21 results about "BASIC DATA STRUCTURE" patented technology

The invention discloses a big data relation mining analysis method based on a graph neural network, which comprises the following steps: S1, acquiring multi-source data, extracting data features, constructing a data relation graph, and mapping the data relation graph into a low-dimensional vector as a basic data structure; s2, inputting a low-dimensional vector through the graph neural network model, outputting a prediction result, calculating an error by using a loss function based on a real relation label, adjusting parameters of the graph neural network model, and obtaining a target data model; s3, obtaining a data relationship prediction result through the target data model, mining a data potential relationship, and mining a data relationship result through the data potential relationship; and S4, combining a data relationship result with domain knowledge and business rules, constructing a relationship knowledge base, and displaying the data relationship through a visualization technology. According to the method, efficient and accurate big data relationship mining is realized, and the accuracy and practicability of potential relationship discovery in a complex data environment are improved.

The invention discloses an unmanned aerial vehicle patrol and security monitoring linkage management method. According to the system, urban geographic information data and key monitoring area coordinates are acquired, hierarchical grid division is realized by using a quadtree spatial index algorithm, and a patrol task distribution basic data structure is established; solving an approximate optimal solution of the patrol path of the unmanned aerial vehicle by adopting an improved greedy strategy, and performing optimization adjustment according to technical parameters and weather conditions of the unmanned aerial vehicle; the unmanned aerial vehicle collects video data in real time through high-definition camera equipment in the patrol process, target detection is conducted through a deep learning model, and potential safety hazards such as personnel gathering and vehicle abnormity are recognized; detecting violent conflicts and illegal intrusion behaviors in combination with a time sequence analysis algorithm, and generating an abnormal event report; cooperative work of the unmanned aerial vehicle, the ground robot and the command center is realized; and a patrol scheme is dynamically adjusted according to meteorological conditions, and robot scheduling is optimized through energy consumption management.

The invention, which relates to the technical field of interactive script generation, discloses a script-centered interaction-driven scene generation system comprising the following modules: a script management module, a script arrangement module, a dependency propagation module, a thesaurus interaction cooperation module and an execution output module. Creating a basic data structure of the script, distributing script attributes, and managing script elements, constraints and logics; identifying scene nodes and events, constructing three-layer dependency and weighting, and generating a reverse causal chain through recursive dependency and depth-first search; by maintaining a dependency table, event-driven updating and dirty node marking for each node, efficient dependency propagation and low-delay updating are realized through a priority queue and differential generation; dividing three levels to cooperatively realize dynamic script generation and interaction, and realizing script control based on gating residual connection, a reverse causal chain and a time attention mechanism; and constructing an interactive execution layer, integrating a real-time feedback mechanism, automatically generating a script, and outputting and displaying an executable format.

The present application relates to the field of photovoltaic power generation, and more particularly to a double-sided photovoltaic tracking method and system based on a genetic algorithm. The method comprises: constructing a basic data structure based on multi-source data such as field station geographic time parameters and actuator constraint parameters; performing solar position and attitude geometric calculation to obtain solar geometric structure and candidate attitude geometric structure; inputting the solar geometric structure and the candidate attitude geometric structure into double-sided irradiation calculation to obtain front effective irradiation, back effective irradiation and shading factor; performing temperature calculation and electrical output calculation to obtain a candidate attitude power sequence and an energy index; performing fitness construction and feasible region processing to obtain a fitness evaluator and a feasible region processor; performing genetic algorithm calculation to output optimal strategy parameters and an angle curve, and generating a target angle instruction. The present application can realize collaborative evaluation and constraint optimization output of geometric, irradiation and electrical links, effectively improving the availability and stability of control instruction generation.

The application relates to the technical field of data processing, and discloses a parking behavior analysis method and system based on data mining and a storage medium. The method comprises the following steps: collecting data through a parking sensor network to construct a parking behavior basic data structure, a local interest point database and a global network configuration database; adopting a local-global feature interaction matrix algorithm to perform fusion processing to obtain a fusion feature matrix and a dynamic weight vector; performing clustering through a fusion density clustering algorithm to obtain a fusion clustering result matrix; and performing pattern recognition based on double-layer space-time mode mining to obtain a parking behavior space-time fusion mode library and a demand prediction result. The application solves the technical problem that an existing parking behavior analysis method based on data mining cannot effectively fuse local interest point features and global network configuration features, leading to a lack of significant correlation between analysis results and actual parking use modes.

