2414 results about "Visulation" patented technology

A computer-implemented method for evaluating integration of Responsible Artificial Intelligence Operations (RAIOPS) and Large Language Model Operations (LLMOPS) is disclosed. A response respective to each of prompts is generated using an LLM, in response to receiving data associated with each of the prompts. The data associated with each of the prompts and data associated with the response respective to each of the prompts is stored as an association. Further, based on user-specified criteria and using the data associated with the prompts or the data associated with the responses respective to the prompts, one or more evaluation metrics are generated for evaluating the responses respective to each of the prompts for one or more aspects. In accordance with the at least one evaluation metric, a knowledge graph visualization or a numerical score is generated to display performance of the LLM and determine whether the LLM needs optimization or tuning.

The invention discloses an engineering project full-cycle cost intelligent accounting system based on a BIM technology, and relates to the technical field of constructional engineering informatization, and the system comprises a BIM visualization platform which is in communication connection with the following modules: a dynamic optimization scheduling module which is used for fusing a target engineering project BIM model and a real-time digital twinborn body, and introducing a bat algorithm to carry out dynamic optimization on construction resource nodes influenced by risks. According to the method, a dynamic resource topology network is constructed by fusing a BIM model and real-time digital twinborn data, accurate tracking and state perception of construction resources are realized, on the basis, a bat algorithm and a graph neural network are introduced to perform dynamic optimization and conflict coordination on resource configuration in a multi-risk concurrent scene, and the resource allocation efficiency is improved. And a rescheduling scheme and an optimal cost increment which conform to actual engineering logic are generated, the limitation of traditional static risk conduction simulation is broken through, and the adaptability of resource scheduling and the refinement level of cost control are remarkably improved.

The invention provides a digital twin three-dimensional model construction method based on a generative large model, and the method comprises the steps: obtaining multi-source monitoring data of a power distribution network, and processing the multi-source monitoring data into a training data set; the method comprises the following steps: mapping multi-source monitoring data into a multi-scale tensor subspace through tensor wavelet structured transformation, adaptively extracting spatial features through a learnable wavelet kernel, and keeping the structural continuity of a physical field in combination with a geometric prior regular term; constructing and training a generative adversarial network through a training data set; inputting and analyzing the physical parameter vector of the target scene, and if the topological similarity score is lower than a preset threshold value, adjusting noise vector regeneration; and if yes, outputting a three-dimensional model tensor and importing the three-dimensional model tensor into a digital twin platform, and driving real-time physical field visualization. According to the method, characteristics of a multi-scale space structure and a nonlinear physical field can be reserved, the physical rationality and generalization ability of the generated model are remarkably improved, and depth identification of topological attributes (such as hole connectivity and surface defects) and local geometric defects of the three-dimensional model is realized.

The invention provides a low-code application logic generation method and system based on a large language model, and the method comprises the steps: obtaining a natural language demand and an operation environment snapshot of a user, and constructing a prompt project context of the large language model based on the natural language demand and the operation environment snapshot; based on the context of the prompt project, performing retrieval by utilizing a large language model to obtain a logic component; processing the logic component based on a pre-constructed agent to generate a logic DSL text; analyzing and rendering the logic DSL text to obtain a visual logic flow graph, and updating the logic DSL text in response to a modification operation of a user on the visual logic flow graph; based on the logic DSL text, verifying application logic corresponding to the logic DSL text in the sandbox environment, and deploying the application logic to the current application after verification is passed. According to the invention, complex business requirements can be met, and logic development thresholds are reduced.

A database query processing method includes receiving a natural language request for information contained within a database from a user in an application session, prompting a large language model to generate a SQL request, and receiving a particular SQL request from the large language model that is parsed to identify a command to access one or more database structures. A security predicate is appended to the command, creating a modified SQL request, to enforce one or more database access constraints constraining a user-authenticated client device that submitted the request that is not enforced in a database session between the application and a database. The modified SQL request is used to access data in the database session, and a visualization of the accessed data is caused to be displayed in the application session.

