102 results about "Database design" patented technology

A platform for dynamically generating application experiences. The platform comprises a design management system, an agent orchestration system, an analytics system, a model management system, a user management system, and databases for storing design elements and templates. The design management system provides a portal for application owners / designers to create UX / UI designs, allowing them to select design elements from a set of categories or templates. The platform gathers existing websites / applications to identify common design patterns, stored in a design catalogue database, and suggests historical interfaces for design exploration. It enables the generation of templated applications that integrate with legacy systems. The agent orchestration system parses user specifications, selects generative AI systems, and generates UX / UI content based on the specifications. The analytics system collects and analyzes data to provide insights for improving UX / UI design and optimizing website performance. The model management system trains and maintains generative AI models used for content generation.

The invention relates to a data-driven lithium ion battery voltage prediction modeling method fusing physical information, and belongs to the technical field of batteries. According to the method, a multi-working-condition battery operation database is constructed, a terminal voltage prediction model fusing a physical model and a neural network is designed, a mathematical constraint relation is established for equivalent circuit parameters and neural network intermediate variables, and data driving characteristics and physical parameters are jointly optimized by using a gradient descent method. The method specifically comprises the steps of collecting battery current, voltage and temperature data; constructing an input feature and an output tag; outputting an intermediate variable through a parameter layer and associating an equivalent circuit parameter; and introducing physical loss function constraint model training to ensure the physical rationality of parameters. The method has high precision of data driving and interpretability of a physical model, improves multi-working-condition adaptability through temperature compensation and parameter constraint, and can be widely applied to battery state estimation and health management of electric automobiles and energy storage systems.

The invention discloses an archive arrangement system and method capable of achieving multilingual conversion, and relates to the technical field of archive arrangement. The system comprises a multilingual archive database, a semantic analysis module, a retrieval matching module and a user interaction interface; according to the method, a multi-language association retrieval system based on semantic understanding is constructed, a semantic deep mining algorithm, a cross-language semantic association algorithm and a semantic association degree algorithm are applied, the effect of accurately matching semantic similar contents in files of different languages is achieved, and automatic index updating and incremental updating algorithms are designed for a multi-language file database, so that the accuracy of the multi-language file database is improved. According to the method, the effect of efficient file storage and query is achieved, complexity and resource waste of index updating during new file input or information change are avoided, the effect of extracting semantic features more accurately is achieved by customizing preprocessing processes for different language texts and combining a word vector generation algorithm based on semantic context, and the efficiency of file storage and query is improved. And the accuracy and efficiency of multi-language archive arrangement are improved.

The invention discloses an industrial robot collaborative optimization system, which relates to the technical field of humanoid robots and comprises a joint state acquisition module for acquiring joint torque, angular velocity, acceleration and external disturbance data in real time; the joint first constraint analysis module is used for decomposing a motion task into a high-level task and bottom-level joint control, introducing joint limiting and torque saturation constraint, solving joint optimal torque distribution through QP quadratic programming, and obtaining a first joint torque distribution result; the second joint constraint analysis module is used for designing a multi-objective optimization function based on the first joint torque distribution result and a humanoid robot joint real-time state database, carrying out weight self-adaption according to the humanoid robot joint real-time state database, synthesizing the weight of the multi-objective optimization function according to a dynamic weight, and obtaining a second joint torque distribution result; and solving an optimal joint angle, speed and moment sequence to obtain a joint moment optimal distribution result. Joint abrasion can be effectively reduced, and meanwhile task adaptability and energy efficiency optimization are enhanced.

The invention belongs to the technical field of teaching management, and discloses a sports classroom multi-dimensional data dynamic weight evaluation method and system. Comprising the steps of collecting physiological index data and classroom image data to obtain student data; performing data cleaning on the student data, and constructing and perfecting a student classroom database; constructing a dynamic weight model and carrying out iterative optimization to obtain an optimized dynamic weight model; performing dynamic weight distribution on the perfect student classroom database by utilizing the optimized dynamic weight model to obtain a weighted student classroom database; constructing a multi-dimensional evaluation framework to perform classroom performance evaluation on the weighted student classroom database, and outputting a classroom performance index of each student; classifying the weighted student classroom database to obtain a marked student classroom database; designing a personalized sports classroom teaching strategy, and sending the personalized sports classroom teaching strategy to a preset teacher terminal; student classroom performance evaluation is carried out by applying the dynamic weight, and personalized teaching of teachers is facilitated.

