90 results about "Database model" patented technology

The invention discloses a method for migrating a traditional electric power SCADA system to a new energy system, and relates to the technical field of electric power system migrating, and the method comprises the steps: building an instance object of each equipment model according to the type of electric power equipment and a four-remote configuration point table, and carrying out database model instance configuration and batch implementation through a model configuration tool, forming a model instance set configuration taking a partition or equipment as a unit; generating a power system calculation formula script by using a calculation formula configuration simulation tool, and recording the information relationship of each virtual point through a standardized data format to realize export and import of calculation script configuration; importing and exporting partition pictures by using a graphic configuration tool to realize automatic configuration from an original engineering project to a new project; and according to the equipment type, classifying the matched configuration image templates, and realizing image static loading and template dynamic configuration. The method can change few codes, smoothly upgrade to adapt to various scenes, and reduce the engineering workload.

The present invention discloses a safety inspection system and method based on a hidden danger database model, comprising the following steps: S1, establishing a hidden danger table, an inspection record table, and a rectification record table, and constructing a hidden danger rule base; S2, collecting hidden danger data, and storing it in the hidden danger database model after standardization; S3, constructing a hidden danger knowledge graph and generating a feature matrix; S4, inputting the data and the feature matrix into a time series model to generate a risk scoring matrix; S5, optimizing the hidden danger classification and updating the rule base based on the risk score and knowledge graph; S6, inputting a multimodal hidden danger identification model to classify the hidden dangers; S7, optimizing task allocation, updating the hidden danger status and storing it in the database; S8, integrating data to generate dynamic feature labels, optimizing the model, and outputting a heat map and trend report. Through multimodal data fusion and dynamic analysis, the present invention realizes intelligent management of hidden danger detection, risk assessment, task allocation, and model optimization, significantly improving the efficiency and accuracy of safety inspections.

The invention discloses a profile alignment-based steel rail abrasion real-time discrimination method and model, and the method comprises the steps: building a steel rail standard profile database model which is used for receiving actual measurement profile data and carrying out the real-time overlapping display; acquiring a point with the minimum vertical coordinate of the outer contour of the steel rail profile from the actually measured profile data, and overlapping the point with the minimum vertical coordinate with the reference point of the standard profile to realize primary alignment of the profile; calculating a perpendicular bisector at the rail waist of the actual measurement profile, and enabling the perpendicular bisector to coincide with the center line of the standard profile to finish rough alignment of the profile; and calculating the center point of the actually measured profile rail web, performing fitting processing to obtain a fitting center line, and enabling the fitting center line to coincide with the standard profile center line to complete profile fine alignment. According to the method, the precision of profile alignment is effectively improved, meanwhile, the influence of profile form errors on an abrasion algorithm is reduced, and then the problem of jumping during alignment of the actually measured profile and the standard profile is solved.

A Hypothesis Generation and Testing System (HGTS) includes a framework for enabling artificial intelligence (AI) systems to autonomously formulate, test, refine, and store hypotheses using structured experimental workflows. HGTS may integrate with, but operates independently from, traditional databases, model repositories, context-aware AI databases and the like to provide a persistent, traceable, and interpretable record of hypothesis lifecycles. The system incorporates a probationary hypothesis database for unverified ideas, a validation engine for controlled experimentation, a confidence scoring and lifecycle management agentic subsystem for hypothesis evaluation, and recursive learning agents that iteratively refine models and experimental methods. Modular agents autonomously propose, test, and document hypotheses using statistical, symbolic, and deep learning techniques. The system ranks outcomes and retains full contextual metadata, enabling reproducible discovery. HGTS thereby provides a foundational mechanism for reproducible, interpretable, and self-directed intelligence, forming a cornerstone technology for artificial general intelligence (AGI).

