109 results about "Interactive visualization" patented technology

The invention relates to the technical field of data processing, in particular to an intelligent supervision method and system based on a data visualization platform, and the method comprises the steps: collecting multi-source water conservancy data through dual-channel redundancy check, converting the multi-source water conservancy data into a standardized space-time matrix, carrying out the data cleaning through a containerization adaptation and variational auto-encoder, and marking the confidence; hierarchically storing the data based on a confidence threshold, and generating a routing strategy through reinforcement learning to distribute data fragments; calculating a flood peak evolution prediction result by using space-time diagram convolution, calculating an output risk assessment value by combining a Bayesian network and long and short-term memory, and activating federal learning parameter updating when the confidence coefficient is insufficient; the digital twin model loads physical constraint parameters to deduce a flood control scene, and a scheduling instruction set and a rehearsal animation are generated through multi-objective optimization; and dynamically rendering to generate an interactive visual interface, associating a causal deduction path, and triggering federal model parameter updating by user feedback, thereby realizing dynamic collaboration of the forecasting and early warning rehearsal plan function chain.

The invention relates to the technical field of digital twinning, in particular to a real-time interactive visualization system and method based on digital twinning, and the system comprises a data collection module which is used for configuring a multi-protocol adapter deployed on a physical equipment layer to collect the operation data of physical equipment, and transmitting the operation data of the physical equipment to an edge computing node. According to the method, the general data adapter is used for driving the three-dimensional rendering engine to execute real-time rendering based on physics, so that the virtual scene can dynamically reflect details such as illumination change and material aging of a physical entity, and high-fidelity visual feedback is provided. According to the method, a closed-loop control mechanism is established in combination with a multi-modal interaction framework, pure data monitoring is converted into operable bidirectional interaction, operation of a user on a visual interface can be converted into feedback instructions in real time to reversely adjust physical equipment, and the response efficiency of remote operation and maintenance is improved.

The invention relates to the technical field of data analysis, in particular to a dialogue type data analysis method, system and device based on a large language model and a medium, and the method comprises the steps that a natural language query request input by a user is acquired, semantic analysis is conducted on the natural language query request through the large language model, and key query elements are extracted; generating a structured query instruction according to the key query elements; calling a data integration engine based on the structured query instruction, and obtaining target data from the plurality of heterogeneous data sources; performing processing analysis on the target data, wherein the processing analysis comprises drilling-down analysis, attribution analysis and anomaly detection; and generating an analysis report and a visual chart based on the processing analysis result, and feeding back the analysis report and the visual chart to the user. According to the method, high-precision intention analysis and multi-source data integration can be realized, deep analysis and interactive visualization are supported, and the accuracy, efficiency and user experience of data analysis are remarkably improved.

The invention provides a software architecture governance system based on automatic modeling and holographic penetration analysis. The software architecture governance system comprises multiple modules: a project management module used for managing all analysis projects; the source code management module is used for pulling, updating and deleting project source codes; the analysis drive management module is used for uniformly managing and calling analysis drive programs; the multi-language analysis driving cluster is integrated with analysis driving programs corresponding to multiple programming languages and is responsible for analyzing source codes, generating a standardized software chart model and storing the standardized software chart model in a database; the rule engine module is used for supporting a complex code analysis service; the cross-project integrated analysis module generates a system architecture diagram according to the plurality of software models and stores the system architecture diagram into a diagram model library; the multi-dimensional data fusion interface module provides penetrating analysis interfaces of a code layer, a design layer and a framework layer; and the architecture model visualization module is responsible for displaying the system architecture in a multi-dimensional visualization manner. The method can be used for automatic modeling, tracing analysis and interactive visual presentation of a complex system architecture.