The invention discloses a machine learning driven vehicle frame lightweight design method, which comprises the following steps: (1) performing vehicle frame parametric modeling in CATIA, constructing a vehicle frame modal analysis model and a stiffness analysis model in ABAQUS, and deducing a mathematical model of vehicle frame lightweight design; (2) performing Latin hypercube sampling and discrete Gaussian sampling on continuous and discrete parameters to generate a frame population, and establishing a database; (3) designing a variable type driven hybrid variation mechanism to obtain a candidate frame population; (4) constructing a radial basis function machine learning model, and deducing a comprehensive minimum statistical lower limit function to screen an optimal candidate frame; and (5) performing parametric modeling and simulation analysis on the optimal candidate frame, updating the frame population and the database, returning to the step (3) until the optimal frame meets the design requirement, and outputting the optimal frame. According to the method, adaptive variation strategies and screening functions are designed according to the vehicle frame parameter characteristics, and the vehicle frame lightweight design effect is good.

The invention provides a geological map three-dimensional visualization method and system based on a database technology, and belongs to the field of geological map visualization. The method focuses on geological map resources, deeply fuses spatial information and attribute information of the geological map, designs a geological map three-dimensional coordinate system based on geological age strata, designs a geological map three-dimensional space data and attribute data storage structure, and provides a relatively effective solution for multi-modal geological resource association. The geological map resources and associated data thereof are systematically stored and managed through a database, the geological map resources are standardized and efficiently integrated, and the innovative purpose of effectively supporting true three-dimensional visualization expression and analysis of geological elements is achieved by relying on a three-dimensional visualization platform. The geological map three-dimensional visualization method based on the database technology comprises the following steps: step (1), data and association thereof; step (2), data processing; step (3), database design; step (4), application; multi-modal geological data is stored based on a database, and a geological map three-dimensional visualization platform is built in combination with a three-dimensional visualization engine.

The invention discloses an amphibious aircraft alarm database design method, an alarm system and an alarm method. Determining the alarm demand of each alarm demand side based on scenarized demand capture and confirmation; converting each alarm demand into an alarm entry with an alarm attribute, wherein each alarm entry is in a decoupling state; and finally, constructing an alarm database through the alarm entries. According to the invention, the alarm demand conversion efficiency and the alarm realization accuracy of the airplane can be improved.

The invention discloses a transformer substation-oriented multi-source heterogeneous data checking method and system. The method comprises the following steps of obtaining various types of data sources, executing a preliminary data cleaning process and outputting standardized data; aiming at database systems of different manufacturers, designing a customized migration tool for each database; extracting specific attribute information contained by the special domain analysis module by constructing the special domain analysis module; sequentially verifying the source database and the target database by adopting a progressive consistency verification strategy, and recording data difference information detected in each stage; a change rationality verification module is configured to analyze an SCD file of the transformer substation, and change rationality judgment is performed on difference items from a source database to a target database; performing unified modeling and graphical display on the obtained difference information through a difference data visualization module; according to the method, the data consistency and correctness in the upgrading and transformation process of the transformer substation monitoring system database are comprehensively verified, so that the stability and the operation reliability of the system are improved.