The invention discloses an enterprise knowledge base construction method based on SaaS private deployment, and particularly relates to the technical field of enterprise knowledge base construction. The method comprises the following steps: firstly, deploying a knowledge base system in a private server or a private cloud environment, and establishing a basic data structure of users, roles, permissions and resources; constructing a permission graph structure of multiple types of nodes and edge relationships thereof based on the entities, introducing a role sensitivity coefficient and a role permission overlapping degree as node features, performing representation learning on the nodes by adopting a graph neural network model, and training the model in a self-supervision mode to generate a user access risk score; when the score is higher than a preset threshold value, triggering an access path analysis and strategy optimization suggestion generation mechanism, dynamically adjusting permission configuration, and synchronously writing an update result into a graph structure to realize closed-loop identification and optimization of permission risks; the method has the advantages of being high in visualization, accurate in recognition, fast in response and the like, and the intellectualization and safety of enterprise authority management are remarkably improved.

The invention relates to the technical field of data processing, in particular to a component data processing method, system and equipment supporting multi-type expansion, and the method comprises the steps that a basic data structure is defined, the basic data structure comprises a basic field and an expansion attribute field, and the basic field comprises a component type; receiving component data which is submitted by the front end and is represented based on the basic data structure; analyzing a component type in the component data; and according to the component type, routing the component data to a corresponding component processor based on a preset policy factory, and processing and storing the component data through the component processor. Thus, through the scheme provided by the invention, remarkable comprehensive beneficial effects can be generated in the aspects of unifying data processing, facilitating function extension, improving development efficiency and guaranteeing system stability.

The embodiment of the invention discloses an intelligent construction method and system for a semantic path structure of a conversation record, and aims to solve the problems that key semantic elements in the conversation record are dispersed and are difficult to structurally associate, and a general model is difficult to adapt to specific semantics in the field. The method comprises the following steps: carrying out analysis and role identification on a conversation text; extracting five types of elements including figures, behaviors, events, time and places from each statement based on a domain behavior ontology library to form a quintuple semantic unit; linking elements in the units according to the semantic dependency and the context relationship to generate a chained semantic path; fusing context information to generate vectorized representation of the path; and finally, outputting a storable and visualized semantic path structure. According to the method, an unstructured text is converted into a unified and computable chain semantic expression, and a basic data structure is provided for consistency analysis, conflict detection and evidence chain generation of conversation records.

The embodiments of the present disclosure disclose a method, device, and electronic device for picking goods. A specific implementation of the method includes: querying the location information of the goods to be picked from a goods location database based on the identification of the goods to be picked, wherein the data in the goods location database is stored in a multidimensional data structure, and the multidimensional data structure includes multiple basic data structures, each basic data structure is used to store a key-value pair consisting of the identification and location information of a goods in the warehouse, and each basic data structure is also configured with at least three sets of bidirectional linked lists, and the at least three sets of bidirectional linked lists are used to identify the relative position of the goods relative to the surrounding goods; the location information is sent to the picking device so that the picking device runs to the position corresponding to the location information and picks the goods to be picked. This implementation method improves the efficiency of picking goods.

The invention provides a dynamic sampling and secure storage method for semi-structured data. The dynamic sampling and secure storage method comprises the following steps: reading to-be-sampled semi-structured data from a data source; determining the data type of the to-be-sampled semi-structured data and analyzing the data structure of the to-be-sampled semi-structured data; determining a first semi-structured sampling algorithm according to the data type, the data structure and a preset sampling requirement; determining the total sampling amount according to the to-be-sampled semi-structured data; inputting the read to-be-sampled semi-structured data and the total sampling amount into a first semi-structured sampling algorithm, executing the first semi-structured sampling algorithm, and completing sampling to obtain sampled sample data; determining a first encryption algorithm, and encrypting the sampled sample data; obtaining a sampling data object according to a preset sampling basic data structure; and the sampling data object is integrated, stored or transmitted, so that the technical effects of improving the flexibility and accuracy of semi-structured data sampling and ensuring the safety and traceability of the sampling data are achieved.