The invention discloses an intelligent early warning method and system based on laser control industrial data, and belongs to the technical field of laser safety early warning. The system comprises an equipment control module, a data acquisition module, an analysis database, a model management module, a monitoring judgment module and an alarm module, the equipment control module is used for controlling the laser to cut the industrial product; the data acquisition module is used for acquiring cutting data and parameter data generated in the industrial product cutting process; the analysis database is used for storing historical data of the cutting data and the parameter data; the model management module is used for establishing a deviation analysis model and analyzing the influence of different influence parameters on the cutting deviation of the industrial product; the monitoring judgment module is used for judging whether current industrial product cutting is abnormal or not; the alarm module is used for carrying out abnormity alarm; according to the method, the influence of different influence parameters on the cutting deviation of the industrial product is considered, and the accuracy of system data analysis is improved.

The invention discloses an AI insole modeling system based on multi-modal biomechanics and a 3D printing method, and relates to the technical field of biomedical engineering, and the AI insole modeling system specifically comprises an external parameter calibration module, an image processing module, a three-dimensional reconstruction module, a measurement and analysis module, a foot database establishment module, an insole database modeling module and an insole 3D printing module. Based on the biomechanical principle and the digital medical technology, a full-link digital service system of three-dimensional scanning, AI modeling and 3D printing is constructed, firstly, based on a foot scanning and analysis system of multi-view three-dimensional reconstruction, through the processing flow of camera calibration, image distortion removal, semantic segmentation, multi-view three-dimensional reconstruction and measurement, a full-link digital service system of three-dimensional scanning, AI modeling and 3D printing is constructed; and finally, key parameters of the foot length, the foot width, the hallux valgus angle and the flatfoot degree are output, high-precision foot modeling and measurement are achieved, accurate customization of the orthopedic insoles is achieved, and the device is suitable for the fields of medical diagnosis, orthopedic shoe customization and sports science and has the characteristics of high precision, automation and modularization.

This invention discloses an automatic update system for website article, tag, and category matching models, relating to the field of model update technology. It includes a data input module, a recommendation query unit, and a training unit. The data input module includes inputting query data and matching keyword data with data obtained from the database by the recommendation query unit to obtain matching data and corresponding articles. The database used is the Milvus database. This application optimizes the model and its performance, accelerating the training speed. Furthermore, this application uses the Milvus database, the Roformer model, and the prompt technique to solve the problem of requiring multiple manual training and restarts for a single site. Model updates are convenient and do not affect business operations. The same model can be adapted to data groups from multiple sites, and the problem of repeated training across multiple sites is solved.

The invention relates to a resource networked modeling and scheduling optimization method based on a Neo4j electrical diagram database, and the method comprises the following steps: building a diagram database model based on a power system structure; flexible resources are extracted and managed based on a graph calculation method; and constructing a graph structure scheduling strategy system. Visual representation and multi-dimensional attribute nesting of the power system topology are achieved, real-time identification, dynamic updating and hierarchical classification are carried out on adjustable loads and controllable equipment, high expansibility, high real-time performance and high adaptability are achieved, the method can be widely applied to novel power systems represented by a power distribution network, a park micro-grid and a source-load-storage cooperative system, and the method is suitable for popularization and application. And accurate modeling and intelligent regulation and control of flexible resources are realized. Compared with an existing SQL (Structured Query Language) or relational database scheduling mode, the method has remarkable advantages in the aspects of modeling granularity, response speed and system integration.

The invention discloses a traffic influence autonomous evaluation system based on natural language processing and a working method, and belongs to the technical field of traffic management. In order to solve the problem of difficulty in urban traffic multi-scene analysis iteration, the system comprises a basic data layer, an NLU engine / intelligent processing layer and a user interaction layer, and the basic data layer, the NLU engine / intelligent processing layer and the user interaction layer are connected in sequence; the basic data layer comprises a road network facility database, a model parameter library, a traffic demand matrix and a traffic partition database; the NLU engine / intelligent processing layer comprises a natural language understanding NLU engine, a traffic analysis modeling evaluation module and a report generation module; and the user interaction layer comprises a Web / App graphical user interface, a voice / text input interface, a parameter confirmation and modification panel and an AR / Web visual report board, and realizes interaction between a user and the traffic influence autonomous evaluation system based on natural language processing. The method has the high efficiency of the whole process.

