59 results about "Database model" patented technology

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 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 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 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.

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.

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.

This invention discloses a design method for a casing centralizer used in cementing and a casing centralizer for cementing. The method includes: generating a wellbore-centralizer model based on a data set of multiple main control factors affecting centralizer performance and calculating the corresponding horizontal well cement displacement efficiency value and swirl section length; training a neural network based on the data set of multiple main control factors and the horizontal well cement displacement efficiency value and swirl section length to obtain a centralizer optimization design database model; inputting the design data of multiple main control factors of the centralizer to be designed into the centralizer optimization design database model; determining and outputting qualified design data based on the displacement efficiency value and swirl section length output by the model. This invention predicts the displacement efficiency and swirl section length corresponding to different design parameters through the centralizer optimization design database model, and selects qualified centralizer design parameters accordingly, which can ensure the maximization of horizontal well displacement efficiency and provide accurate guidance for centralizer design.

The invention discloses an incontinence care closed-loop system and method based on perception to service mapping. The incontinence care closed-loop system comprises a sensing acquisition module, a data analysis module, a service mapping module, a service execution module, a care rule base, a database, an AI model, a feedback loop and a nurse intelligent terminal. The system directly converts sensing data into a nursing service instruction by sensing service mapping, and automatic judgment and intelligent scheduling of excrement monitoring, body position monitoring, paper diaper replacement and turning-over nursing are achieved; multi-task linkage execution, task priority, responsibility nursing personnel priority, merging scheduling and AI optimization are supported; an edge-cloud architecture is adopted, and the system is adaptive to multiple scenes of families, old-age care institutions and door-to-door care. According to the invention, automatic closed loop of the whole incontinence nursing process is realized, the nursing timeliness, efficiency and safety are improved, and the labor cost and the disturbance to the nursed person are reduced.

The invention relates to the technical field of shear wall performance evaluation, and discloses a biaxial coupling anti-seismic performance evaluation method and system for a flanged shear wall, and the system comprises an acquisition and preprocessing module which is used for acquiring geometric, material and biaxial coupling load data of the flanged shear wall in real time; after processing, a parameter-performance association database is established in combination with historical data; the model building module performs modeling based on the database and introduces a pre-diagnosis algorithm to identify potential damage risk points; the analysis module inputs real-time data to calculate an anti-seismic performance index, judges a health level, analyzes a degradation rate, predicts a fault probability and generates a pre-diagnosis report; and the management and evaluation module generates a management strategy, outputs an evaluation report, feeds back a data iterative optimization model, and realizes dynamic evaluation of the anti-seismic performance of the shear wall. Scientific basis is provided for safety management of the shear wall, and the anti-seismic safety and operation and maintenance reasonability of the structure are effectively guaranteed.

This application discloses an artificial intelligence-based method for detecting tunnel exterior defects, belonging to the field of data processing technology. The method includes acquiring general defect data, tunnel features, and engineering design parameters of the target tunnel for different tunnels to obtain a basic defect database model; acquiring specific defect data for different tunnels, identifying texture, shape, and color features of the specific defect data to obtain a specific defect database model; generating a drone's identification route based on the engineering design parameters within the target tunnel; acquiring visible light and infrared thermal images of the target tunnel's exterior and identifying defect points; identifying defect points and performing correlation analysis to obtain composite defect risks; constructing a three-dimensional point cloud model of the target tunnel, building a three-dimensional defect map, and formulating a maintenance plan to obtain a maintenance treatment plan. This application improves the accuracy and efficiency of detecting exterior defects inside tunnels.

This invention provides a method and system for determining the stability of intelligent vehicles. The method includes establishing a three-degree-of-freedom (DOF) dynamic model; constructing a three-dimensional phase space based on the DDF dynamic model; dividing the stability domain boundaries of the three-dimensional phase space to obtain an initial stability domain database; optimizing the initial stability domain data using RBF and nonlinear fitting based on the initial stability domain database; dividing the stability state into several instability states based on the optimized stability domain database model, combined with the three-degree-of-freedom dynamic model, the state parameters of yaw stability, the state parameters of roll stability, the yaw angular velocity, and the load transfer coefficient; establishing stability criteria based on these instability states; and using the stability criteria as the intervention condition for the stability controller. This invention solves the problem of traditional methods' difficulty in identifying coupled instability, improves the adaptability and judgment accuracy of stability boundaries, and helps improve the active safety performance of vehicles.

The invention discloses an online efficient prediction method for rolling force and torque in the plate and strip rolling process. The online efficient prediction method comprises the following steps that firstly, rolling parameters are obtained; secondly, actual rolling parameters of rolled passes are collected; 3, calculating a temperature drop influence correction coefficient; 4, calculating rolling force and torque values of subsequent non-rolling passes; fifthly, rolling force and torque calculation results of all passes are output; and sixthly, the rolling force and torque of the follow-up passes are updated till rolling of all the passes is completed. According to the method, any database related to rolled pieces, rolling mills, friction working conditions and the like does not need to be established in advance, the universality and robustness of the model are high, and the defects that in an existing conventional method, a stable and reliable material database needs to be established in advance for accurately representing the current deformation resistance of materials, and time and labor are consumed are overcome; as the model structure is simple enough, the model structure can be directly written into a PLC (Programmable Logic Controller) without being executed in process automation, and is particularly suitable for a rolling production line with lower automation level and without a secondary control system.

The application discloses a database automatic design method and system based on a large language model, which comprises the following steps: based on a large language model combined with a preset chain reasoning prompt engineering template, analyzing and processing natural language requirement information input by a user for a database to obtain a preliminarily constructed database model, including database design elements and an E-R diagram; checking the preliminarily constructed database model for normal form and integrity; after the checking, converting the preliminarily constructed database model into an SQL statement and deploying the SQL statement in a local MySQL database. The application realizes end-to-end automatic conversion from natural language requirements to database structure design, improves database design efficiency, enhances design accuracy and standardization, realizes modularization and decoupling, is easy to extend and maintain, supports full-process closed-loop automation, and can improve user interaction experience and visual effects.

The application relates to a real-time database and a model construction, loading, data subscription and synchronization method, wherein the real-time database is an independent function module in a two-by-two voting security platform, provides an external interface, realizes data interaction, and comprises a database model self-defining module, a data loading module, a real-time data subscription module, a real-time data query module, a real-time data adding and modifying module, a real-time data deleting module, a real-time data synchronization module and a real-time data persistence module. Compared with the prior art, the application has the advantages that the unified organization and management of internal data of the security platform are realized, common key functions such as data sharing between two-by-two voting security platform modules, configuration loading and reading, configuration consistency comparison, master-slave data synchronization, master-slave state interaction, input-output consistency comparison and the like are conveniently provided, and the like.

The invention provides an intelligent vehicle stability determination method and system. The method comprises the following steps: establishing a three-degree-of-freedom dynamic model; constructing a three-dimensional phase space based on the three-degree-of-freedom dynamic model Dividing a stability domain boundary of the three-dimensional phase space to obtain an initial stability domain database; based on the initial stability domain database, performing optimization and nonlinear fitting on the initial stability domain data by using RBF (Radial Basis Function); and the stability state is divided into a plurality of instability states by combining the three-degree-of-freedom dynamic model, the state parameters of the stability of the yaw, the state parameters of the stability of the roll, the angular velocity of the yaw and the load transfer coefficient, a stability criterion is established based on the instability states, and the stability criterion is used as an intervention condition of a stability controller. The method solves the problem that a traditional method is difficult to identify coupling instability, improves the adaptability and judgment precision of the stable boundary, and facilitates the improvement of the active safety performance of the vehicle.