The invention relates to the technical field of data storage and recovery, and provides an electro-hydraulic actuating mechanism small PLC data storage method, which comprises the following steps: acquiring operation data generated during debugging of a small PLC of an electro-hydraulic actuating mechanism in real time; preprocessing the operation data to obtain a plurality of operation data segments; performing feature extraction on the operation data segment through a self-supervised learning model to obtain key features; processing the key features through a double-layer generative adversarial network to obtain a basic data structure and reconstruction data; and storing the basic data structure and the reconstructed data in a classified manner. According to the method, the precision and efficiency of data storage are improved, and the storage strategy can be dynamically adjusted according to the importance and complexity of the data, so that the utilization rate of storage resources is optimized, and redundant storage is reduced. And the reliability and the safety of long-period operation of the electro-hydraulic actuating mechanism in an industrial application site are further improved.

The application relates to a kind of test data management and control methods based on service data construction, comprising: establishing service basic data structure model;Establishing service basic test data link model;According to test data number generation service, generate original test data;Based on original test data, set key field identification sensitive information;Non-original test data declaration and declaration audit;Actual test data application control, actual test data is sequentially carried out sensitive information identification, original check and non-original check, and check through test data and check not through test data are determined;Based on service basic test data link model, check not through test data is carried out full-link tracing and destruction.Compared with prior art, the application can actively and accurately identify sensitive test data, and trace and process sensitive test data link to improve the persistence and availability of business test data.

The invention provides a cache simulation model and a construction method thereof, a white box verification platform and a related product. The cache simulation model comprises a cache configuration module, a cache basic data structure module, a cache container module and a cache model module. Parameter information of a to-be-simulated cache is recorded in the cache configuration module, basic data of the to-be-simulated cache is recorded in the cache basic data structure module, and the cache configuration module and the cache basic data structure module are instantiated in the cache container module; the cache container module is used for constructing the cache basic data structure module into a data structure specified by the parameter information according to the parameter information in the cache configuration module; the cache container module is instantiated in the cache model module, and a cached operation function is configured in the cache model module. According to the method, the construction universality of the cache simulation model can be improved, the construction difficulty of the cache simulation model is reduced, and the white box verification efficiency is improved.

The application relates to the technical field of power system grid engineering management, and discloses a data management method and system based on a GIM model, which comprises the following steps: acquiring GIM model data; importing the GIM model data into a database to obtain database data; performing data recognition and judgment operations on the database data to obtain a recognition result, and performing attribute relationship matching operations according to the recognition result to obtain structured data; extracting attribute conditions and relationship conditions related to a current business demand type of the structured data, and determining the attribute conditions and the relationship conditions as query conditions; performing index query classification operations on the structured data according to the query conditions to obtain a final main data set; and performing initialization and data loading operations according to the final main data set to obtain a basic data structure and a complete data set supporting visual display of power grid engineering business. The method can solve the problems of intuitive expression and unified management of three-dimensional data of power grid engineering.

The present invention relates to the technical field of data preservation and recovery, and provides a method for preserving data of a small PLC of an electro-hydraulic actuator, comprising real-time collection of operating data generated by a small or medium-sized PLC of an electro-hydraulic actuator during debugging; pre-processing the operating data to obtain multiple operating data segments; extracting features from the operating data segments through a self-supervised learning model to obtain key features; processing the key features through a two-layer generative adversarial network to obtain a basic data structure and reconstructed data; and classifying and preserving the basic data structure and reconstructed data. The present invention improves the accuracy and efficiency of data preservation, and can dynamically adjust the storage strategy according to the importance and complexity of the data, thereby optimizing the utilization of storage resources and reducing redundant storage. This further improves the reliability and safety of the long-term operation of electro-hydraulic actuators in industrial application sites.

This invention specifically relates to a key-value separation storage method and system. This method and system uses an ART prefix tree as the basic data structure for data indexing. Within each data node, space is allocated separately for storing the key and value, and the corresponding SequenceNumber and ValueType are stored within the node, thus achieving key-value separation. No encoding is performed during data storage; the key, SequenceNumber, ValueType, and value are directly stored and retrieved. This reduces I / O throughput, increases CPU cache hit rate, and improves database read / write performance. Furthermore, this key-value separation storage method and system eliminates the need for decoding information during data read / write operations; information can be directly obtained using the node, reducing disk I / O consumption, lowering I / O throughput, increasing CPU cache hit rate, and improving database read / write performance.