The invention relates to an OpenGL (Open Graphics Library)-based large-scale three-dimensional model object quick pickup method. The method comprises the following steps: converting an interactive operation of a user into a three-dimensional space structure; a CPU constructs octree space acceleration structures based on a bounding box of an object in a large-scale three-dimensional model, and leaf nodes, intersecting with a pickup ray or a pickup view pyramid, of an axis alignment bounding box in each octree space acceleration structure are screened out to serve as candidate leaf nodes; collecting triangles contained in all candidate leaf nodes, and constructing a candidate triangle set; dynamically allocating thread groups and threads of the GPU based on the number of candidate triangles in the candidate triangle set; and performing highlight display on the candidate triangles intersected with the pickup ray or the pickup view cone, and feeding back IDs of the corresponding candidate triangles. According to the method, the data transmission quantity and the video memory access pressure are remarkably reduced, the pickup response time is greatly shortened in a large-scale three-dimensional model scene, and the requirements of real-time interaction and visual operation can be met.

The invention provides a land unmanned equipment semantic preserving large model deployment method and system, and relates to the technical field of navigation control. According to the deployment method, a preliminary control suggestion is directly output through a lightweight fusion model, optimization fusion is carried out through an MPC framework, underlying dynamics and environmental constraints, and seamless connection from semantics to control is achieved; in combination with a VILO odometer and instance segmentation, a global map containing dynamic obstacle semantic information is constructed and updated in real time, and an accurate context is provided for planning and decision making; model pruning, knowledge distillation and edge calculation scheduling are adopted, so that a complex multi-modal semantic model can run in real time on an embedded platform; the decision basis from instruction analysis to control execution is recorded and visualized in the whole process, and the transparency and credibility of the system are improved; on-line re-planning, multi-stage fault detection and switching strategies are integrated, and the robustness of the system in a dynamic environment and an abnormal condition is remarkably improved.

The invention relates to the technical field of multi-modal large language model training, in particular to a prompt construction method and system for a multi-modal large language model, computer equipment and a medium. The method comprises the following steps: extracting a key frame set from an input video stream; executing a motion reconstruction process on the video stream to generate motion track information; and performing visualization processing on the motion track information to generate a track visualization graph. Performing space-time correlation coding on the key frame set and the motion track information to generate an enhanced key frame; a multi-modal prompt is constructed in a mode of integrating visual input and text input, and the multi-modal prompt is input into a preset multi-modal large language model for spatial reasoning. Through the mode, the technical problem that an existing prompting method is difficult to give consideration to the spatial reasoning precision and the calculation efficiency is solved, efficient and accurate spatial reasoning of the multi-modal large language model is achieved, and the calculation efficiency, the reasoning precision and the environmental adaptability of the model are improved.

The invention discloses a knowledge document-oriented method for structurally and stably presenting large language model output. The method comprises the following steps of: preprocessing a knowledge document and converting the knowledge document into a text by a system; the back-end service module adopts a prompt word engineering technology based on a preset JSON mode, constructs a structured prompt containing clear instructions and output format constraints, calls a large language model to carry out analysis and information extraction on text contents, and forces the model to generate structured JSON data following the preset mode; the back-end service provides access to the structured JSON data for the front-end application; and the front end executes templated mapping rendering according to a preset user interface component template isomorphic to the JSON mode, and fills the content of each field of the JSON into a corresponding visual component. According to the method, through the cooperation of the back-end constraint prompt word engineering and the front-end modularized template rendering, the defects that the output content format of a large language model is unstable and is difficult to be directly applied to standardized interface presentation are relieved.

