250 results about "Field mapping" patented technology

The invention discloses an unmanned aerial vehicle outdoor inspection method based on multi-modal fusion, and the method comprises the following steps: obtaining the inspection data of an unmanned aerial vehicle, and carrying out the feature extraction and space-time alignment; calling a GNPDE algorithm, and constructing a multi-modal field mapping layer; constructing a structure-thermal field joint graph structure, and establishing a double-branch coupling solution structure; constructing a topological adaptive edge weight adjustment module, and dynamically modulating the edge weight by adopting a physical modulation function; introducing an energy conservation constraint layer, and executing constraint solution; a multi-scale PDE evolution algorithm subset is quoted and combined, and a scale weight sharing mechanism is adopted to complete cross-scale joint optimization; constructing an abnormal residual reasoning module, and generating an abnormal significance map; and performing spatial registration and superposition on the abnormal saliency map and unmanned aerial vehicle inspection data, and outputting an equipment-level inspection report and a risk level conclusion. According to the invention, the inspection abnormity identification precision and the structure-thermal field reasoning stability are improved.

The invention discloses an intelligent decision data inquiry system and method based on a generative large model, and belongs to the technical field of artificial intelligence. Natural language inquiry input by a user is received, and an inquiry intention and a target field are extracted; extracting structured and unstructured cost data from the real estate project database, and constructing a candidate field set; performing semantic matching by utilizing the generative large model to generate an intention field mapping matrix; constructing a field dependency graph based on a mapping result, and extracting a minimum closed-loop field set; performing credibility evaluation on the fields, and constructing a weighted field set; generating a dynamic query template, outputting a natural language answer, and attaching a field tracing path; if the field is missing or the credibility is insufficient, automatically generating a reverse query until a credibility requirement is met; according to the method, automatic association and accurate question and answer between complex semantic query and heterogeneous cost data are realized, and the method has good interpretability, traceability and intelligent interaction capability.

The invention discloses an intelligent accounting and analysis system for enterprise operation cost and expense, and relates to the technical field of intelligent accounting and analysis of enterprise operation, comprising a data preprocessing module used for obtaining original cost data from an enterprise ERP system, a financial system and a production management system, performing cleaning, field mapping and time sequence alignment operations on the original cost data, and outputting a structured unified data set; the deviation decomposition module is used for dividing a total cost deviation into four types of components, namely a usage difference, a price difference, an efficiency deviation and a structure migration deviation, based on a budget value and an actual value in the structured unified data set, performing attribution analysis according to a department, a product line or a project dimension, and outputting deviation detail data; and the weight calculation module is used for generating a dynamic weight vector according to the historical fluctuation characteristics of each cost item in the deviation detail data and the business association strength of the cost item in the enterprise operation in combination with an external market change signal.

The invention relates to the technical field of data integrity verification, in particular to a drug compliance detection method and system for drug supervision, and the method comprises the following steps: extracting a process change data field, eliminating a deviation value and setting a reference, marking and classifying a current batch difference field, recognizing a deviation expansion item, constructing a field mapping path and recognizing an interruption point. And judging whether the interrupt field is missing or not, and generating various result lists. According to the method, through medicine process parameter extraction and abnormal value elimination, a stable reference standard is constructed, representativeness of a comparison standard is guaranteed, classification is performed based on field differences, parameter offset is identified, difference identification precision is improved, continuous offset fields are judged in combination with trend changes, risk early warning timeliness is enhanced, and data inheritance continuity is expressed; according to the method, breakpoint fields are filled and verified, missing information is accurately captured, a closed-loop process of offset identification, trend research and judgment, path tracing and missing verification is integrally formed, and the integrity and sensitivity of data compliance inspection are improved.