The invention discloses a slope anchor cable prestress measuring method based on data clustering. The slope anchor cable prestress measuring method comprises the steps that a multi-dimensional database containing environment characteristics, echo energy and counter-pulling method prestress values is constructed; a mixed distance clustering algorithm is designed, numerical features and classification features are jointly processed, and automatic data classification is achieved by iteratively updating a cluster center; the cluster quality is dynamically evaluated based on the contour coefficient, and only when the sample size is gt; 3 and an average contour coefficient gt; constructing an exclusive regression model in the cluster when the contour coefficient is a threshold value; and finally predicting the anchor cable prestress in real time through echo energy. According to the method, the prediction precision under the complex working condition is remarkably improved, the use frequency of the reverse drawing method is reduced, and safe and efficient prestress nondestructive testing is achieved.

The invention provides an artificial intelligence-based data analysis method, which comprises the following steps of: integrating and cleaning collected multi-source data, storing the data into a relational database, designing an entity-relationship-based data model to construct nodes and relationships, and storing the nodes and the relationships into the relational database; analyzing and calculating the knowledge graph through a community discovery algorithm, a graph neural network and quantitative analysis to capture complex features and potential abnormal conditions of the knowledge graph; and fitting three results of the community discovery algorithm, the graph neural network and the quantitative analysis through an integration algorithm, and generating final suspicious score judgment in a multi-party weighted voting mode. According to the method, suspected problem clues are extracted from thousands of or even hundreds of thousands of data, a possible clue direction is provided for case investigation, problems can be found more timely, supervision is more accurate and efficient, and case handling efficiency is improved.

The invention relates to the technical field of oil and gas pipeline valve inner leakage online diagnosis, and discloses an oil and gas pipeline valve inner leakage online diagnosis method based on voiceprint analysis. According to the method, valve operation voiceprint data are obtained through a distributed interface to construct a feature database, a diagnosis framework is designed according to the database, and a multi-source voiceprint collection scheme is determined. And the voiceprint acquisition terminal acquires a multi-dimensional voiceprint signal according to the scheme, inputs the multi-dimensional voiceprint signal into a model after feature extraction to complete inner leakage level judgment and abnormal mode recognition, and outputs a diagnosis result. A diagnosis result is transmitted to the management optimization module, and diagnosis strategy adjustment is achieved through timestamp calibration, mapping table construction and the like. And a three-level evaluation sub-frame is also constructed to assist diagnosis. According to the method, accurate diagnosis and strategy optimization of oil and gas pipeline valve inner leakage are realized, and the diagnosis management level is improved.

The invention provides an intelligent prediction method and system based on a thermal working area and a maintenance range. The method comprises the following steps: S1, acquiring point location data of a thermal working area in real time, and uploading the point location data to a server through a data transmission protocol; s2, storing point location data by using a time sequence database, and performing data management based on a timestamp, a tag field and a measurement value; s3, performing incremental training on historical data and real-time data based on a machine learning model, and dynamically predicting a maintenance loss risk prediction result; s4, dynamically loading the thermodynamic point location data according to the zoom level of the user interface map; s5, generating a resource allocation strategy based on a prediction result, and dynamically scheduling maintenance resources according to risk levels; the invention has the following advantages; 1, the real-time performance of data acquisition and processing is enhanced; 2, the intelligence and accuracy of the prediction algorithm are improved; 3, high efficiency of thermodynamic point location data display; and 4, the expansibility and the performance of database design are optimized.

The invention aims to provide a gas turbine remote maintenance method based on a knowledge base. The gas turbine remote maintenance method comprises the following steps: collecting data related to operation maintenance; establishing a system three-dimensional model database; defining a definition relationship between the gas turbine parts and the data; designing the structure of the knowledge base, and defining related attributes; importing the processed data into a database to form an operation and maintenance database; designing and developing a human-computer interaction interface based on mixed reality head-mounted equipment, and integrating the human-computer interaction interface with an operation and maintenance database to obtain a gas turbine remote maintenance system based on a knowledge base; operation and maintenance personnel use the integrated system to carry out function testing; the integrated system is connected with a remote expert, and the expert assists operation and maintenance personnel in analyzing problems, pushing data and guiding problem processing online. According to the invention, with the assistance of the mixed reality head-mounted device, the operation and maintenance personnel can rapidly position the root of the fault and take targeted maintenance measures, so that the fault diagnosis and maintenance efficiency is greatly improved.

