118 results about "Visual modeling" patented technology

The invention relates to the technical field of building information modeling, in particular to a building drawing geometric feature extraction and visual modeling method and system, and the method comprises the steps: carrying out the self-adaptive noise reduction, contrast enhancement and line refinement processing of an original building drawing image, and carrying out the automatic layer separation based on colors and line types; linear geometric features and specific symbol geometric features in the drawing image are extracted, and a geometric feature set is constructed; component instantiation, attribute assignment and topological relation reasoning are carried out by using a predefined building component semantic rule base, and a building component semantic network is generated; and mapping the semantic network to a parameterized three-dimensional modeling engine, calling an IFC standard three-dimensional template, performing parameter driving and automatic assembly, generating a three-dimensional building model with semantic information and a spatial structure, and performing visual output. According to the method, efficient and standardized conversion from a two-dimensional building drawing to a three-dimensional building model can be realized, and the method has the remarkable advantages of processing complex drawings and high-precision modeling.

The invention relates to the technical field of digital twinning, in particular to a storage space utilization rate optimization method and system based on digital twinning, and the method comprises the steps: determining three-dimensional visual modeling input data of a storage digital twinning body according to an obtained environment data set of a storage space and an operation state data set of storage equipment; performing feature extraction processing on the three-dimensional visual modeling input data to generate a storage feature set, and generating a three-dimensional visual model of the storage digital twin based on the storage feature set; calling a spatial layout simulation analysis algorithm, performing joint simulation processing on shelf distribution characteristics, equipment moving path characteristics and goods access frequency characteristics in the three-dimensional visual model, and generating a spatial layout simulation result set; and generating a warehousing operation adjustment strategy set according to the path conflict simulation result and the space idle simulation result in the space layout simulation result set, and indicating a warehousing control system to perform space layout optimization processing based on the warehousing operation adjustment strategy set.

The invention discloses a small sample industrial defect image segmentation method and system based on text background perception enhancement, and a storage medium. The method comprises the following steps: constructing a corresponding support-query pair according to an industrial defect image set; establishing a text background perception enhancement model; utilizing all support-query to train a text background perception enhancement model; and inputting a query image to be segmented, the corresponding support image and the mask label into the trained text background perception enhancement model, and obtaining an output result of the few-sample segmentation model as a segmentation prediction result of the corresponding query image. Through fusion of a multi-modal language-visual modeling mechanism and a joint activation graph optimization strategy, the precision and efficiency of defect detection are greatly improved, small-sample and low-cost detection is realized, and the generalization ability is high.

The invention relates to the technical field of visual lane modeling, and discloses a business data processing method and system based on visual lane modeling, and a multi-task prediction model based on multi-source historical business chain data training graph neural network and Transform fusion. A plurality of groups of lane layout and event configuration schemes are generated in combination with user real-time operation captured by a design interface, an optimal scheme is screened through simulation evaluation and then is visually displayed, finally, visual lane modeling is executed according to user feedback, and through automatic data processing, high-precision model prediction, real-time interaction optimization and visual modeling, the optimal lane layout and event configuration scheme is obtained. According to the method, the service chain design efficiency and quality are improved, meanwhile, artificial experience deviation is avoided through model prediction based on historical data, the comprehensive requirements of complex equipment development for real-time performance, reliability and resource efficiency are met, and efficient technical support is provided for landing of model-based system engineering in the field of complex equipment.

The invention relates to the technical field of network geographic information systems, and discloses a visual modeling method, system and device for a spatial analysis process and a medium. The method comprises the following steps: constructing a visual component library; in response to a canvas interaction instruction input by a user, performing parameter configuration and component connection based on the visual component library to obtain workflow logic of the canvas; analyzing the workflow logic in real time based on a directed acyclic graph to generate a spatial analysis code and obtain an analysis result of the spatial analysis code; and performing result visualization and export on the analysis result based on the visual component library. According to the method, component dragging, parameter configuration and connection mechanisms suitable for WebGIS spatial analysis are defined, and visual workflow construction is achieved. Based on a directed acyclic graph process analysis algorithm, efficient and executable spatial analysis codes are automatically generated, and dynamic optimization and parallel computing are supported, so that visual modeling and automatic execution of a spatial analysis process are realized.