The invention provides a satellite image fuzzy query method and system based on multi-dimensional vectorization indexing, and relates to the technical field of satellite image retrieval, the method comprises the following steps: mapping a structured query condition generated based on natural language query into a three-dimensional hierarchical index condition structured database to retrieve and output three-dimensional index metadata; and after the three-dimensional index result set is loaded according to the three-dimensional index metadata, space-time interaction visual output for generating the three-dimensional index result set is carried out by taking dynamic weight distribution as a sorting basis. The technical problems that in the prior art, satellite image high-response query cannot be carried out based on user fuzzy expression, so that the satellite image data query and calling efficiency is low, and the query result practicability is insufficient are solved. The technical effects that full-link closed-loop retrieval driven by natural languages is achieved, query flexibility is improved through intelligent mapping, efficient positioning is guaranteed through multi-dimensional indexing, the accuracy of dynamic sorting optimization results is guaranteed, and interaction friendliness is visually enhanced are achieved.

A system for automated real-time publication processing may comprise a data collection module configured to automatically gather data from multiple external sources. A data analysis module may be configured to process the gathered data using artificial intelligence models. A data visualization module may be configured to generate interactive visual representations of the processed data. An update control module may be configured to automatically update published content and maintain version history with timestamps. The data collection module may utilize application programming interfaces and web scraping tools to gather data from government databases and real-time data feeds. The data analysis module may employ machine learning libraries to process and analyze the collected data. The data visualization module may use visualization tools to create interactive charts and graphs. The update control module may use Git-based version management and automated scheduling scripts to implement updates and record modification dates.

A multi-dimensional data processing system is disclosed for the automated ingestion, normalization, and computational mapping of project data across spatial, temporal, and regulatory dimensions. The system operates by ingesting diverse datasets—including two-dimensional schematics, three-dimensional data models, cost structures, and workforce logistics—and normalizing them within a unified schema. A dimensional calculations model enables the system to computationally align normalized data with spatial zones, project phases, and operational constraints, structuring it for further computational processing. By integrating this mapped data within a coordinated digital environment, the system applies task sequencing and resource allocation algorithms, generating optimized project plans that support complex, multi-dimensional data interoperability. The structured data is further configured for display through an interactive visualization interface, allowing computational resources to facilitate real-time analysis and adaptive data-driven project management.

The invention discloses a three-dimensional visualization method, system and device based on heterogeneous spatial data fusion and dynamic sectioning, and a medium, belongs to the technical field of urban information model visualization, and aims to solve the technical problem of how to improve data fusion efficiency, sectioning response delay and mobile terminal frame rate in a million patch scene. Light-weight and high-interaction visual display of scenes such as smart cities and underground pipe galleries is realized, and the defects of multi-source spatial data splitting, high sectioning interaction delay and poor cross-terminal compatibility are overcome. According to the technical scheme, heterogeneous data dynamic normalization is carried out, wherein local coordinates of a building information model, WGS84 coordinates of a geographic information system and computer aided design data are unified to an Euclidean coordinate system through a space dynamic reference conversion algorithm, and normalized data are obtained; constructing a semantic data relation graph; generating a dynamic sectioning plane in real time; vector elements are highlighted in a linkage manner; and carrying out cross-terminal adaptive rendering.

The invention discloses a digital twin-driven intelligent construction site resource dynamic scheduling system and method, and belongs to the technical field of building construction management, and the system comprises a four-dimensional resource topology construction module which constructs a four-dimensional topological graph of construction resources based on UWB and RFID technologies; the mixed engine scheduling module adopts a mixed integer programming engine to generate a reference scheduling scheme in an initial stage, and adopts a reinforcement learning optimization engine to perform dynamic adjustment in an execution stage; the conflict prediction network module is used for establishing a conflict prediction model based on historical data and triggering a resource redistribution mechanism; the virtual interaction visualization module displays a scheduling scheme in a virtual reality environment and supports manual intervention, depth relation modeling, double-engine collaborative optimization and active conflict prevention of construction resources are achieved, the resource utilization rate is increased by 35% or above, the construction period is shortened by 15% or above, and conflict events are reduced by 50% or above.

Systems and methods are described to determine relationships between one or more components of an isolated execution environment system based on data obtained from a data intake and query system. Based on the determined relationships, an interactive visualization is generated that indicates the hierarchical relationship of the components. In some cases, to illustrate the relationship between components of the isolated execution environment system, the visualization can include one or more display objects displayed in a subordinate or superior relationship to other display objects. In certain cases, based on an interaction with a display object, the system can generate a query and / or display additional information and / or visualizations based on the results of the query.