The application discloses an online education data intelligent planning system and method based on big data analysis, and belongs to the technical field of education data analysis. The system comprises a learning text management module, a data acquisition module, an analysis database, a model management module and a test question generation module; the learning text management module is used for collecting different learning texts for user learning and calculating the complexity of each learning text; the data acquisition module is used for respectively acquiring reading behavior data and test question data of different user learning texts; the analysis database is used for storing historical data; the model management module is used for analyzing the influence of different reading behaviors on the understanding degree of user learning texts; and the test question generation module is used for automatically generating a test question set about the user and pushing the test question set to the user; the application automatically generates a test question set about the user by connecting the weak knowledge points of the user, and improves the intelligent service level of the online education platform.

The present invention relates to a method based on multimodal code generation and progressive delivery, which belongs to the field of code generation technology and natural language processing. The present invention builds a visual low-code development platform based on a basic template, which sets configuration data through a visual page; generates database model data based on the configuration data, and pregenerates basic code in combination with the basic template; inputs the generated basic code into a pre-trained PLBART model; uses the PLBART model to reason and complete the language syntax and semantics, and outputs executable code; pushes the executable code to a code warehouse, and automatically builds, tests, and packages the executable code; uses a grayscale release strategy to achieve grayscale release and progressive delivery; the present invention realizes systematic code generation through multi-modal data processing, organically combines grayscale release, and achieves progressive delivery, significantly improving development efficiency, code quality, and system reliability.

The application provides a database model automatic construction method and system, and the method comprises the following steps: obtaining information in a first table structure table, wherein the information in the table structure table at least comprises the following technical fields: unique identification ID, data flag, release time, update time, update ID, valid flag, and deletion time; the unique identification ID is generated according to the release time of the information, and when multiple pieces of information are released at the same time, the unique identification ID is sorted; the data flag is used for recording data generation flag; the update ID is generated according to the update time of the information, and when multiple pieces of information are updated at the same time, the update ID is sorted; and a first database model is automatically constructed according to the information in the first table structure table. The database model automatic construction method and system provided by the application can realize automatic construction of a database by providing standardized technical fields, avoid mistakes in understanding and operation of database model establishment by developers, and greatly improve work efficiency.

The invention discloses a finite element-based calculation method for heat distribution of a large-scale three-dimensional integrated circuit (3DIC). The method comprises the following steps of: establishing a large-scale 3DIC model; performing heat distribution calculation on the established large-scale 3DIC model; for an existing heat dissipation method, 3DIC is systematically looked up, and important parameters in the aspects of geometry, heat dissipation, heat sources and the like are collected; parameterizing geometry, heat dissipation, a heat source and the like; establishing a large-scale 3DIC model database; performing heat distribution calculation on the database model; collecting a database model heat distribution calculation result, and inputting the result into a database; and establishing an artificial intelligence / machine learning optimization system. According to the method, the finite element analysis FEA technology with an accurate solving function is combined with an efficient XSim calculation tool, high accuracy and calculation efficiency are achieved, the super-strong performance of comprehensively simulating thermal behaviors of the whole packaging large model and the surrounding thermal environment of the whole packaging large model is achieved, and the heat distribution calculation problem of large three-dimensional integrated circuit 3DIC packaging is solved.

The invention provides a database object relation mapping method based on secondary equipment of an electric power system, which comprises the following steps: analyzing and classifying the secondary equipment of the electric power system, defining attributes and parameters of different equipment, sorting association relations among the equipment, and forming a secondary equipment object information system; designing an adaptive database model according to a secondary equipment object information system, and creating corresponding data tables for different types of secondary equipment to realize effective storage and management of secondary equipment data; the method comprises the following steps: mapping secondary equipment in a power system and related data thereof into a database through a data relation mapping method of the secondary equipment in the power system, and establishing a corresponding data relation; and querying and analyzing the data according to actual requirements through the mapping relationship. The method has the advantages that the problems existing in data management of secondary equipment of a traditional power system are effectively solved, the efficiency and reliability of data management and application are improved, and powerful support is provided for safe and stable operation of the power system.