The invention belongs to the technical field of enterprise informatization management and big data integration, and particularly relates to an enterprise informatization management integration platform based on big data. Comprising an auditing element unified structured acquisition module, a main body unique identifier analysis and failure closed loop module, a caliber version and field mapping version joint locking module and an evidence index binding and consistency verification packaging module. The platform reads interface and field mapping from a service system log according to a configuration table, normalizes the interface and field mapping and writes the interface and field mapping into an event account book collocation state; executing main body gating on the original entry record to generate a main body identifier and writing back the main body identifier; when failure occurs, the reason code is written and blocked, and the failure evidence index is returned; performing node analysis on the aperture script and generating an aperture chain fingerprint; and serializing the event segments, calculating abstracts, constructing batch abstract roots, positioning first inconsistent serial numbers when recalculation is inconsistent, and scheduling and supplementary collection, so as to output a recheckable audit evidence packet. According to the invention, aperture consistency and evidence traceability can be realized.

The invention discloses a business data modeling method and system based on metadata, and relates to the technical field of business data management.The method comprises the steps that a standard field list is created; creating a business object; extracting table structure metadata from the database to obtain a physical table field; establishing a field mapping matrix between the physical table field and the standard field list; and generating a business data model based on metadata according to the business object and the field mapping matrix. According to the scheme of the invention, the business model is constructed on a unified standard field, and scattered, disordered and difficult-to-understand physical data in an enterprise can be systematically converted into high-quality data assets which are clear in responsibility, unified in meaning, clear in relation and traceable.

The invention provides an AI-based policy analysis and enterprise intelligent matching method and system, and the method comprises the steps: mapping original policy elements of a policy text to a structured rule template, and generating a policy situation model; carrying out AI identification on enterprise information of a target enterprise input by a user, and generating an enterprise standard portrait; performing field mapping on the enterprise standard portrait and the access condition of the policy situation model to determine a policy set; performing weighted calculation on the matching fields of the policy set based on the matching factor of the policy situation model, and generating a matching value of each policy in the policy set for the target enterprise; and binding the matching value with the identification information of the target enterprise to generate an enterprise policy matching result. Through implementation of the scheme of the invention, the original policy elements are mapped to the structured rule template to generate the policy situation model, the enterprise standard portrait is constructed, and in combination with access condition logic judgment, accurate matching of the structured logic model is realized, and the accuracy of enterprise policy recommendation is effectively improved.

A vehicle infrared radiation simulation method based on temperature field mapping comprises the following steps: S1, performing thermal influence analysis on an original vehicle model to generate a simplified vehicle model; s2, grid division is carried out on the simplified vehicle model, and a temperature field of the simplified vehicle model is solved by adopting a numerical analysis method; s3, respectively extracting node coordinates of the original vehicle model and the simplified vehicle model, respectively calculating geometric centers of the original vehicle model and the simplified vehicle model, and realizing spatial registration of the original vehicle model and the simplified vehicle model through translation transformation; s4, mapping the temperature value of the simplified vehicle model to a corresponding grid node of the original vehicle model by adopting a KNN algorithm based on a KD tree and combining an inverse distance weighted interpolation algorithm; and S5, on the basis of the mapped original vehicle model temperature field data, in combination with the material emissivity and the environmental radiation parameters, calculating the infrared radiation characteristics through a ray tracing method. According to the method, the calculation efficiency can be remarkably improved while the simulation precision is ensured, and the advantages are obvious.

The invention discloses a data leakage detection method and device, computer equipment and a storage medium, belongs to the technical field of data security, and is applied to sensitive data detection of a financial system or a health medical system. Firstly, the authenticity and complexity of a test sample are remarkably improved, various scenes such as format change, field splitting, encryption processing, noise interference and semantic camouflage are covered, and a complex attack environment can be effectively simulated; secondly, an adaptive field mapping and dynamic test template mechanism is introduced, so that test data can be flexibly adjusted according to different service scenes or detection products, and the test efficiency and scene adaptability are improved; and finally, through presetting various machine learning algorithms, automatically training to generate a high-precision sensitive data classifier, and realizing accurate identification of sensitive fields in unknown data. According to the method, a set of end-to-end sensitive data detection and evaluation framework capable of being automatically executed is constructed, and the method has the technical advantages of high efficiency, flexibility and intellectualization.