The invention relates to the technical field of big data processing, in particular to a multi-source data fusion generation method for a diabetic foot health status assessment report, which comprises the following steps of: firstly, converging and preprocessing multi-modal heterogeneous data from wearable equipment, clinical input and historical records; the method comprises the following steps of: firstly, extracting data by using an attention mechanism-based deep learning network, then extracting deep correlation features among the data by using an attention mechanism-based deep learning network, then analyzing fusion features through a mixed decision engine combining rule reasoning and a machine learning model, generating structured risk assessment tags, and finally, dynamically calling parameterized templates by a system according to the tags, thereby realizing risk assessment. And a natural language generation technology is utilized to output an interactive visual evaluation report capable of performing personalized rendering according to a user role. According to the method, multi-source data can be automatically fused, deep analysis is carried out, a personalized, dynamic and interactive report is generated, and original and isolated monitoring data is converted into intelligent insight capable of guiding clinical actions.

A graphical, hierarchical document stream browser and environment for semantic (e.g. framing) and performance data analysis and interactive visualization integrates three scales: entities (competitive), entity (diachronic), and document (linguistic). The document level includes annotation and computational linguistics facilities; the entity level has calendrical and time-series focus. All levels emphasize deep linkage and network (i.e. connective / relational space) view of objects, with user-configurable connectivity. Large language model (LLM) integrations provide synthetic advisories, public opinions, reports, plot insights, comparisons; traditional natural language processing techniques and neural models are also employed. A smart plot system includes a “plot cart” and interpreter with an analysis snippet library. Graph structure may arise via adjustable blending or perceptual optimization of canned attribute-related distance functions or via link-induction query language with deep “semantic stored procedure” subexpressions, or feed into graph neural network-style inference for predictions. Most non-LLM ongoing computational load is client-side, using precomputed hierarchical summary files.

Approaches are described for facilitating remote ophthalmic examinations using three-dimensional (3D) imaging and mixed reality technology. A system obtains real-time or stored 3D data of a patient's eye, capturing detailed anatomical structures. The system analyzes the 3D data to identify specific regions of the eye, such as the cornea or retina, and retrieves corresponding diagnostic data and patient-specific clinical information. The 3D data, diagnostic metrics, and clinical records are integrated to generate an interactive visualization, which is presented through a mixed reality interface. The system allows healthcare professionals to manipulate diagnostic overlays, investigate flagged abnormalities, and adjust the visualization using gesture-based inputs. Machine learning models may be applied to detect potential abnormalities in the eye, while the system also determines stages of the examination based on changes in the anatomical structure of the eye.

The invention relates to a report processing method and device, computer equipment, a storage medium and a program product. The method comprises the following steps: constructing and deploying a configuration table system in a business database, wherein the system comprises a job configuration table, a job dependency table, a report parameter table and a front-end display configuration table; and performing semantic analysis on the historical task logs of the batch jobs recorded in the job configuration table through the large language model, and outputting a dynamic scheduling strategy which is used for adjusting the initial execution frequency and the resource allocation quantity of the batch jobs in the job configuration table. By identifying entity information in a user service query instruction and matching an optimal chart type, accurate conversion from a database field to a front-end display field is completed in combination with a front-end display configuration table. And finally, an interactive visual chart is generated. By adopting the method, the data change rule can be intelligently analyzed, the business decision-making efficiency is improved, and meanwhile, the comprehensive cost of report development, operation and maintenance is effectively reduced.

The embodiment of the application discloses a rule engine interactive visual construction method and a computer readable medium; the construction method comprises the following steps: constructing a metadata structure of a rule engine table; constructing a one-to-one reversible mapping relationship between the rule engine table and an SQL statement; constructing a one-to-one reversible mapping relationship between the rule engine table and a CQL statement; taking the constructed rule engine table as a bridge, and performing interactive configuration through a visual interface of a rule engine front end, and performing mutual conversion of the SQL statement and the CQL statement. The construction method can more conveniently and effectively perform subsequent analysis based on table data, and also provides a basis for interactive configuration of a webpage end; the interactive configuration provides a table field set, and enables a business personnel to select in a check manner, and the field set displayed to the personnel can also be controlled according to permissions. The method has the beneficial technical effects of simplifying operation difficulty, standardizing code format and flexibly controlling permissions.

