics of key points in the candidate region; and step 3, fusing the global features and the local features, extracting the local features by using the global features to provide prior information, and then integrating the local features into a global feature map of a three-dimensional space. According to the invention, self-attention three-dimensional object representation is realized.

The invention discloses an industrial formula and process knowledge answer generation method and device, and the method comprises the steps: forming a field knowledge graph oriented to industrial formula and process knowledge according to an entity set and a relation set; establishing an inverted index according to node attributes and edge attributes of the domain knowledge graph; coding and retrieving nodes and edges of the domain knowledge graph according to the inverted index and a query embedding vector generated by a user input question to obtain an optimal sub-graph; and inputting the user input question subjected to text coding and the optimal sub-graph subjected to graph coding into a preset large language model to generate an answer containing self-certification information. According to the invention, automatic data processing and knowledge graph construction reduce the demand of manual intervention, and reduce the construction and maintenance cost; and the reverse index and the efficient retrieval algorithm are introduced, so that the query speed is increased, and the system can quickly respond to user requirements.

The embodiment of the invention discloses a data query method, computer equipment and a program product, and the method comprises the steps: obtaining a first query request of first data, the first query request comprises a target business query identifier, the target business query identifier comprises any one or more of a plurality of identifiers, and the plurality of identifiers comprise a user identifier and a business identifier; determining a target storage position of the first data based on the target business query identifier; and querying the first data in the target storage position. Data query in a high-concurrency scene can be realized, and rapidity and stability of data query are ensured.

The present invention relates to a query system based on data analysis, and in particular to the technical field of database management. The query system comprises a user information management module for implementing dynamic authority management for users, a data source management module for managing user requests, caches, data sources and data security, and a database management module for managing a number of databases. The present invention analyzes the query request of the user to determine whether the user request exists in the cache, so as to determine the selection of the query mode for the query request, thereby making flexible selections in the query process, and setting different supervision strengths in the corresponding query mode to supervise the query process, thereby improving the accuracy of control over the data query process.

The present invention discloses a hybrid mode API knowledge graph adaptive construction and intelligent question-answering method. The content of the method includes: based on Stack Overflow platform question discussion, Github open source project, network software library API description document, local project collection API information and knowledge extraction to build API knowledge graph; adaptive training hybrid mode API knowledge graph query model; query user uses hybrid mode knowledge graph query to query API information through natural language description; build a structure partitioned visual API information display page. The present invention solves the problems of low accuracy, slow speed, low content richness and unintuitive presentation when using natural language description query in traditional API query. The hybrid mode knowledge graph API query method provides query users with more accurate, richer content and more intuitive API information, thereby improving the development efficiency of programmers.

A credit evaluation method for construction industry enterprises relates to the field of informatization, characterized in that the method comprises the following steps: standard modeling: data analysis in index extraction, forming a standard model library; data aggregation: real-time detection of the qualification of the evaluation object and the evaluation user through unified authentication, forming the final evaluation data; data aggregation of the current evaluation period; special evaluation: executing the final evaluation data, index model and other data sources as parameters into the calculation engine for process log recording, obtaining the operation result and persistent storage. Advantage: by accessing different construction industry enterprise qualification credit evaluation standards, a unified standard index analysis is provided, mainly from the aspects of type, traceability length, data source, aggregation mode and the like. Through index data analysis, a data model of index extraction data is formed, and a standard index information is formed taking one type of information as an example.

The application relates to the technical field of data query, in particular to a query result acquisition method and device based on a large model and a medium, the method comprises the following steps: based on a preset large model, acquiring a result keyword sequence corresponding to a target result text output according to a target query statement, converting the result keyword sequence into target bitmap data of a bitmap data structure, and storing the target bitmap data in association with the target query statement in a preset database; when it is judged that the target query statement is received again, obtaining the corresponding result keyword sequence; based on the result keyword sequence, outputting a new result text through the preset large model, and taking the new result text as a current query result corresponding to the target query statement; by storing the logical relationship of the keywords in the query result, the application greatly reduces the occupation of the storage space, improves the query speed when repeatedly querying, and provides great convenience for repeated query of the user.

The invention belongs to the technical field of data storage, and discloses an airport machine room supervision agent data storage method and system. The method comprises the steps that structured data and unstructured data form a ternary entity relation group to be integrated, a unified knowledge graphical data structure is constructed, and a Neo4J graph database is selected as back-end storage; and a unified knowledge graphical data structure is stored in a Neo4J graph database, so that the query speed of the great relational supervision data of the airport machine room is improved, and subsequent supervision data analysis and function extension are facilitated. Besides, the method provides a unified query interface for the graphical data of the machine room, so that a user can conveniently retrieve and query the data, and meanwhile, powerful support is provided for fine management and intelligent development of the airport machine room.