The invention discloses a query method and device adaptive to multiple types of databases and a storage medium, and relates to the technical field of data processing. According to the method, the target query mode is determined by matching the keyword node combination in the abstract syntax tree with the query mode list, the problem that table names and field names of different databases are inconsistent is solved through the field mapping table, and finally, the target database is queried according to the syntax rule of the target database. According to the method, the target query mode is instantiated into a specific grammar conforming to the target database, and correct target table names and target field names are filled in, so that new query statements of which grammar and semantics are adaptive to the target database are generated, and adaptive conversion of the query statements of different types of databases is realized.

The invention relates to the technical field of furnace temperature control, and discloses a furnace temperature intelligent control device and method, and the device comprises a multi-source sensing temperature field construction module, a thermal state process inversion module, a target temperature field mapping generation module, a multi-target dynamic optimization module, a control instruction resolving mapping module, and a rolling execution optimization module. Interpolating the multi-source heterogeneous sensing data to obtain a three-dimensional thermal temperature field; performing inversion on the three-dimensional thermal temperature field to obtain a current material reaction process state; mapping to a preset process knowledge graph to obtain a target temperature reference and a distribution rule so as to construct target temperature field distribution; solving by combining thermodynamics-heat transfer constraints of the furnace to obtain a global optimal dynamic transition trajectory; mapping the global optimal dynamic transition trajectory to obtain an accurate energy input instruction set; fusing newly acquired real-time data to update three-dimensional temperature field distribution, and reconstructing a track to obtain an updated control strategy; according to the invention, the accuracy of intelligent control of the temperature of the furnace can be improved.

The invention relates to the technical field of big data, and particularly discloses a natural language and semantic mapping-based business data model automatic construction method, which comprises the following steps of: performing structured analysis on a natural language demand input by business personnel, and extracting a dimension entity, a measurement index and a user intention; performing semantic matching on the business terms and the metadata fields by using a Sentence-BERT sentence vector model to generate a field mapping list; constructing a data consanguinity map based on a historical SQL, and reasoning an optimal multi-table association path through a shortest path algorithm by taking a center table as a root node; automatically generating a target wide table structure definition and a complete SQL (Structured Query Language) code by combining a template engine; and performing grammar and logic consistency verification on the output statement. According to the method, full-automatic, high-precision and interpretable end-to-end modeling from natural language requirements to executable wide tables can be realized, the data modeling efficiency and accuracy are remarkably improved, and the participation threshold of business personnel is reduced.

The invention relates to the technical field of data migration and synchronization, in particular to a heterogeneous database real-time incremental synchronization method and system for cloud migration, which can capture a change log stream of a local source database in real time by arranging a plug-in, analyze and reconstruct the change log stream into a uniform event change model, and improve the data migration and synchronization efficiency. According to the method, data processing capabilities such as field mapping and type conversion are completed, functions such as table structure synchronization, writing into a cloud target database and processing and fault-tolerant mechanism aiming at abnormal conditions are realized, and automatic scheduling is realized through a DSServer scheduler, so that efficient, stable and reliable synchronization of cloud migration on a cross-platform database is realized, and the cloud migration efficiency is improved. Low-delay and high-consistency data synchronization from the source database to the target database is achieved, smooth transition of a service system in the migration process is ensured, and the method is particularly suitable for micro-service architecture environments of large complex systems such as a power grid.

The application is suitable for the technical field of data processing, and provides a database query method, system, device and medium based on natural language. The method comprises the following steps: acquiring a natural language text; based on the natural language text and a field library, calling a root matching strategy, a semantic matching strategy and a fuzzy matching strategy through a hierarchical cooperation mechanism to perform field mapping and determine a target field; splicing the target field to obtain an initial semantic query statement; loading and executing multiple correctors in sequence through a service discovery mechanism to obtain a target semantic query statement; converting the target semantic query statement to obtain a target physical query statement; executing the target physical query statement to obtain a target query result and return the query party. Through hierarchical cooperation of the root matching strategy, the semantic matching strategy and the fuzzy matching strategy, the application improves the scalability and adaptability of the matching strategy, improves the field recognition accuracy, expands the field matching range, and optimizes the matching efficiency.

