839 results about "Relational database" patented technology

The invention relates to a multi-modal data and RAG technology fused power design knowledge base construction method, and belongs to the technical field of power software development. The method comprises the following steps: carrying out collection and information extraction on multi-source heterogeneous original data; the method comprises the following steps of: constructing a multi-dimensional knowledge element structure containing parameters, specifications and case relationships by carrying out classification, specialized and precise processing and cross-modal association on data; based on a vector, graph and relational database mixed storage architecture, semantic vector efficient retrieval, knowledge graph relation management and business data synchronization are achieved respectively; and a dynamic optimization result is subjected to hybrid retrieval, a dual-drive reasoning mechanism outputs compliance conclusions and bases, and a retrieval enhancement generation service ensures that output contents conform to specifications. And systematic management and intelligent application of the electric power design knowledge are realized.

A method for AI-driven natural language search includes receiving a user query for one or more items from a user, processing the user query by searching against at least one relational database associated with the query, where the relational database is generated by extracting features from electronic documents of a plurality of items associated with the one or more items and by identifying specifications or respective values corresponding to the extracted features of the plurality of items, generating one or more query results based on the processing of the user query, where the one or more results include at least one item identified from the plurality of items and a justification for explaining an irrelevance of the at least one item, and transmitting the one or more query results to a user device for presentation to the user.

The invention discloses an enterprise data link management and value management method and system, and the method comprises the steps: carrying out the real-time capturing of multi-source heterogeneous data of all business systems in an enterprise through a distributed data collection engine, and recognizing the types of original data in different formats through a preset data source adapter; if structured data is detected, a relational database connector is adopted for extraction, and if the structured data is recognized as unstructured data, a document analysis module is started for content extraction, and an initial data set containing metadata tags is obtained; performing format conversion and field mapping on the initial data set according to a pre-established data standardization rule base, eliminating duplicate records and abnormal values through a data cleaning algorithm, performing automatic evaluation on a data quality grade by adopting a naive Bayes classifier, if a data quality score is lower than a preset threshold value, triggering a data recovery process, and if the data quality score is lower than the preset threshold value, performing data recovery. And standardized data meeting a unified standard is obtained. The normativity and value utilization efficiency of data management are effectively improved.

Systems and methods for processing search queries are provided. A method, according to one implementation, includes a step of receiving a query from a user interface, the query including one or more questions or commands pertaining to datasets stored in a relational database. The method also includes a step of generating a prompt having instructions related to how a Large Language Model (LLM) is to handle a complex query having one or more cascading dependencies. Also, the method includes a step of providing the prompt, datasets, and query to an LLM with instructions to convert the query into Structure Query Language (SQL) code.

The invention relates to the technical field of power system fault diagnosis, and discloses a distribution network line fault detection data processing method, system and device and a medium, and the method comprises the steps: obtaining load data of a target distribution line detection point, and carrying out the first preprocessing of the load data, and obtaining a fusion feature vector; performing second optimization operation on the fusion feature vector to obtain an optimized fusion feature vector; calculating a potential feature matrix according to the optimized fusion feature vector, and mapping the potential feature matrix to a low-dimensional space to obtain a low-dimensional sample set; presetting an adaptive label propagation algorithm, and performing fault category judgment on the low-dimensional sample set based on the adaptive label propagation algorithm; and storing a judgment result in a relational database. The problems that feature extraction is not accurate in a high-noise environment, and a classification model is insufficient in new fault expansion capacity are effectively solved, and fault signal processing robustness is improved.

The invention discloses a multi-source field-level blood relationship tracking method and system. The method comprises the following steps: extracting features from a multi-source heterogeneous system, matching templates, triggering a corresponding acquisition strategy, and outputting an original blood relationship log; reading an original blood relationship log to generate an abstract syntax tree, extracting a source / target field set to output a field-level mapping relation, further writing the field-level mapping relation into a graph database to form a blood relationship edge, writing metadata into a relational database, establishing a two-level index, and outputting a blood relationship graph capable of being quickly positioned; and taking the blood relationship map as input, returning a target path with the maximum sum of confidence coefficients by adopting a weighted shortest path algorithm, outputting a link-level traceability result, and displaying the link-level traceability result. According to the method, complete tracking of the field-level blood relationship is realized, the query response time is shortened to a millisecond level, rapid access to multiple types of data sources is supported, and the problems of insufficient blood relationship analysis precision, low query efficiency and weak multi-source adaptability in the prior art are solved.