The invention discloses a computer algorithm visualization teaching generation system based on a large model, and relates to the technical field of artificial intelligence-driven education. The work content of the system comprises the following steps: constructing a mapping relationship between algorithm categories and features, generating an understandable feature set, and labeling difficulty levels; guiding a user to select an algorithm category and program a basic label through a graphical algorithm classification graph; k rounds of dynamic questions and answers are adopted, questioning features are screened based on an information entropy gain ratio, and answer vectors are constructed in combination with user answers; through cosine similarity matching algorithm feature vectors, teaching content is recommended, difficulty is adjusted, or non-questioning features are supplemented and inquired; and converting the user data into a natural language text, calling a preset large model interface to generate a learning suggestion, and performing interactive visual display. According to the system, a whole-process closed loop of algorithm teaching from data acquisition and preprocessing to dynamic generation and personalized recommendation is realized, and the teaching precision and efficiency are improved.

Exemplary systems and methods for visualization of data analysis are provided. In various embodiments, a method comprises accessing a database, analyzing the database to identify clusters of data, generating an interactive visualization comprising a plurality of nodes and a plurality of edges wherein a first node of the plurality of nodes represents a cluster and an edge of the plurality of edges represents an intersection of nodes of the plurality of nodes, selecting and dragging the first node in response to a user action, and reorienting the interactive visualization in response to the user action of selecting and dragging the first node.

The invention relates to the technical field of financial data analysis, in particular to an interactive financial data retrieval and analysis system based on big data. Comprising a data access module, a data unification module, a semantic understanding and intention recognition module, a retrieval execution module, a financial analysis module and an interactive visualization module. The system can access financial information from multi-source data and perform cleaning, standardization, main data alignment and management to generate data for query and analysis. Query intentions and entities are recognized through natural language analysis, structured semantic representation is constructed, and multi-dimensional aggregation, backtracking and predictive analysis are achieved. And the retrieval execution module and the financial analysis module cooperate to ensure that the result is reproducible and credible. And the interactive visualization module dynamically presents the analysis result. According to the method, accurate understanding and structured representation of natural language query of the user are realized, so that financial data retrieval can quickly respond to the intention of the user, the query accuracy and efficiency are improved, and the reliability and precision of financial decisions are improved.

This invention discloses an artificial intelligence-based method for predicting drug interactions based on external entity association mapping, comprising the following components: (1) Extraction of intrinsic properties of drug molecules: The spatial geometry and atomic properties of molecules are processed using a Uni-Mol pre-trained model to obtain drug molecule characterization. (2) External entity association mapping: Projection blocks are constructed using a knowledge graph, and complex association patterns of external entities corresponding to drugs are captured through graph neural networks and global perception logic. (3) Deep fusion of multi-source heterogeneous information: Information is efficiently integrated using attention mechanisms and multilayer perceptrons to form the final fused characterization. (4) Prediction and decoding of interactions: The specific types of interactions are accurately decoded and predicted using a decoder architecture. (5) Interactive visualization and decision support: Visualization tools and AI decision support are provided to help researchers reduce trial-and-error costs and make scientific decisions.

The invention relates to the technical field of medical education and biological information visualization, in particular to a disease mechanism-associated protein structure and function visualization teaching virtual simulation system, which comprises a data storage module, a structure calling visualization module, a function-disease association module, an interactive operation module and a teaching evaluation module, all the modules interact through data interfaces. According to the protein structure and function visual teaching virtual simulation system associated with the disease mechanism, deep association of a protein three-dimensional structure, a function mechanism and a disease case is realized for the first time, the knowledge splitting barrier of traditional teaching is broken, and students are helped to construct a complete cognitive chain; autonomous operation and mutation simulation are supported, an abstract structure function relation is converted into an interactive visual model, the learning difficulty is remarkably reduced, and the knowledge absorption rate is increased; an experiment task and evaluation system is built in, a teaching closed loop of preview-operation-assessment-feedback is achieved, and the requirement for large-scale medical talent training is met.