A data pipeline orchestration tool facilitates the creation of re-useable aggregate components that can be created during building of new data pipelines or integrated into existing data pipelines and manages the placement and connection of aggregate components within an existing pipeline. The aggregate components utilize virtual components as connectors to other data pipeline components, which include a virtual source and / or a virtual sink. The virtual source maps a specific schema of a source of data to be processed by the aggregate component, such as specific fields of a database table, with a generic schema of the virtual source. The virtual sink designates the flow of data from the aggregate component to one or more downstream components of the data pipeline. Aggregate components can also be stored in a component library or other component storage offered by the data pipeline orchestration tool to facilitate reuse of aggregate components across data pipelines.

The invention relates to the technical field of big data access control, and discloses a cross-component metadata access control method and device for a credential big data platform, and the method comprises the steps: firstly constructing a metadata virtualization layer used for mapping a plurality of metadata databases, and enabling the metadata virtualization layer to map the plurality of metadata databases; subsequent cross-database field mapping and result aggregation operation can be realized on the metadata virtualization layer, so that each database does not need to be accessed independently, and efficient cross-component access operation is realized. According to the method, the authentication key is designed into the retrieval segment and the key segment, the retrieval segment is only used for retrieving and distinguishing the key, the user side and the metadatabase respectively send the respective key segment to the metadata virtualization layer, and unified authentication of the user side authority is realized through matching of the authentication key in the virtual mapping layer. And the user side does not need to perform independent authentication with each metadatabase, so that the metadata access control efficiency is improved.

The application discloses a feature interaction method and device based on dynamic graph constraints, which maps input feature fields into low-dimensional dense embedding vectors and forms an embedding matrix; the similarity between any two fields is obtained by calculation to form a dense similarity matrix; the micro Top-K algorithm is used for screening to obtain K most relevant neighbor fields of each field and assign weights to generate a field adjacency matrix; in a Transformer attention module, the field adjacency matrix is used as an attention mask, each field is interacted with K most relevant neighbor fields connected in the field adjacency matrix to obtain a graph-constrained high-order interaction result; in an FM module, a pair of second-order feature cross results are obtained by calculation; the second-order feature cross results are multiplied by corresponding weights to obtain a graph-constrained second-order interaction result; the two are fused and subjected to prediction processing to output a prediction probability. The application can solve the problems of existing technologies, such as more noise, low calculation efficiency and poor interpretability.

The present application relates to a kind of metadata-driven two-dimensional standard data automatic storage method, belong to coal mine informatization technical field, including the following steps: S1: construction metadata system and define two-dimensional standard data model specification, generate standardization data model specification document, the metadata system includes data structure metadata, constraint metadata and storage adaptation metadata, the model specification is clear two-dimensional data's row dimension rule and automatic storage trigger condition;S2: by ETL tool, establish target data with the dynamic mapping association of the data model specification, generate and include field mapping relationship, conversion rule and storage routing information's mapping configuration;S3: based on the data model specification and mapping configuration, trigger automatic storage process, including automatically parsing model specification generation storage structure, automatically match storage medium, automatically execute data write and check, realize the automatic storage of two-dimensional data.

The invention provides a test data generation method, a program product, electronic equipment and a storage medium. The method comprises the following steps: acquiring request data, aiming at a target function, of a user on a tested system and response data corresponding to the request data; the request data comprises a request field; the response data comprises a response field; comparing the request data with the response data, and determining an interface field mapping relation of the tested system; the interface field mapping relation is used for describing a corresponding relation between a response field of the tested system and a request field used for generating response data; obtaining configuration list data of the tested system, and converting the configuration list data of the tested system into test request data for the target function based on the interface field mapping relation; wherein the configuration list data comprises at least one piece of data expressed in the format of the response data. The process of independent development and data configuration for automatic testing is omitted, and the efficiency of automatic testing is improved.

This invention discloses a method for aligning fields based on structured parsing of overseas open-source information, relating to the field of data fusion and parsing. The method includes: acquiring raw data packets from overseas open-source platforms; performing structured parsing and field extraction on the raw data packets to generate a candidate field set; performing semantic recognition and field mapping on the fields in the candidate field set based on a dynamic cognitive network to generate a field mapping decision result; resolving and correcting the consistency of conflicting field values ​​mapped to the same standard field based on the field mapping decision result to obtain an aligned field set; and organizing the aligned field set into a unified structured record and outputting it according to the standard field model. This method achieves intelligent mapping and conflict resolution of cross-platform fields through an evolvable semantic network, possessing the ability to adaptively learn unknown fields, achieve deep semantic understanding, and output interpretable decisions, significantly improving the intelligence level and accuracy of multi-source information fusion.