The invention discloses a dynamic data docking method based on a rule engine, which comprises the following steps: S1, data source registration and automatic detection: a user inputs various heterogeneous data source information through a system console, and a system automatically detects the data source type, the data structure and the connection availability and generates an adaptive connection configuration file; according to the method, a dynamic data docking method with the rule engine supporting hot updating as the core is introduced, seamless integration and flexible conversion of multi-source heterogeneous data are achieved, and the problem of business interruption caused by code modification and service restarting due to rule change in a traditional scheme is thoroughly solved; through visual rule management, a unified data model and a closed-loop verification feedback mechanism, the development and maintenance cost of the system is remarkably reduced, and meanwhile, the flexibility, reliability and traceability of data processing and the continuous self-adaptive optimization capability of the system are greatly improved.

Data from manufacturing is highly uncontextualized and siloed, requiring expert knowledge of context and substantial data pre-processing to support meaningful queries and visualizations. To address this problem, data for a number of sources in a manufacturing context can be retrieved and converted into an intermediate representation in a natural language or near-natural language form, which can in turn be ingested by a generative AI engine, along with suitable prompts by the user to summarize, analyze, and make recommendations based on the data.

The invention discloses an engineering vehicle safety simulation and prediction system based on digital twinning, and the system comprises a data collection layer which collects multi-source heterogeneous data in real time; in the knowledge graph layer, a streaming inference engine is constructed based on an Apache Jena graph database, and an entity-relationship-attribute triple dynamic graph structure is adopted; according to the AI model layer, a physical rule serves as a loss function constraint term to be embedded into a neural network through a physical information neural network, a digital organ model concept is combined to split a vehicle into key organs for heterogeneous modeling, a simplified physical model is adopted in the core physical process, and an LSTM-AI model is adopted in external behaviors; the explanatory analysis layer is used for integrating an SHAP / LIME explanatory tool to output a visual evidence chain during fault prediction, and deploying an online incremental learning framework to allow the model to learn from new data and dynamically adjust normal range definition; and the visualization and application layer is used for performing three-dimensional visualization rendering based on WebGL or Three.js, and ensuring data transmission security through block chain evidence storage and end-to-end encryption.

Data platforms described herein are configured to monitor a compute environment and provide a user interface. Such a data platform may direct an application to process, on a user interface computing thread, user input to a graphical user interface view that is rendered based on data received from a data platform, to detect, on the user interface computing thread, a set of instructions associated with a visualization of a logical graph, to determine that the set of instructions satisfies one or more criteria, to execute, based on the set of instructions satisfying the one or more criteria, the set of instructions on a set of additional computing threads, and to render the visualization of the logical graph in the graphical user interface view based on the processing of the user input and the executing of the set of instructions. Corresponding methods, systems, and products are also disclosed.

The invention discloses an industrial software cloud base intelligent operation and maintenance and fault self-healing method based on digital twinning, and relates to the technical field of digital twinning. According to the method, the hierarchical digital twinborn model is constructed and dynamically updated, and the operation state of the cloud base is accurately mapped and visually displayed in combination with independent visual modules of a physical layer, a logic layer and an application layer; the method comprises the following steps: calibrating a reference value in real time through a dynamic reference library, quickly identifying abnormity of each layer, generating graded early warning, improving abnormity response timeliness, constructing a dynamically updated fault knowledge graph based on historical fault data, integrating a multi-dimensional correlation analysis and confidence coefficient verification mechanism, positioning a unique fault reason, greatly shortening a fault diagnosis period, and improving fault diagnosis efficiency. And a strategy library is constructed based on a fault knowledge graph and historical self-healing cases, simulation verification is carried out on candidate strategies through a digital twin model, the effectiveness of the self-healing strategies is ensured, and then the self-healing strategies are issued and executed, so that intelligent and automatic fault repair is realized, and stable operation of the cloud base is ensured.