The invention discloses a Java enterprise-level rapid development method based on visual modeling. The method comprises the steps that modeling behaviors are collected to generate a cognitive map, a view is constructed, and operation behaviors are collected to generate cognitive feature data; generating a semantic constraint model, and fusing the cognitive features and the node features to construct the semantic constraint model; semantic consistency detection is executed, design and implementation differences are automatically compared, and bidirectional correction is triggered; generating a project engineering structure, and generating a structured code and an interface document according to the correction model; zero-shutdown migration evolution is executed, a migration relation graph is constructed, and seamless switching is carried out in a gray level mode; and performing semantic self-correction updating in the operation period, monitoring semantic offset and backfilling design content for closed-loop synchronization. According to the method, intelligent modeling and uninterrupted evolution of Java enterprise-level applications are realized through cognitive map driving and a multi-mode migration mechanism.

The invention provides an intelligent detection and visual representation system for solid engine grain defects. The system comprises a two-dimensional slice data preprocessing module, a three-dimensional visual modeling module and a model post-processing and analysis module. According to the system, by fusing a multi-modal image processing algorithm and a three-dimensional modeling technology, sub-voxel-level three-dimensional reconstruction and spatial quantitative analysis of defects such as air holes and cracks are realized, and coordinate distribution, geometric dimensions and quantity statistics of the defects in a grain three-dimensional space can be accurately positioned; the technical bottleneck of a traditional two-dimensional detection method in the aspects of defect deep analysis and multi-parameter coupling analysis can be solved. All the core modules cooperate to improve the accuracy and efficiency of detecting the defects of the air holes in the solid engine, accurately detect the spatial positions and shapes of the air holes in the grain, and ensure the integrity and safety of the SRM grain structure.

The invention provides a visual modeling method for a ship pipe network program based on a YOLOv8 target detection technology, and the method comprises the following steps: S1, constructing a human-computer interaction visual interface of a ship pipe network system in the form of an SVG base map and a control position map through employing a WPF interface generation technology; s2, identifying the pipe network elements in the human-computer interaction visual interface by using a YOLOv8 target detection technology, and obtaining an identification result; s3, using a Python optimization algorithm to carry out classification arrangement and model recombination on identification results, generating an architecture model containing pipe network elements and control spatial positions and attribute parameters by a system, and storing the architecture model in a standard CSV file form; and S4, converting the architecture model stored in the CSV file into a mathematical model by using a C # programming language, performing real-time calculation, and outputting a calculation result to a human-computer interaction visual interface. According to the invention, the integrated operation of the ship pipe network system from design to simulation is realized, the design efficiency is obviously improved, and the operation is more convenient.

The invention provides a mineralization domain spatial distribution prediction method and system based on geological priori knowledge, and relates to the technical field of mineral exploration, and the method comprises the steps: obtaining drilling core test analysis data and magnetic measurement data of a target mining area; processing the geochemical data to obtain an element concentration data set, and performing potential field conversion on the magnetic measurement data to generate a magnetization direction data set; identifying geochemical anomaly information from the concentration data set by using a fractal algorithm, determining an anomaly range, fusing the anomaly range and the magnetization direction data set, performing three-dimensional visual modeling, and constructing a three-dimensional geologic model; and finally, extracting feature data in the three-dimensional geologic model, and inputting the feature data into a machine learning prediction model for processing to obtain a distribution diagram representing the existence probability of the mineralization domain in the mining area space. According to the invention, the accuracy of blind mineralization domain spatial position prediction is improved.

The invention discloses a method for automatically processing a business process embedded with a man-machine interaction node, and relates to the technical field of business process processing. Modeling is carried out according to BPMN2.0, node logic and data formats are defined, visual modeling is carried out through a tool, and version control is carried out; identifying a manual intervention scene, embedding an interaction node, configuring a multi-trigger condition, and adapting to multiple terminals and an interaction template; deploying a process engine, configuring parameters and mapping a system interface; the task is pushed when the interaction node is triggered, and the engine drives the process after user operation; abnormal and operation logs are recorded, stored and analyzed; and generating an execution report, regularly analyzing the bottleneck, and optimizing the process and parameters. According to the method, the man-machine interaction node is flexibly embedded, and the process execution flexibility and stability are improved; priority and response time efficiency are optimized, and risk management and control are enhanced; authority is refined, data are integrated, the operation and maintenance and iteration efficiency is improved, and the multi-service scene requirement is met.