The application relates to the technical field of data processing, and provides an account checking method, an account checking system, a computer and a storage medium. The account checking method comprises the following steps: obtaining a to-be-checked data set, cleaning the to-be-checked data set to obtain standard upstream billing data and standard downstream billing data; obtaining a field mapping rule, and respectively mapping the standard upstream billing data and the standard downstream billing data into to-be-checked upstream data and to-be-checked downstream data according to the field mapping rule; obtaining account checking scene parameters, constructing a multi-dimensional difference rule network, comparing the to-be-checked upstream data and the to-be-checked downstream data based on the account checking scene parameters and the multi-dimensional difference rule network to obtain a difference identification result; performing an abnormal category prediction on the difference identification result to generate an abnormal identification result, and generating an account checking report based on the abnormal identification result. Through the above method, the data of upstream and downstream business systems can be connected, and the low account checking efficiency and the flexibility and adaptability of the account checking can be improved.

The application relates to the technical field of computer programming, and discloses a Go language structure body automatic conversion method and system. The method first receives the definitions of a source structure body and a target structure body as input, automatically matches the fields of the two structure bodies according to preset rules through a field mapping rule engine, and generates a field mapping relationship; then, based on the field mapping relationship, a code generator is used to automatically generate conversion code containing field assignment and type conversion logic; finally, the generated conversion code is compiled into an executable conversion function, which can convert and fill the data in the source structure body instance into the target structure body instance according to the field mapping relationship during program running. The method realizes the automation of structure body conversion, avoids the error-prone problem of manually writing conversion code, improves the maintainability of the code, significantly improves the conversion efficiency by replacing the runtime reflection mode with code generation, and simultaneously supports batch conversion and concurrent processing, and can meet the performance requirements of large-scale data processing.

The application belongs to the field of dynamic combustion flow field mapping measurement, and specifically discloses a mapping-all-in-one test structure based on a mask technology, and designs a high-resolution, high-spectrum and high-dynamic-range thermal measurement system specially designed for solid rocket engines. The system can accurately measure and monitor the temperature distribution of the exhaust plume of the solid rocket engine by using advanced sensing technology and data processing algorithms. The system has excellent spatial resolution, high-spectrum measurement capability and high-dynamic-range response to rapid temperature changes. By providing accurate temperature data, the system provides key technical support for performance optimization, fault diagnosis and safety control of the solid rocket engine.

The application belongs to the technical field of network data transmission, and discloses a data internal and external network transmission method and equipment. The method comprises the following steps: in response to a transmission request of to-be-transmitted data, dividing the to-be-transmitted data according to fields; determining an encryption level according to the sensitivity level of the to-be-transmitted data; generating a plurality of key-value pairs by taking each field name as a key and taking field content as a value, to obtain structured data; mapping each field name into a field code according to a field mapping dictionary, and encrypting the field content according to the corresponding encryption level; and generating a message header comprising a field mapping dictionary identifier, an encryption level identifier and a data type identifier of the to-be-transmitted data; and packaging and transmitting the message header and the structured data. The application realizes the safe transmission of data between internal and external networks.

The invention discloses an insurance policy information management system and method, electronic equipment and a storage medium, and the system comprises an insurance policy information query module which carries out the unified authentication and routing arrangement of an insurance policy query request, and generates a target request; according to a configuration rule, obtaining insurance policy data from a plurality of data sources through the target request, and executing field filtering, field mapping, data desensitization and result sorting on the insurance policy data to generate a standardized query response; the configuration management module is used for carrying out visual configuration, storage and distribution management on the configuration rules; the security management module is used for carrying out encryption and decryption and signature verification on the transmission message and managing an encryption key and an algorithm suite; and the log auditing module is used for recording the operation logs and carrying out centralized storage and retrieval. According to the method, the problems of different query calibers, slow cross-system joint query, insufficient configuration and weak security compliance are solved, the query response speed and experience consistency are improved, the system reusability and configuration flexibility are enhanced, and the security compliance capability is enhanced.