The invention relates to the field of energy storage management, in particular to a large-scale battery health degree prediction method for an energy storage power station. Preprocessing the data in the field to obtain processed data; initializing a vector database, and importing the processed data into the vector database; designing a first Prompt, packaging the input test data into the first Prompt, and then calling the large model to predict the input test data to obtain a large model SOH predicted value; based on input test data, N SOH values are retrieved from a vector database; on the basis of the SOH predicted value of the large model and the retrieved N SOH values, optimizing the first Prompt so as to call the large model to carry out iterative prediction on the input test data until the SOH predicted value, obtained through iterative prediction, of the large model meets a preset condition; and calling the large model to output a battery health evaluation and optimization suggestion based on the integrated SOH predicted value and the second Prompt. According to the method, reliable and effective large model prediction can be carried out on the specific field of the energy storage power station with low investment cost.

Provided are a data query method, an electronic device and a computer readable storage medium. A public relation table is added between a first-stage table and sub-tables corresponding to the first-stage table in database design, wherein the public relation table comprises a single record corresponding to each sub-table needing to be associated, and represents the association relationship between a root node and other nodes in a relation tree.

The invention belongs to the technical field of software engineering, and particularly relates to a quick code repairing method for lightweight compressed context generation. According to the method, efficient repair is realized by constructing a'retrieval-compression-generation 'collaborative architecture; comprising the following steps: constructing a cross-file code retrieval database, designing a lightweight semantic compression encoder (SCE), and compressing retrieved cross-file code blocks into short tokens with high semantic density; semantic compatibility with a large language model (LLM) is realized through a two-stage training strategy; wherein in the semantic alignment stage, the SCE is trained so that the compression token can be accurately analyzed by the LLM, and in the task alignment stage, the LLM is finely adjusted so that the compression token can be utilized to complete repair. Experiments show that on the premise that key logic dependence is reserved, the reasoning efficiency of the model can be improved, the code repairing effect is guaranteed, the method is suitable for cross-file dependence repairing scenes of a large code warehouse and can be integrated into integrated development environment plug-ins, automatic code auditing tools and the like, and the software development and maintenance efficiency is remarkably improved.

The invention provides a rapid detection method for degradation performance of degradable plastics, and relates to the technical field of degradable plastics. The rapid detection method for the degradation performance of the degradable plastic specifically comprises the following steps: S1, establishing an auxiliary database; s2, designing rapid separation and purification; s3, using a Fourier transform infrared microscope; s4, detecting by using activated vermiculite; s5, debugging, and performing rapid separation and purification; and S6, combining the biodegradation rate and the heavy metal index. The rapid detection method for the degradation performance of the degradable plastic is very high in detection accuracy and reliability, supports a sustainable development policy and an ecological environmental protection target, and provides powerful technical support for improvement of the detection capability of enterprises in the industry.

The invention relates to a dynamic extensible composite material database design method, and relates to the field of computer simulation technology, the method comprises the following steps: S1, creating a TPID database, respectively creating a T table, a P table and an I table, mapping the T table, the P table and the I table based on ORM technology to create the TPID database, the T table being a type table, the P table being an attribute classification table, and the I table being an attribute item table; s2, managing tree structure data based on a pre-sequencing traversal tree model; s3, creating a template table based on the format of the TPID database, collecting data of the composite material based on the template table, and inputting or updating the data of the composite material into the TPID database; s4, establishing a Redis cache library, extracting an attribute classification table of high-frequency access, and storing the attribute classification table into the Redis cache library; and S5, obtaining a query result, obtaining a query instruction, and extracting data through the pre-sequencing traversal tree model or extracting data from the Redis cache library based on the category of the query instruction. According to the method, the efficiency of querying data in the database by engineers can be improved.