A method is described for communicating with a computer device comprising a knowledge database modelling data in the form of a knowledge graph. The method includes, on the device, receiving a first request comprising information relating to an entity of the knowledge graph; commanding the rendering of a web page containing this information; receiving a second request requesting at least one missing property of said entity, from among said rendered information; commanding the rendering of a web page containing a list of missing properties classified by the observation frequency of these properties for other entities of the same type; polling a language model, based on a prompt generated by said device in natural language, with said prompt asking the language model for the value of at least one of the properties in the list; and commanding the rendering of a web page containing that value.

The application discloses a batch processing method of an AI database based on postgresql. Based on multiple pieces of data in the postgresql database, the multiple pieces of data are input into an AI model for inference calculation. The process of the inference calculation comprises sequentially performed data loading, data preprocessing, AI model inference calculation and result type conversion. A sliding window is constructed by using a built-in window function of the postgresql database, the process of the inference calculation is batch processed by using the sliding window, and after the batch processing, the data after the inference calculation is output piece by piece in a backward sliding window mode. The batch processing method proposed by the application significantly improves the inference speed of the AI database model based on postgresql, and realizes batch processing of data without changing the database kernel.

The application discloses an intelligent splitting and assembling method of a database model based on a business scene, belongs to the technical field of database management and application, and relates to the technical field of database management and application. The splitting method comprises the following steps: converting an abstract or unstructured business model into a calculable or structured graph representation form, mapping a business function unit into a node in the graph, mapping the relationship between businesses into an edge, and constructing a business topology structure. The assembling method comprises the following steps: acquiring the business topology structure, automatically analyzing a natural language business requirement into a structured requirement model, performing feature extraction on the analyzed requirement, generating a multi-dimensional feature representation, and assembling business model slices in a progressive matching mode. The application can improve the database operation efficiency, reduce the database construction and management cost, and enhance the adaptability and flexibility of the database to business changes.

Systems, computer program products, and methods are described herein for intelligent database modelling. The present invention is configured to capture, using the augmented reality application, a drawing made by the user on a medium; initiate a first machine learning model on the drawing; determine that the user is attempting to design a database model; extract at least a first entity from the drawing; determine, using the first machine learning model, one or more attributes for the first entity; initiate, via the augmented reality application, a first push notification for display on the computing device of the user; electronically receive, via the augmented reality application, a user selection of a subset of attributes from the one or more attributes; generate, using the augmented reality application, a conceptual database model based on at least the first entity and the subset of attributes.

The application discloses a kind of plant station end panoramic data and the dynamic linkage method of monitoring system application, comprising the following steps, in the panoramic model data of plant station end, the attribute value of each data is increased, and source end management is carried out to whole model data by integrated configuration configurator, integrated configuration configurator is wired terminal information (reference) as keyword, the mapping of model data attribute and monitoring database record field is realized, by the mapping relationship of model data and monitoring database, and then automatically realize the one-time modification of monitoring system database data and data attribute, the dynamic association of each application and database model data of monitoring system, automatically identify the change of database data and data attribute, realize the dynamic loading of data.The method reduces the workload of multiple, repeated modification data of operation and maintenance personnel, reduces the error risk of human intervention, improves operation and maintenance efficiency.

The present application relates to the technical field of database construction, and particularly relates to a construction method of a foraminifera morphological feature database, comprising the following steps: S1, collecting foraminifera images from multiple sources, identifying scale drift and shooting deviation based on principal axis normalization and local vorticity field, performing structure-preserving image enhancement, and outputting an enhanced image set consistent in shell substance, shell arrangement, shell opening, suture line and micro-pore features; S2, extracting a multi-scale shell structure atlas, constructing a structure-semantic coupled label nested tree, performing polysemy recognition and ambiguity resolution, and generating a structured annotation set; S3, fusing the image set and the annotation set, and constructing a three-layer database model containing a part layer, an attribute layer and a variation layer according to the label nested tree. Through image structure enhancement, semantic ambiguity resolution and three-layer database construction, the present application effectively improves the recognition accuracy of foraminifera morphological features, the label organization logicality and the information retrieval efficiency.