A system and method for querying, processing, and ranking governmental data across heterogeneous databases may include integrating large language models (LLMs) and multi-agent orchestration to enhance accuracy and mitigate bias. The system receives a natural language query, processes the query using an agent orchestration LLM to generate search query instructions, and executes specialized data record processing agents to retrieve data from diverse sources, including relational, vector, and graph databases. A plurality of candidate natural language responses is generated and validated by data verification LLMs based on relevance and accuracy metrics to reduce hallucinations. The system further employs cross-source validation, statistical and linguistic consistency analyses, and weighted scoring to refine responses, which may include textual summaries, tables, or downloadable files presented via a graphical user interface. Accordingly, the approach ensures precise and contextually relevant results, particularly for applications involving sensitive or regulated data such as legislative and governmental records.

The invention relates to the field of large models, in particular to a mixed information retrieval generation method, system and device and a medium. The method comprises the steps that a user retrieval request is input into a preset special large model, and whether a structured retrieval intention is recognized or not is judged; if the structured retrieval intention is recognized, querying a relational database, judging whether a query result exists or not, and if the query result exists, taking the query result as a generation result; if the non-structured retrieval intention is recognized or no query result exists, querying a vectorization database; and if the similarity of the queried recall content exceeds a threshold value, inputting the recall content and the user retrieval request into a preset general large model to obtain a generation result. According to the technical scheme, the appropriate data source can be automatically selected for query according to the retrieval intention of the user, and both structured query needing accurate data and unstructured query needing semantic understanding can be met, so that the applicability and the flexibility of the system are improved.

The disclosed techniques provide improved methods of operating system (OS) search. Users are enabled to search for documents, emails, presentations, content they entered into a web form, meetings they participated in, and other interactions they had with their computing device. To accomplish this, screenshots are periodically captured and indexed. Machine learning models are used to infer embeddings for visual elements of the screenshots and / or text extracted from the screenshots. A full text index of a relational database may also be populated with text extracted from the screenshots. The embeddings and full text index may then be used to retrieve screenshots in response to a user history query. For example, screenshots of embeddings within a defined distance of an embedding of the user history query may be selected. Query results from different embedding indices and relational databases may be ordered by applying different weights to different kinds of search scores.

The invention belongs to the technical field of log monitoring, and particularly relates to a real-time log monitoring alarm method, system and equipment based on event driving, and the method comprises the steps: dynamically obtaining a log file path needing to be monitored, monitoring a log file on a server, and sending incremental log data to a specified Topic of Kafka in real time; through an event-driven architecture, using a Kafka consumer group to consume log data in Kafka in real time, and using a kset data type of Redis to temporarily store the log data; performing real-time processing on the log data in the Redis; comparing the statistical result with a preset threshold value, and if the statistical result reaches the preset threshold value, sending alarm information according to a configured notification mode and a notifier; and storing the monitoring result in a relational database, and displaying the monitoring big disk through a visual page. And an event-driven architecture is adopted, so that the data processing flow is more efficient, and the overall performance and expandability of the system are improved.

Methods, systems, and devices for data management are described. A method may include obtaining a new snapshot of a relational database of a source computing environment, comparing the new snapshot of the relational database to a prior snapshot of the relational database, updating, in response to the comparison indicating that data of a row of a relational database table changed between the prior snapshot and the new snapshot, a field of a second versioning control column of a corresponding row of a backup database table of the set of backup database tables to indicate a version of the new snapshot, and adding, in response to the comparison indicating that the data of the row of the relational database table changed, an additional row to the backup database table, where a field of a first versioning control column of the additional row includes an indication of the version of the new snapshot.