The invention aims to provide a gas turbine expert remote fault diagnosis and guidance method based on a mixed reality technology. The method comprises the following steps: establishing a gas turbine remote fault diagnosis database; establishing a three-dimensional electronic maintenance manual database of the gas turbine; designing and developing a network communication module; designing and developing a gas turbine audio and video call function; developing automatic pushing, manual retrieval and online loading of a three-dimensional electronic maintenance manual; a client and server network management module based on mixed reality is designed and developed, and a model data synchronization environment for gas turbine fault diagnosis and guidance is generated; performing system integration on the three-dimensional electronic maintenance manual and a network management module, and designing and developing a remote fault diagnosis model; a man-machine interaction function is designed and developed and is integrated with a remote fault diagnosis model function. The defects that in the diagnosis process, experts cannot arrive at the site in time, the drawing and technical file checking speed is low, and results are not easy to understand can be overcome.

The invention discloses a data processing method and device based on an AI model. Identifying data from at least one data source, and determining sample data from the identified data; performing data analysis on the sample data through an AI model to obtain a data analysis result; a classification identifier is added to the identified data through an AI model; generating a data processing rule based on an analysis result of the data analysis, writing a database design script, and synchronizing the data processing rule and the database design script to a data processing platform; and accessing the data source to a data processing platform, preprocessing the collected data by using a data processing rule through the data processing platform, generating a database table by using a database design script, importing the preprocessed data into the database table, and storing the preprocessed data based on the classification identifier. According to the invention, data acquisition and rapid analysis are carried out through AI, rapid storage of various data in the park is realized, and the problems of low data processing efficiency, low data utilization rate and insufficient data security in the prior art are solved.

The present application belongs to the technical field of industrial detection, and particularly relates to a conveying belt laser vision tear detection system and method, comprising a layered storage architecture to construct a dynamically updated cross-model conveying belt basic database; a working condition adaptive dynamic enhancement model is designed to perform data enhancement processing on the constructed cross-model conveying belt basic database; an improved YOLOv13 vision tear detection neural network model is constructed to realize cross-model conveying belt laser vision tear intelligent detection; and a multi-dimensional three-level evaluation index system is established based on the vision tear intelligent detection result. The present application effectively improves the range, intelligent degree and detection accuracy of the conveying belt laser vision tear detection, and realizes digital quantifiable evaluation of the conveying belt tear degree.

According to some embodiments, methods and systems may be associated with a cloud computing environment. A workload prediction framework may receive observed workload information associated with a database in the cloud computing environment (e.g., a DataBase as a Service (“DBaaS”)). Based on the observed workload information, a Statement Arrival Rate (“SAR”) prediction may be generated. In addition, a host variable assignment prediction may be generated based on the observed workload information. The workload prediction framework may then use the SAR prediction and the host variable assignment prediction to automatically create a workload prediction for the database. A physical database design advisor (e.g., a table partitioning advisor) may receive the workload prediction and, responsive to the workload prediction, automatically generate a recommended physical layout for the database (e.g., using a cost model, the current physical layout, and an objective function).

Adaptive content delivery systems and methods are disclosed herein. An example system is configured to determine capabilities of a requesting end user system, interface with a database designed to store images characterized by criteria, select an image from the database that balances a highest quality and a smallest file size for the end user system, based on the capabilities, and provide the image to a network for delivery to the end user system.

The invention belongs to the technical field of nuclear power, and particularly relates to a system data migration method and device. According to the system data migration method provided by the invention, aiming at two sets of PDM systems which are deployed in different environments, different in deployment architecture design and different in function, the problems that database design and historical data of the two sets of PDM systems are inconsistent, massive documents / CAD files processed by an algorithm are stored, the data structure is complex, multiple data bottom layer incidence relations exist, and deep coupling exists can be solved; data of the two PDM systems are rapidly and accurately migrated, and functions of the two PDM systems are combined. Therefore, file transmission is realized in a system deployment environment with strict limitation, and functions of two sets of systems with huge difference are combined quickly and accurately.