The invention relates to the field of computer software, and provides an AI-based low-code visual component dynamic generation method and system. The method comprises the following steps: receiving a component demand description input by a user, and converting the component demand description into structured cue word data to obtain an initial cue word sequence; retrieving matched template data and grammatical rule data from a component knowledge base according to the initial cue word sequence, and fusing the template data, the grammatical rule data and the initial cue word sequence to obtain an enhanced cue word sequence; performing semantic analysis and code generation processing on the enhanced cue word sequence through a large language model to obtain a component source code; and performing real-time rendering processing on the component source code through a component rendering engine, and generating an interactive component instance in a preview interface to obtain reusable component resources. According to the method, the code quality consistency is ensured, and the development efficiency is improved.

The invention discloses a crack width measurement method and system based on dynamic topological structure analysis. A system hardware basis comprises an image acquisition module, an image processing unit, a data storage module and a result display module. According to the method, the working process of an image processing unit is divided into two stages according to a time sequence: the first stage is used for realizing data processing and crack segmentation, and the second stage is used for completing dynamic topology analysis and width measurement of cracks. In the second stage, the steps of form closed operation, skeleton extraction and enhancement, end point bridging, topological statistics and segment width measurement are executed in sequence, and finally a visual result and quantized data are output. The method comprises the following steps: processing an initial skeleton image by adopting an independently researched and developed topology enhancement algorithm; the method is especially good at processing complex net-shaped cracks, and the defect that measurement is inaccurate at crossed and bent cracks in a traditional method is effectively overcome through a dynamic topology analysis method.

A processing system including at least one processor may obtain a natural language request for a network topology visualization associated with a communication network. The processing system may next generate a prompt based upon the natural language request in accordance with a prompt mapping function, apply the prompt as an input to a generative model to generate a query, and apply the query to a communication network database system to obtain a query result. The processing system may generate the network topology visualization from the query result. The processing system may then present the network topology visualization via at least one display device.

The invention relates to the technical field of streaming computing, and provides a real-time service computing system based on a dynamic rule engine, which comprises a rule management module and a streaming computing engine, the rule management module is used for providing visual configuration and release functions of service rules and performing versioning storage on the released service rules; the streaming computation engine comprises a rule synchronization unit and a plurality of parallel processing units; the rule synchronization unit is used for acquiring service rules from the rule management module and distributing the acquired service rules to each parallel processing unit based on a broadcast mechanism; and each parallel processing unit is used for receiving the business event flow and performing real-time rule matching on the business event flow according to the received business rule so as to output a decision result. According to the system, complete decoupling of business rule configuration and execution is realized, and the problem that rule updating in a traditional business system needs shutdown deployment is effectively solved.

The invention relates to an engineering construction stage user multi-dimensional demand analysis system and method, and the system comprises a multi-modal semantic model construction module which integrates a multi-source knowledge base, and extracts triple description statements from the provisions of the multi-source knowledge base to construct an engineering object ontology knowledge graph; the demand structured guidance and intelligent analysis engine module dynamically identifies an engineering stage and a user role, guides a user to perform text demand input, and performs semantic completion and standardization processing; the demand conflict detection and coordination correction module is used for detecting conflicts in user demands and generating a conflict influence analysis report and a coordination processing scheme; the intelligent drawing and dynamic optimization module is used for automatically drawing according to the triple obtained through demand analysis; and the demand analysis visualization and flow closed-loop module is used for generating an executable parameterized demand document and an association chart, and completing demand-design-verification engineering closed-loop management, so that intelligent analysis and standardization of user multi-dimensional demands are realized, and the system has the advantages of high efficiency, accuracy and intelligence.

The invention discloses a dynamic digital twinning three-dimensional Gaussian splash rendering system and a dynamic digital twinning three-dimensional Gaussian splash rendering method. According to the system, a static scene is reconstructed by utilizing a three-dimensional Gaussian splashing technology through a semantic scene reconstruction module, semantic information is associated to Gaussian primitives in combination with spatial alignment and semantic injection, and a model with a semantic identifier is generated; multi-source dynamic data are fused and converted into a dynamic data field which can be accessed by a GPU through a multi-mode spatio-temporal data processing module; and through a rendering attribute dynamic modulation module, screening a target primitive according to the semantic identifier, and directly modulating internal rendering attributes such as color, transparency or shape of the target primitive based on a data field query value, thereby realizing internal rendering and visualization of dynamic data. According to the method, the problems that in the prior art, rendering reality and real-time performance are difficult to give consideration to and data and scene fusion is superficial are solved, and dynamic digital twinning rendering with high reality and strong immersion is realized.