The invention relates to an intelligent application development and deployment platform, and belongs to the technical field of artificial intelligence. The platform comprises training resources, a model development module, a model training module, a model deployment module and a large model agent. According to the method, flexible scheduling of computing resources is realized on the server, universal goods shelves such as a database, a model library, an algorithm library, a lightweight library and an operator library compatible with multiple development frameworks are created, tools such as multi-modal data labeling, model conversion, mirror image packaging and online development are integrated, services such as intelligent labeling and cloud edge collaboration are preset, rapid updating and iteration of models are supported, and the development efficiency is improved. And carrying out one-key deployment on an end-side algorithm. The platform can form a replicable and generalizable product through the combination of a basic type and a specific component, and the platform can be applied to the same row in the industry and has a wide application prospect.

The invention discloses an apnea knowledge question and answer model construction method and device based on knowledge enhancement, and the method comprises the steps: constructing a database containing apnea knowledge and a test set, and carrying out the apnea knowledge question and answer model on the basis of the database through employing a predetermined external knowledge decoding strategy, a deep and shallow knowledge decoding strategy and preset probability distribution, and constructing an apnea knowledge question-answer model, and testing the apnea knowledge question-answer model by using the test set. Therefore, according to the apnea knowledge question and answer model construction method and device, on the basis of the question and the constructed apnea knowledge database, the model decoding emphasizes external knowledge, emphasizes high-level knowledge and reduces an algorithm of shallow-layer knowledge, so that the accuracy of answering the apnea question by a large model is improved; the problem that in a specific scene of apnea knowledge questions and answers, a natural language processing method is poor in answer accuracy due to insufficient professionality is solved.

The application relates to a task-driven multi-agent emergency decision support method and device, wherein the method comprises the following steps: constructing a subtask for a risk guidance decision support model, splitting a complex task into simple subtasks, so that a more accurate emergency decision support process is realized; constructing an interactive agent for each subtask, constructing corresponding prompt engineering content according to definition, so that an analysis agent and a test agent for different tasks are constructed; collecting safety analysis report data, and establishing a sample database for emergency operation procedure decision support; model training, giving the sample database to the agent, and constructing a successful case library and a failed case library; inputting super-reference original event information, and generating a decision support procedure for the described original event. Therefore, the problems that an existing emergency plan decision method is extremely dependent on expert knowledge, is limited by human cognition, and it is difficult for on-site personnel to make a quick decision on an event beyond the emergency plan are solved.

The invention relates to the technical field of fire emergency simulation, and provides a dynamic generation interaction control system suitable for various visual fire scenes, comprising a fire scene database model generation module which outputs a fire scene model which can be used by a visual system; the self-defined fire scene model generation module generates a dynamic fire scene model according with a physical rule through a grid-based fire scene expansion model generation algorithm, a time step increment fire point detection algorithm and a direction-sensitive fire spread distance correction algorithm; the dynamic fire scene simulation module selects a fire scene model according to the parameter configuration management module and dynamically generates multiple fire source types, the multi-physics field coupling module simulates smoke diffusion, and the fire extinguishing module generates a fire extinguishing instruction; the interaction control module is compatible with an existing database and a communication protocol, and the interface adaptation module is seamlessly integrated with an external system. The system can be used in the fields of simulation test verification, demonstration training and the like of flight simulation fire emergency scenes, and the fire emergency simulation and training capability is effectively improved.

Systems, computer program products, and methods are described herein for intelligent database modelling. The present invention is configured to capture, using the augmented reality application, a drawing made by the user on a medium; initiate a first machine learning model on the drawing; determine that the user is attempting to design a database model; extract at least a first entity from the drawing; determine, using the first machine learning model, one or more attributes for the first entity; initiate, via the augmented reality application, a first push notification for display on the computing device of the user; electronically receive, via the augmented reality application, a user selection of a subset of attributes from the one or more attributes; generate, using the augmented reality application, a conceptual database model based on at least the first entity and the subset of attributes.