The invention provides an intelligent agent-based automatic verification and rule matching system for insurance-waiting evaluation reports. The intelligent agent-based automatic verification and rule matching system comprises a report acquisition module which pulls to-be-verified and historical insurance-waiting reports; the auditing processing module calls an attention Bi-LSTM model which is subjected to reinforcement learning fine adjustment and is fused with knowledge graph embedding, and scores the report sentence by sentence; the rule management module is used for storing and analyzing an equal-guarantee 2.0 structured machine rule and carrying out secondary accurate matching on low-confidence sentences; the knowledge graph module is used for maintaining a multi-dimensional association graph of a standard family, a control measure and an evaluation item and providing graph reasoning; the agent decision-making module generates actions of passing, returning, manual rechecking or automatic correction according to the auditing state; the feedback learning module collects artificial recheck differences, an incremental training model, a strategy network and atlas vectors; and the storage module stores reports, models, rules, maps and logs in a multi-modal manner through a relation library, a map library and a vector library, and implements data governance and access control. According to the invention, the audit efficiency, accuracy and standard consistency of the evaluation report can be improved.

The invention discloses an electric power field credible question-answering system based on a knowledge graph and multiple agents, and belongs to the technical field of intelligent power grids. The electric power field credible question-answering system comprises the steps that an existing knowledge base is stored through a vector knowledge base, the knowledge graph and a relational database, and then a multi-agent system is constructed based on a large language model; a complex problem is decomposed into a plurality of sub-problems by adopting a logic form language in real-time dialogue, solving is carried out based on operators such as planning, reasoning and retrieval, symbolization and structuring of a problem solving process are realized, knowledge is aligned and integrated by using a semantic reasoning technology, a semantic relationship between the knowledge is identified and established, and a real-time dialogue result is obtained. And realizing credible questions and answers in a manner of recalling related knowledge. According to the method, the deep fusion of the unstructured text, the structured data and the semantic relationship is realized by constructing the multi-modal knowledge storage system, the knowledge coverage rate and the semantic consistency are remarkably improved, and the understanding and response capabilities of the system to compound problems are improved.

The invention relates to the technical field of data processing, in particular to a relational database intelligent query method based on machine learning, which comprises the following steps of: processing multi-modal flow data through time sequence alignment, generating a unified semantic representation vector, constructing a dynamic psychological state map, and modeling a psychological state evolution track by utilizing a neural common differential equation mechanism. After user query is received, historical dialogue nodes are retrieved from the graph, enhanced query intention representation is generated, the enhanced query intention representation is converted into an execution plan through a neural symbol inference engine, and a graph neural network is adopted to predict execution cost. And finally, a personalized analysis report is generated by combining a causal discovery algorithm, and system adaptive optimization is realized through feedback signals. According to the method, the problems of inconsistent time sequence semantics and strong context dependency of the multi-modal psychological data are effectively solved, and the query accuracy and the personalized level in a psychological dialogue scene are improved.

Queries may be made against a non-relational database without impacting the capacities of the non-relational database by enabling performance of queries to a non-relational database via an external query management, backup management, and a non-relational database backup hosted in an external data storage. Query units may be provided to an external query engine to provide parallel units of work for accessing and performing queries on a backup of a database.

The invention discloses a structured data storage method based on natural language transformation, which comprises the following steps of: a system initialization configuration stage: deploying a protocol adapter in a local memory of a PC (Personal Computer) client, and loading natural language processing pipeline configuration parameters; a heterogeneous data acquisition stage: capturing a multi-source text data stream through the protocol adapter, uniformly converting the multi-source text data stream into a standardized data packet, and sending the standardized data packet to a message queue theme; a text cleaning stage: a named entity recognition stage: inputting the pure text data into an NER module deployed with a language model loader; in the conditional feature extraction stage, feature vectors are generated for texts meeting preset conditions on the basis of entity type tags in the entity recognition result; and a consistent storage stage: inserting the entity identification results into a relational database in batches, and updating the entity mapping relationship in the cache. According to the method, the intelligent level of cache management is remarkably improved, and the access fluency of the key data of the user is guaranteed.