The application discloses a script-centered interactive driving scene generation system and relates to the technical field of interactive script generation, and specifically comprises the following modules: a script management module, a script arrangement module, a dependency propagation module, a narrative control interactive cooperation module and an execution output module; basic data structures of scripts are created, script attributes are distributed, script elements, constraints and logics are managed; scene nodes and events are identified, three layers of dependencies are constructed and weighted, reverse causal chains are generated through recursive dependency and depth-first search; dependency tables are maintained for each node, event-driven update and dirty node marking are performed, efficient dependency propagation and low-latency update are realized through a priority queue and differential generation; three levels of cooperation are divided to realize dynamic script generation and interaction, script control is realized based on a gated residual connection, a reverse causal chain and a time attention mechanism; an interactive execution layer is constructed, a real-time feedback mechanism is integrated, automatic script generation is realized and an executable format is output and displayed.

The invention relates to the technical field of power system power grid engineering management, and discloses a GIM model-based data management method and system, and the method comprises the steps: obtaining GIM model data; importing the GIM model data into a database to obtain database data; performing data identification judgment operation on the database data to obtain an identification result, and performing attribute relation matching operation according to the identification result to obtain structured data; extracting attribute conditions and relation conditions of the structured data related to the current business demand type, and determining the attribute conditions and the relation conditions as query conditions; according to the query condition, performing index query classification operation on the structured data to obtain a final main data set; and performing initialization and data loading operation according to the final main data set to obtain a basic data structure and a complete data set which support visual display of the power grid engineering business. According to the method, the problems of visual expression and unified management of three-dimensional data of the power grid project can be solved.

The invention discloses an XML (Extensible Markup Language) serialization and deserialization implementation method based on a Qt meta-object technology. The method comprises the following steps of: defining a basic data structure for describing an xml (Extensible Markup Language) node; the method comprises the following steps: defining an XML document structure needing to be serialized and deserialized into a class; declaring data items needing to be serialized and deserialized through attribute definition macros provided by Qt to ensure that relevant information is added into the meta-object system of the class; wherein the basic data structure should comprise an XML (Extensible Markup Language) document structure initialization process; generating an XML document structure according to XML node types represented by the attributes and association relationships among the attributes, filling attribute values contained in the class instances into the XML document structure, and generating an XML data stream; reading the XML data stream, searching the value of the specific node name in the XML data stream according to the document structure, filling the value into the attribute corresponding to the node name, and simplifying the definition of the XML file structure.

The invention discloses an open world standardization processing method and system, and the method comprises the following steps: S1, dividing an open world scene into a plurality of logic tiles, abstracting all to-be-managed scene objects into a unified basic data structure, and forming tile data associated with the logic tiles; s2, in a working thread independent of a main thread, based on the tile data, executing hierarchical loading, unloading management and integrated data rejection for the logic tiles; and S3, synchronizing the rendering data processed by the working thread to a main thread, and calling a graphic engine interface by the main thread to instantiate and render. According to the application, the load of a main thread is remarkably reduced, a unified data abstraction and tile management framework is realized on the architecture, different modules such as physical modules, illumination modules and audio modules can be accessed in the same normal form, redundant codes are eliminated, and the system complexity is reduced.

The invention provides a format-independent oil reservoir model post-processing general agent interface method. The method comprises the following steps: step 1, customizing analysis engine agent models of different numerical simulation software and a public access interface; 2, accessing a plurality of model analysis engines, and loading and analyzing different types of simulator data results; 3, storing the analyzed numerical simulation result data to a unified model basic data structure; 4, accessing the model data through a public interface of the oil reservoir model; and step 5, obtaining various model data through the step 4, and developing business applications such as data statistical analysis, visual rendering function and model comparative analysis. According to the format-independent oil reservoir model post-processing general agent interface method, supported simulation software types can be increased or decreased at will under the condition that upper-layer statistical analysis and visual rendering functions are not modified, and format independence and development isolation are achieved.