The application relates to the technical field of real-time monitoring, in particular to a data background real-time monitoring processing method and system based on plug-ins, which comprises the following steps: obtaining an activated plug-in thread identifier, analyzing field output content to extract a name path and a write state to establish a mapping structure, pairing path fields to identify name coincident data groups, judging field write time window overlap and buffer channel consistency to extract conflict path numbers, processing field order and delayed writing and updating the write state, and obtaining a monitoring field processing state list; in the application, plug-in field mapping structure is constructed to bind fields and output paths, conflict paths are identified, write time windows and buffer channel consistency are compared, a field order comparison mechanism is established to control repeated field delayed writing, a field control state table is generated, a monitoring processing state list is output according to field attribution and a function block, field behavior and control information consistency is guaranteed, and monitoring data processing integrity and logical reliability are improved.

The application discloses a data quality management method and device, and belongs to the technical field of data processing. The data quality management method comprises the following steps: receiving a first input of a user, wherein the first input is used for inputting a target configuration; in response to the first input, a data model is constructed based on the target configuration; a data source corresponding to a target layer in a data warehouse is associated to a corresponding position of the data model and field mapping is performed; at least part of data in the data source corresponding to the target layer is checked based on a target data checking rule, and a quality checking report is obtained. The data quality management method can unify the data quality standard, ensure the consistency of data processing in the subsequent application process, unify the data storage structure, directly associate the data when the data of multiple systems is called, and realize the data sharing between different systems.

The application provides a multi-source heterogeneous data adaptive fusion and management method, relates to the field of data processing, and comprises the following steps: sampling data sources and analyzing sample data; extracting structural features and semantic features of the sample data to obtain data source fingerprints, and determining reference data sources; identifying fields and inferring types of the sample data to obtain metadata; performing semantic matching based on the metadata and preset target fields to generate a first mapping scheme, and performing feature matching calculation to generate a second mapping scheme; fusing the first mapping scheme and the second mapping scheme to obtain field mapping rules and comprehensive divergence; performing data conversion on the data sources according to the field mapping rules and performing quality evaluation to obtain quality scores; and adjusting a sensitivity coefficient according to the quality scores and the comprehensive divergence. The application realizes strategy migration and parameter adaptive optimization based on historical experience, and improves the automation degree and conversion quality of heterogeneous data fusion.

The embodiment of the invention provides a data migration method and computing equipment. Performing semantic retrieval on a plurality of second tables (belonging to a plurality of tables included in a second database) according to table information of the first table (any one of the plurality of tables included in the first database), and determining a target second table; the table information comprises a table splicing vector; the table splicing vector indicates a service function and positioning information of the first table; constructing a table mapping relation based on the first table and the target second table; performing semantic retrieval on a plurality of second fields included in a target second table according to field information of the first field (any one of the plurality of fields included in the first table), and determining a target second field; the field information comprises a field splicing vector, and the field splicing vector indicates a service function and positioning information of the first field; constructing a field mapping relation based on the first field and a target second field; and migrating data between the first database and the second database according to the table mapping relation and the field mapping relation. And the data migration efficiency is improved.

The invention discloses an automatic data set cleaning method and system for a large model in the geotechnical engineering field, and belongs to the technical field of data processing and artificial intelligence. The method comprises the following steps: acquiring multiple source files under a specified directory, reading multiple worksheet contents, and analyzing to generate an analyzed data table; performing structured verification and optimization on the analyzed data table, eliminating invalid rows and columns and recording dimension changes; performing multi-level standardization processing on fields in the data table, and generating a field mapping relation table; performing anomaly detection on the standardized fields; and outputting the standardized data set and the whole-process audit log. According to the method, the defects that traditional manual cleaning is low in efficiency and poor in consistency are overcome, high-quality and standardized structured data support can be provided for large model training in the geotechnical engineering field, and the efficiency and reliability of data preparation are remarkably improved.