The invention relates to the technical field of natural languages, in particular to a method and system for improving SQL generation accuracy of an LLM large model based on the CoT concept. The method comprises the following steps: firstly, preprocessing database metadata, and extracting a table structure and field information; the method comprises the steps that firstly, a complex natural language query task is divided into a plurality of sub-problems with definite semantics on the basis of the Chain-of-Though concept, SQL sub-query statements capable of being independently executed are sequentially generated in a multi-pass SQL mode, and input of each statement is based on an output result or original data summary of the previous statement. A verification mechanism is introduced in the generation process, the grammar and logic validity of the SQL statement is checked, and if a grammar error or no problems of fields and table names are found, the system automatically recognizes and prompts the error, so that the executable performance of the SQL is guaranteed. According to the method, the accuracy and the stability of the large model in the relational database query task are effectively improved, the illusion phenomenon is reduced, and the practicability and the reliability of an intelligent agent system are enhanced.

The invention discloses a meteorological operation and maintenance intelligent question-answering method based on multi-mode GraphRAG. The method comprises the following steps: S1, a meteorological operation and maintenance intelligent question-answering system divides input data into unstructured data and structured data and processes the unstructured data and the structured data respectively; s2, constructing a knowledge base system composed of a vector database, a relational database and a graph database; s3, analyzing the user query text and dividing question types; s4, selecting a corresponding retrieval strategy according to the question type and starting a processing flow, and finally processing a retrieval result through a fusion and rearrangement module to obtain a knowledge evidence set; and S5, the meteorological operation and maintenance intelligent question-answering system organizes the knowledge evidence set and the user questions into structured cues and submits the structured cues to the large language model for processing to generate structured answers. According to the method, optimization is carried out according to characteristics of the meteorological operation and maintenance field, professional terms and field specific knowledge can be effectively processed, and high-quality field professional services are provided.

The invention discloses a method and system for generating an engineering design specification based on a large language model, and the method comprises the steps: converting a plurality of formats of engineering documents into structural data through a non-structural document analysis module, and carrying out the multi-modal storage through a vector database and a relational database; a document recall module is combined with an expert predefined generation strategy and user input information to intelligently retrieve related materials from a vector database; and finally, calling a large language model through a document generation module to rewrite, expand or independently generate recalled contents, and outputting a highly customizable design specification which conforms to engineering specifications. According to the method, the efficiency, accuracy and specialty of engineering design document generation are remarkably improved, multi-section concurrent generation and manual fine adjustment are supported, and the method is suitable for multiple engineering stages such as project proposal, feasibility research report and construction drawing design.

The invention relates to the technical field of equipment control, and provides an equipment control method and system based on a natural language and electronic equipment. According to the application, the machine language vector is generated through the intention recognition result of the natural language instruction, and the graph query statement is generated according to the semantic concept after the machine language vector is deconstructed, so that the equipment knowledge graph of the original equipment is queried through the graph query statement to obtain the equipment operation path meeting the semantic concept; the knowledge graph has a mesh topology structure, the equipment knowledge graph is used for replacing a rigid relational database structure, deep requirements in natural language instructions are mined through intention recognition, machine language vectors are obtained, the machine language vectors are deconstructed, and the control of the original equipment is achieved. And generating a graph query statement corresponding to the equipment knowledge graph according to the deconstructed semantic concept, thereby accurately and comprehensively querying the complex context semantic relationship between the nodes, and improving the understanding accuracy of the natural language instruction.