This invention relates to the field of data visualization technology, and provides a method and system for visualizing operation and maintenance data based on smart grids. This method aims to improve the efficiency and intelligence of power grid operation and maintenance visualization, thereby enhancing the timeliness of power grid operation and maintenance decision-making and management. The method includes: real-time acquisition of multi-source heterogeneous operation and maintenance data sets from the smart grid; cross-modal cleaning and time alignment processing of the operation and maintenance data sets to generate a preprocessed data set; dynamic feature fusion and correlation analysis of the preprocessed data set to generate a set of equipment status features and a set of equipment-environment interaction features; generation of an interactive visualization element set based on the set of equipment status features and the set of equipment-environment interaction features through a multi-dimensional visualization strategy; dynamic rendering and layout optimization of the interactive visualization element set to output a real-time updated power grid operation and maintenance visualization interface; and configuration of a user operation priority response mechanism for handling interaction conflicts within the power grid operation and maintenance visualization interface.

Disclosed herein is a multimodal meal model configured to receive a variety of inputs associated with one or more meals, the inputs including image data, textual data, video data, and audio data. Inputs may be combined into a predefined prompt template that includes placeholders defined for certain types of inputs and includes instructions for how the output from the model should be structured. The meal visualization model is configured to generate dynamically annotated and interactive graphical user interfaces based on the inputs including interfaces that provide interactive graphical elements for manipulating meal components identified within the inputs. The model is also configured to provide personalized recommendations based on the inputs and user data, such as user glucose information and medical history. The interactive user interfaces may also be configured to display the personalized recommendations, which may also include interactive elements that enable manipulation of the recommendations by the user.

Systems and methods are described that enable dealers to manage their end user traffic in an own traffic environment on a distribution platform. The system includes a server configured to provide a single window user interface (SPoG UI) and a real-time data grid (RTDM) module for ingestion and standardization of data from multiple sources. An advanced analysis and machine learning (AAML) model analyzes the data to provide predictive analysis, anomaly detection, and personalized recommendations. The SPoG UI presents real-time data and insights through interactive visualization, enabling dealers to perform operations such as creating offers, issuing orders, and managing customer accounts. The system supports real-time pricing negotiation, compliance management, and integration with external systems via an API. The method and system generates an end-to-end real-time view of the provider's interaction with the end-customer.

The invention discloses an interactive rule arrangement system based on a graph structure, and relates to the technical field of rule engines, and the system comprises an interactive rule arrangement module which is used for creating each node in a to-be-executed flow chart and carrying out flow sorting and flow combination on each node in the to-be-executed flow chart; the graph rule engine module is used for obtaining a node and edge relationship in the graph rule file and analyzing to obtain a corresponding graph structure; and the interactive rule arrangement module is also used for carrying out process sorting and process combination on each node in the to-be-executed flow chart based on the graph structure in the graph rule file to form a constructed execution flow chart. According to the method, flexible arrangement of the rules is completed in an interactive visualization mode, the graph structure rule file is generated, operation is convenient, the learning cost is low, and the service rules have the global perspective advantage.

This invention discloses a method for evaluating and comparing comprehensive economic and social development indices, addressing the technical problems of inefficient data processing, rigid models, singular analysis, and static results in existing evaluation methods. The method sequentially completes five layers of operations: constructing and dynamically configuring a three-level evaluation indicator system to generate a configuration file containing comprehensive information; automatically collecting multi-source heterogeneous data and performing cleaning and standardization to generate a standard dataset; calculating and storing sub-domain indices and comprehensive development indices according to a bottom-up hierarchical aggregation logic; conducting longitudinal time-series comparisons, structural differentiation identification, and automated attribution analysis to generate a structured analysis report; and generating a multi-partition interactive visualization interface to achieve a step-by-step exploration of the index from macro to micro levels. This invention automates data processing, dynamically adapts the indicator system, completes in-depth index analysis and interactive display, improves the efficiency and practicality of evaluation, and provides precise decision-making support for the formulation of policies related to economic and social development.