The invention relates to the technical field of plasma numerical simulation, in particular to a data processing system suitable for a two-dimensional boundary plasma fluid calculation program SOLPS. According to the technical scheme, the system comprises a simulation calculation convergence state analysis module, an experiment and simulation comparison module and a simulation result processing module. According to the method, one-key data processing is realized through an automatic script and a graphical interface, and the limitation of a specific computing environment is broken through; the system can quantitatively analyze the simulation convergence state, provides a direct comparison function of experiment and simulation data, and provides a reliable basis for transport coefficient calibration. Meanwhile, flexible customization of various visualization forms is supported, the problems that a traditional method is tedious in operation, low in efficiency and insufficient in flexibility are effectively solved, and the efficiency, accuracy and reliability of data processing are comprehensively improved.

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 belongs to the technical field of code-free development, and particularly relates to a Web3D zero-code interactive design platform and method based on a unified model, and the platform comprises a unified business logic model UBLM and a platform-independent, self-described and structured data container which is used for completely defining all behavior logics in 3D interactive application, including events, conditions, actions, parameters, variables and flow relations; the dual-mode editor comprises a form-type editor and a blueprint-type editor, and the form-type editor and the blueprint-type editor can be used for completely creating, editing and visualizing the same UBLM and realizing real-time state synchronization; and the interpreted rule execution engine IREE is a lightweight engine running in a JavaScript environment of a browser and is responsible for analyzing the UBLM during running and converting the declarative logic into an executable instruction in a 3D scene through a rule matching and function registration mechanism. According to the invention, the development and cooperation efficiency can be improved, and the iterative maintenance process is simplified.

The invention discloses a multi-field coupling concrete dam parameter intelligent inversion method, system and device based on deep learning and a medium, and belongs to the technical field of dam engineering safety monitoring and computational mechanics crossing. The geometry and boundary modeling unit is used for uniformly expressing a dam body-dam foundation geometric region and a boundary type; simultaneously representing a state field and a parameter field by utilizing PINN inversion, calculating a physical residual error, and implementing parameter physical feasibility constraint and prior regularization; the organization optimizer, residual drive sampling and weight self-adaption are used for training scheduling, and result review, visualization and data export are carried out through the verification and output unit. According to the method, end-to-end parameter field inversion is realized on the premise of not depending on frequent mesh generation, the calculation cost of multiple forward modeling is reduced, the non-uniqueness of inversion is inhibited, and the method has higher recognition capability for engineering concerned areas such as permeation channels and degraded zones.

The invention provides a visual form construction method, which comprises the following steps: receiving user form operation data, carrying out business logic calculation, state change control and inter-service coordination operation on the user form operation data based on domain-driven design, and generating domain events, state data and service governance data. Domain events and state data are recorded to an event storage system, a query optimization view is constructed, event logs and query view data are generated, and dual optimization of data persistence and query efficiency is ensured. According to a preset security policy rule, real-time security monitoring is performed on the service governance data, a system health state index and security audit data are generated, and a system-level observability and security protection mechanism is established. And performing interface rendering and synthesis based on the event log, the query view data, the system health state index and the security audit data to generate a user interactive form interface. Through fusion processing of multi-source data, deep integration of interface rendering and security policies is realized.