The invention discloses a multi-source heterogeneous information extraction and structured processing method based on natural gas business data, and relates to the technical field of artificial intelligence application in the energy industry, and the method comprises the steps: analyzing a multi-modal document: carrying out the content analysis of natural gas sales documents in various formats, extracting key information, and obtaining the analyzed original data; data preprocessing: cleaning, recombining and standardizing the data to obtain preprocessed data; the mixed information extraction comprises key business index extraction, field rule base establishment, mixed extraction model establishment and context reasoning, and missing items in data are complemented by analyzing overall information and local content of a document, so that the integrity and accuracy of the information are improved; performing intelligent post-processing and constructing a relational database; according to the processing method, the natural gas service data can be accurately and efficiently extracted from the documents in various formats, and a basis is provided for subsequent data analysis and decision support.

The invention relates to a streaming data and mass batch data storage method, which belongs to the technical field of data storage, and comprises the following steps: classifying mine data into streaming data and batch data; according to the method, a mixed storage architecture is constructed, the mixed storage architecture comprises a data acquisition layer, a batch processing layer, a speed layer, a service layer and an application layer, so that streaming data and batch data are processed and stored by adopting different rules, and the method comprises the following steps of: acquiring the streaming data by adopting an acquisition adaptation gateway and a real-time message queue Kafka; collecting the batch data by adopting a relational database DM8 and a timing scheduling Airflow mode; the batch processing layer is used for dividing the data into cold and hot temperature data and performing classified storage on the data; the speed layer is used for processing and storing the real-time streaming data; the service layer is used for carrying out data integration on the temporary stream processing data and the batch processing result data and providing data query interface service; and the application layer is used for setting a business application module and accessing each database to realize data application.

The invention provides an enterprise-level API gateway management method and system, and the method comprises the steps: API registration: an API registration platform receives input or batch-uploaded API metadata, and submits an auditing application after the registration is completed; aPI examination and approval: executing a differential examination and approval process according to the interface type, and exporting interface data after the examination and approval are passed; aPI release: importing the approved interface data into an API gateway management station, persisting the data to a relational database at the management station, and issuing a change notification to an API gateway; and updating the configuration of the API gateway: pulling and caching the database configuration data when the API gateway is started, continuously monitoring the data change of the management station, and updating the local cache in real time to take effect of a new routing strategy. According to the application, the reliability, the safety and the observability of the whole API management system can be improved.

The invention provides a method for determining the influence of the corrosion degree of a grounding grid on the frequency response characteristic of high-frequency current, and belongs to the technical field of grounding grid corrosion, and the method comprises the steps: firstly building a small grounding grid physical model with different preset corrosion degrees, and simulating the actual soil environment parameters; high-frequency excitation current is injected, data such as voltage signals, current signals and potential distribution are collected, and the signals are subjected to multivariate mixing decomposition to obtain components. Then establishing a characteristic relation matrix, calculating the impedance value of each frequency point, and constructing a corresponding relation database of the impedance values and the corrosion degrees; and finally, establishing an influence equation set based on the database, thereby accurately determining the influence degree of the corrosion degree of the grounding grid to be detected on the frequency response characteristic of the high-frequency current, and providing reliable technical support for state evaluation of the grounding grid. According to the scheme, the technical problem that the quantitative relation between the corrosion degree of the grounding grid and the high-frequency current frequency response characteristic of the grounding grid is not established in the prior art is solved.

The present disclosure describes methods, systems, apparatus, and media for object identification and classification, utilizing multi-feature and multi-modal data. This includes shape, material, brand, price, odor, taste, tactility, and sound. The system integrates a server space for data processing, a querying device for iterative searches, and a data interface module for refining results. It features AI-driven image optimization, feature extraction, and pattern recognition, employing novel techniques for fusing multi-feature and multi-modal embeddings utilizing multi-head attention. Additionally, a linker module powered by two active learning with feedback loops AI models consolidates scattered data into a unified object information database. The system also employs novel AI algorithms for isolating the object of interest through a saliency map and semantic analysis, as well as for enhancing raw images with a GAN-autoencoder.