The application discloses a marine buoy data artificial quality control method based on lasso interactive visualization, which comprises the following steps: 1) based on a data loading instruction, reading a target marine buoy observation data file and analyzing the same to construct an original data set; 2) constructing a visualization view containing two switchable interactive modes in a graphical user interface; 3) obtaining a lasso path made by a user through the visualization view and matching the same with data in the original data set to generate an index list of data points to be operated; 4) based on the index list, responding to a quality control instruction of the user to perform a persistent quality control operation on the data; 5) performing view rendering based on updated quality control data; and 6) repeating steps 3) to 5) until the marking of all data points is completed. The application integrates data dynamic visualization, graphical point selection editing, quality control logic real-time execution and effect instant feedback in a unified Web interface, realizes a "what you see is what you get" expert quality control closed loop and greatly improves the intuitiveness, accuracy and work efficiency of quality control work.

Disclosed systems and methods may receive real-time, external credit line information into one or more source applications. Thereafter, the real-time, external credit line information may be merged with internal credit line information and legacy information via a data orchestrator. The merged information may be further consolidated via the data orchestrator resulting in one or more micro batches of merged credit line information that are transmitted to a credit line decisioning system at frequent intervals. At least one exclusion rule may be applied to the transmitted credit line information, and thereafter, the transmitted credit line information may be provided to an interactive visual tool for real-time credit line management. The interactive interface allows for a user to incorporate real-time credit line information into credit line management decision-making. Thus, the credit line management system described herein provides real-time credit line information to enable real-time decision-making regarding credit line increase, decrease, and closure.

The invention discloses a hotel operation-oriented multi-dimensional data visualization report automatic generation method and system, and belongs to the technical field of hotel informatization management. The method comprises the following steps: packaging multi-source heterogeneous data inside and outside a hotel into a standard event stream in real time through a differential acquisition strategy; performing cleaning and semantic mapping based on domain ontology on the event stream, and constructing a dynamic knowledge graph and a data warehouse; carrying out monitoring, prediction and root cause analysis through a hierarchical analysis engine based on the mixed data assets, and generating a structured insight; dynamically binding the insight with a preset template through a template engine, and automatically synthesizing an interactive visual report in combination with a digital twin view; finally, safe distribution, real-time updating and feedback optimization closed loop based on authority are achieved. According to the invention, end-to-end automation from multi-source data to intelligent decision making is realized, the problems of data isolated island, analysis surface and report staticization in the prior art are solved, and the depth and timeliness of hotel operation analysis are remarkably improved.

The invention discloses a forest park ecological environment dynamic monitoring and management system based on an unmanned aerial vehicle, and belongs to the technical field of environment monitoring. Comprising an intelligent unmanned aerial vehicle cluster for realizing efficient and continuous monitoring of a wide area of a forest park; the multi-source data acquisition module comprehensively captures visual, structural and environmental information of the forest park; the data preprocessing and fusion module is used for accurately aligning, purifying and integrating the acquired data; the multi-scale ecological change analysis module is used for deeply analyzing change characteristics of the forest ecological system on different spatial scales; the ecological system health assessment module comprehensively assesses the ecological health condition of the forest park and judges the health condition of the forest park; the change prediction and early warning module is used for predicting the future change trend of the forest park ecosystem and carrying out early warning on potential risks; and the decision support and visualization module is used for displaying an analysis result through an interactive 3D visualization platform and generating a management suggestion based on data analysis.

Aspects of the present disclosure are directed to a system having at least one processor and memory instructions executable by the at least one processor to maintain a data store that associates subscribers with subscription tiers and stores a permission policy defining allowed subscriber interactions with media items supplied by creators. The instructions further cause the system to receive, from a client device of a premium tier subscriber, a request relating to a referenced media item. The instructions further cause the system to determine, from the permission policy, at least one content-interaction mode permitted for the subscriber with respect to the referenced media item. The instructions further cause the system to generate, by an AI model selected based on the content-interaction mode and permission policy, modified content, supplemental content, or generative content. The system may generate interactive visualizations that respond to one or more aspects of the referenced media item.