A system is provided.SOLUTION: A system, comprising: means for collecting applicant paperwork; means for analyzing the collected paperwork and utilizing a generative AI model to evaluate the applicant's skills, experience, and educational background; means for generating and displaying evaluation results in the form of a visual report; means for utilizing the generated evaluation results to generate a set of interview questions; and means for integrating the paperwork examination and interview results, performing a final evaluation, and recommending informal candidates.SELECTED DRAWING: Figure 1

The invention relates to the technical field of digital twinning, in particular to a high-performance digital twinning system rendering method based on dual-grid and neural network mapping, and the method comprises the steps: constructing a high-precision calculation grid and a low-precision rendering grid, and building a space mapping relation between the two grids; executing multi-working-condition numerical simulation to obtain a high-dimensional simulation result snapshot matrix; the dimension reduction projection operator is used for reducing the dimension of a high-dimensional simulation result of any working condition into an r-dimensional feature vector; generating low-dimensional reference field data by using the space mapping relation; training the neural network until a mapping network parameter is obtained through convergence; obtaining current working condition parameters of the equipment in real time, and obtaining a current r-dimensional feature vector by using the dimensionality reduction projection operator; and quickly generating physical field prediction distribution on the low-precision rendering grid and performing pseudo-color rendering. According to the scheme, the problem that a traditional method is low in rendering efficiency is solved, and the method has the advantages of reducing computing resource consumption and keeping visualization precision.

The embodiment of the invention provides a modeling method and device for an airborne system function architecture model, computer equipment and a medium, and relates to the technical field of aviation architecture design, the method comprises the following steps: inputting a design requirement document into an airborne large language model, and in the large language model, under the structural constraint of an airborne system knowledge graph, establishing a design requirement document; the method comprises the following steps: extracting a logical relationship between entities required by airborne system modeling from a design demand document, screening a corresponding airborne meta-model according to the extracted logical relationship between the entities, and constructing a demand graph; constructing and outputting a text model of a concept scene, a text model of a task scene, a text model of a system function, a text model of a logic architecture and a text model of a physical architecture of the airborne system based on the demand graph; and inputting each text model into a system modeling language modeling terminal for visualization to obtain a multi-level functional architecture model of the airborne system. According to the scheme, the modeling efficiency, consistency and normalization are improved.

The invention discloses a cascade reservoir scheduling method and system based on an artificial bee colony algorithm, and the method comprises the following steps: the system collects multi-source hydrological data in real time through a hydrological perception and preprocessing module, and introduces a large language model to carry out the semantic judgment and anomaly labeling of an abnormal hydrological time sequence; inputting the processed high-quality data into a reservoir model construction module, establishing a cascade reservoir optimal scheduling system, and setting corresponding boundary conditions and operation constraints in combination with reservoir scheduling regulations; the scheduling optimization module receives model input, adopts a variable structure taking a water level as a core to construct an optimization individual, and completes population initialization, disturbance generation and fitness evaluation based on a potential solution guide mechanism in an improved artificial bee colony algorithm; the system transmits the scheduling sequence optimized and output by the scheduling optimization module into an LLM intelligent auxiliary module; and the intelligent text interpretation generated by the LLM and the scheduling optimization solution enter a result evaluation and visualization module together. According to the scheduling method and system, a high-quality and physically feasible scheduling scheme can be output within reasonable calculation time.

The invention relates to the technical field of computers, and discloses an application development method based on a large model technology, and the method comprises the steps: 1, carrying out the demand analysis, and converting a fuzzy business description into an executable technical scheme through natural language understanding and a structured modeling technology; 2, carrying out architecture design and planning, and constructing a code-free and low-code dual-mode collaborative architecture; 3, establishing a visual arrangement engine, and establishing a dual-mode development interface of a code-free development mode and a low-code development mode; step 4, aiming at different requirements of a code-free scene and a low-code scene, a dynamic adaptation strategy is adopted, and differentiated resource management of lightweight adaptation and elastic expansion is carried out; and step 5, performing field adaptation, and obtaining the industry exclusive capability according to the general model and the field knowledge through code-free rapid adaptation and low-code deep customization. By means of the scheme, the development threshold can be lowered, the efficiency can be improved, and the accuracy of cross-industry application is improved.