This application relates to a method for generating intelligent SQL question answering based on a large model in a database. The method includes: constructing large model prompts based on historical SQL statements; obtaining a business query request description; establishing a correspondence between the business query request description and historical SQL statements, adding the description to a corresponding vector database; upon receiving a business query request, matching it against the vector database to obtain the closest historical SQL statement and its corresponding business query request description; constructing large model prompts based on the closest historical SQL statement and its corresponding business query request description; and generating the SQL statement for the business query request. This application significantly improves the accuracy of NL2SQL by utilizing the SQL execution history of the database, overcoming the previous problem of low accuracy in multi-table question answering with NL2SQL, and providing a new method for the application of NL2SQL and ChatBI in complex databases.

The invention relates to the technical field of petrochemical engineering, and discloses a petrochemical engineering real-time analysis intelligent charring optimization control system, which comprises an on-line gas analyzer used for detecting the concentration of carbon monoxide and carbon dioxide in charring gas in real time and transmitting data to an intelligent charring management system in real time; and the intelligent charring management system is used for receiving the data transmitted by the online gas analyzer, judging the charring progress and depth in combination with a database model, and controlling the whole charring progress in real time in an interlocking manner according to the actual situation on site, namely controlling and correcting the injected air amount, water vapor amount, temperature and the like in real time. The concentration of carbon monoxide and carbon dioxide in the charring gas is monitored in real time by combining the intelligent charring management system with the online gas analyzer, and the charring progress and depth can be accurately judged. Once an abnormal condition is detected or is close to a set threshold value, the system can immediately adjust the scorching parameters through the DCS, and it is ensured that the scorching process is always in a safe and controllable range.

This invention discloses a smart elderly care service management system and method with anomaly alert function, relating to the field of elderly care service technology. It includes: a data acquisition module for collecting data; a data preprocessing module for preprocessing the collected data and constructing a database specifically for the elderly; a model building and optimization module for building, training, and optimizing anomaly prediction models; an anomaly identification and early warning module for predicting and comparing real-time collected data, determining the degree of data deviation, and triggering early warnings; a smart service interaction module for pushing early warning information to service personnel, the elderly, and their families; a mindset management module for monitoring the well-being of the elderly; and a resident mutual assistance module for providing mutual assistance reminders. This invention can predict health data for future moments, classifying anomalies based on relative deviation, solving the problem of timely detection of sudden health risks in traditional elderly care, and improving the timeliness of elderly care services.

The invention discloses a miRNA function recognition system and method, a data acquisition module is used for acquiring multiple groups of to-be-analyzed miRNAs and constructing a real-time updated miRNA database based on the Internet, and a model establishment module establishes a real-time updated function recognition model based on a cloud platform and performs real-time update training according to the real-time updated miRNA database. The comparison output module is used for comparing and analyzing the miRNA to be analyzed as the input of the model updated in real time and outputting the function of the miRNA to be analyzed; the miRNA function recognition model is established on the basis of the internet cloud platform, after real-time self-updating is conducted on the model in combination with internet big data, function analysis and recognition are conducted on multiple sets of extracted to-be-analyzed miRNAs, relevance among different diseases is analyzed according to the miRNAs after induction and arrangement are conducted, and powerful support is provided for improving life quality and health of patients.

The application discloses an offshore wind power converter output voltage intelligent modulation control system and method, and belongs to the electrical control technical field.The system comprises a wind power equipment management module, a data acquisition module, a storage database, a model analysis module and an intelligent modulation control module; the wind power equipment management module is used for transmitting the electric energy generated by a wind turbine generator set to a parallel converter to be converted into the form of electric energy and then being connected to a power grid; the data acquisition module is used for acquiring power generation data and converter parameter data; the storage database is used for storing historical data; the model analysis module is used for analyzing the influence of different output voltages on the operation efficiency of the converter and the probability of equipment failure under different converter loss risk values; and the intelligent modulation control module is used for adaptively modulating the output voltages between the converters; and the application maximizes the safety and operation efficiency in the electric energy conversion process.