The invention provides a method and a system for establishing a relationship between data tables, and belongs to the technical field of big data. Comprising the following steps: S1, foreign key constraint: explaining how the foreign key constraint maintains a relationship between tables, including cascade operation and reference integrity, and discussing an implementation mode of the foreign key constraint in a database, such as use and optimization of an index; s2, a connection table explains the effect of the connection table in processing a many-to-many relationship, including the structure and use of an intermediate table, and analyzes the influence of the connection table on query performance and an optimization strategy; and S3, self-association: how self-association supports storage and query of tree structure data is described, and advantages and disadvantages of self-association in database design are discussed. According to the system for establishing the data table relation, the foreign key constraint of the RDBMS is taken as a core, logical association is realized through the primary key, the foreign key and the relation type definition, and the non-relational database simulates the relation through a reference or embedded document, so that the data consistency and the query efficiency are ensured.

The invention discloses a land value spatio-temporal database design method and system, which are applied to the technical field of spatial geographic information data processing and image correction and are used for acquiring spectral remote sensing image data. Performing geographic coordinate matching on the spectral remote sensing image data to generate coordinate spectral remote sensing image data; performing digital rasterization on the spectral remote sensing image data through a digital elevation model to generate point cloud data, and performing three-dimensional reconstruction according to the point cloud data to obtain a three-dimensional landform model; performing boundary region reconstruction processing on the three-dimensional landform model to obtain a reconstruction model; performing ground feature extraction on the reconstruction model to obtain ground feature data; performing spatio-temporal indexing on the ground feature data to construct a spatio-temporal database; according to the method, brightness correction can be carried out on edge defects of interval type and linear ground features according to predicted brightness changes, gray distortion of a three-dimensional image can be greatly reduced, and blur caused by interference is eliminated.

Systems and methods of the present disclosure relate to workflow optimization for farm level food waste. A method includes employing a material database design for identifying new uses for food waste. The method further includes image processing for verifying aesthetic imperfections of produce, and supply chain optimization for addressing supply chain challenges.

The embodiment of the invention provides a dangerous chemical database design method and system, and belongs to the technical field of data processing. The system comprises a system management module, a database management module, a hazardous chemical data module, a scene adaptation module and a dynamic analysis and evaluation module. The system management module comprises a user management sub-module and a role management sub-module; the database management module comprises a hazardous chemical substance data management sub-module and a report data management sub-module; the hazardous chemical substance data management sub-module is used for newly adding, editing and deleting hazardous chemical substance data; the report data management sub-module is used for newly adding, editing and deleting report data; the hazardous chemical data module is used for storing data information of chemicals; the scene adaptation module is used for adapting to different management scenes; the dynamic analysis and evaluation module is used for generating a management scheme. According to the invention, customer groups can be analyzed according to basic data, customer resources can be developed in a targeted manner, and statistical data of chemical risk assessment can be summarized and processed.

The blood donation and use database design scheme is a blood donation point management system designed for solving the difficulty in recruitment of blood donors based on the current blood collection and supply management system and blood donation and use mode in China, and the blood donation point management system operates independently, is connected with a blood station business management system, solves the supply and demand contradiction from the blood use link of a hospital, recruits the blood donors, and improves the blood donation efficiency. The blood donation amount and the blood use amount are converted into equivalent points to serve as accounting symbols, a database is used as a carrier, three blood use modes are divided according to blood use scenes, blood donation point use rules are formulated, and virtual blood donation points and actual blood donation points are shared by utilizing overdraft and payment functions of the database, so that the form requirement of using blood according to the blood donation points is met; the essence of blood use without blood donation points is overdraft, relatives of a patient are required to donate blood and points or commitment subsequent blood donation, the policy is public, fair and transparent, mutual-aid blood donation legalization is supported, and endogenous motivation of citizens participating in blood donation is motivated; the hospital uses remote blood donation points to provide convenience for remote medical treatment and blood use; the non-local blood donation integral net value is the basis for blending and dispensing blood products from integral inflow places, can assist in solving the contradiction and problem that medical resources are rich and blood sources are insufficient in extra-large cities such as Shanghai in Beijing, and is suitable for being popularized and used nationwide.