The invention discloses a flexible slope support optimization design system, and relates to the technical field of flexible slope support, a data acquisition module is constructed, dynamic data and image data of a slope surface are acquired based on a multi-array sensor deployed on the slope surface, and the dynamic data are transmitted to a dynamic relational database; the instability model building module is used for analyzing the dynamic data to generate an instability model of the slope surface and generating a stress analysis report of the slope surface based on the instability model; a support interference field module is constructed, a support interference field is generated based on the stress analysis report, and an optimization scheme of flexible slope support is generated based on interaction of the support interference field and the instability model; constructing a visualization module for visually displaying the instability model and the optimization scheme of the flexible slope support; according to the scheme, an intelligent analysis closed loop with data driving and mechanical model depth coupling is constructed, and efficient optimization of slope support from passive response to active prediction is achieved.

The invention provides a virtual equipment and variable data processing method for power monitoring, which realizes intelligent definition, calculation, alarm and visual data binding technology of virtual equipment and variables in a power monitoring scene by integrating MQTT, a memory database, a time sequence database and a relational database and combining a regular expression analyzer collaborative analysis mechanism. The system supports various data such as current real-time values, equipment attributes, accumulated value differences and historical data to form an expression, the real-time data is stored in a Redis database and the historical data is stored in a TD engine database by adopting an atomic storage strategy taking station + deviceid + measure as key values, and efficient query and atomic storage combination based on the Redis and the TD engine are realized through a unified API interface, so that the data display speed is greatly increased, and the data display efficiency is improved. The innovatively designed zero-code binding mechanism is based on a front-end data driving framework, and automatic binding of real-time acquisition variables, virtual variables and power monitoring display components can be completed without additionally developing an API (Application Program Interface).

The invention discloses an acceleration tube full-process automatic reliability test system and device, and relates to the technical field of high-power microwave device testing, and the system specifically comprises the following modules: a control test module, a hardware control module, an acquisition processing module, a business logic module, a data persistence module, and a user performance module. Writing and executing an automatic reliability test script of the acceleration tube; receiving and executing a hardware control instruction, and uploading an original analog / digital signal of the equipment; the communication module communicates with equipment in the hardware control module, converts an original analog / digital signal into a digital signal which can be processed by a C # program, and carries out filtering, unit conversion and validity verification on the digital signal; an over-limit alarm function is provided, and the structured test data is sent to the data persistence layer; storing all test related data through a relational database; test parameter configuration, real-time monitoring, alarm states, data records and dose rate curves are provided based on a graphical user interface.

The invention relates to the technical field of information security, and discloses an information security testing and evidence obtaining platform, which comprises a graphical user interface module for acquiring project information, project types, equipment information and task information, and storing the project information in a relational database; and encrypting and storing the equipment information. And the protocol simulation module integrates SSH, HTTP and MySQL protocol client libraries, realizes remote equipment login, dynamically loads plug-in configuration and executes a multi-dimensional evaluation algorithm, such as regular matching, keyword scanning and configuration priority analysis. A standard rule base is arranged in the compliance rule judgment module, a quantitative evaluation result is generated through Boolean operation, and an SM2 signature engine is integrated for data signature and integrity verification. The abstract is recalculated through the public key data packet and the signature value is compared, so that the data integrity is ensured. According to the invention, the accuracy and pertinence of equipment safety assessment are ensured.

The invention relates to the technical field of chip design, and provides a clock constraint generation method, electronic equipment and a storage medium, and the method comprises the steps: building a relational database based on hierarchical design information of a chip, the relational database comprising an instantiated module relationship in the chip and a cross-module port connection relationship; determining a clock source from the relational database, and traversing a propagation path of the clock source in the relational database by taking the clock source as a starting point; and generating a clock constraint file of the chip based on the propagation path of the clock source. According to the method, the electronic equipment and the storage medium provided by the invention, the hierarchical design information is converted into the dynamic, queriable and traversal relational database, so that the clock propagation path is reconstructed, the clock constraint file is driven to be automatically generated, and on the premise that the complete hierarchical design information is reserved, the automatic generation of the clock constraint file is realized. The efficient, accurate and complete propagation path reconstruction is realized, and the clock constraint generation efficiency and accuracy are improved.