The invention discloses a SysML-based satellite constellation architecture modeling method and system and a storage medium, and the method comprises the steps: analyzing a satellite constellation system strategy scene and a target described by a natural language, and building a satellite constellation architecture system layer model by using a SysML language; based on a system capability demand model in the constructed system layer model, building the system layer model by combining an RFLP (Restriction Fragment Length Polymorphism) method and a SysML (Systematic Modeling Language); analyzing designed functions in the constructed system layer model through a system forward design method, and respectively establishing a satellite platform model and a satellite load model by using an RFLP (Restriction Fragment Length Polymorphism) method and an SysML (SysML) modeling language; and extracting parameters from the constructed satellite parameter model, platform parameter model and load parameter model to carry out orbit design, and establishing a satellite orbit model by using an SysML language. According to the method, comprehensive and visual modeling of the satellite constellation from a macroscopic system to a microcosmic component is realized, the standardization, consistency and understandability of the model are greatly improved, and the modeling efficiency is improved.

The invention provides a salt lake resource dynamic monitoring system based on a Kriging interpolation method. Comprising a drilling deployment module, a resource reserve initial exploration module, a multi-source data acquisition and preprocessing module, a spatial interpolation algorithm module and a three-dimensional visual modeling and rendering module. According to the method, the Kriging interpolation method and the Co-Kriging interpolation method are combined, the main and auxiliary variable spatial correlation is utilized to improve the reserve estimation accuracy, the limitation of dependence on a large number of samples traditionally is broken through, center encryption and peripheral control drill hole arrangement is combined with uncertainty evaluation to optimize the exploration cost, comprehensive evaluation is supported by a small number of samples, the model is dynamically updated by the system monthly, and the exploration efficiency is improved. The problem of traditional data lag is solved, the resource dynamic state is visually presented through the three-dimensional visual modeling and rendering module, a basis is provided for decision making, the resource utilization rate is improved, and premature exhaustion is avoided.

The present application relates to the technical field of three-dimensional geological visualization modeling, and discloses a mine geological structure intelligent analysis method and system based on three-dimensional visualization modeling, which comprises the following steps: acquiring continuous drilling process parameters along a drill hole, establishing a parameter fingerprint library to identify the causes of parameter changes, identifying effective physical beacon points capable of representing real geological discontinuity, and then generating a geological reality guide field in three-dimensional space using the beacon points as a source, and imposing constraints on the weight across potential geological boundaries when performing spatial interpolation. The present application converts long-neglected drilling process data into effective geometric constraints for the three-dimensional modeling kernel, changes the model construction from pure mathematical filling to a form closer to the engineering reality guided by the physical process, and ensures the reliability of the constraint source through an internal anti-fake mechanism, thereby improving the structural reality of the final geological model.

The application relates to the technical field of visual lane modeling, and discloses a business data processing method and system based on visual lane modeling, wherein a multi-task prediction model of a graph neural network and a Transformer fusion is trained based on multi-source historical business chain data, a plurality of groups of lane layout and event configuration schemes are generated in combination with real-time operations of a user captured by a design interface, the optimal scheme is selected through simulation evaluation and filtering, and visual display is performed, and finally, visual lane modeling is executed according to user feedback, through automatic data processing, high-precision model prediction, real-time interactive optimization and visual modeling, the design efficiency and quality of a business chain are improved, meanwhile, model prediction based on historical data avoids artificial experience deviation, meets the comprehensive requirements of real-time performance, reliability and resource efficiency for complex equipment development, and provides efficient technical support for the landing of model-based system engineering in the field of complex equipment.

This invention provides an automatic modeling method and system for low-voltage power grid data based on visual data acquisition, relating to the field of low-voltage power grid technology. The method includes: dividing the low-voltage power grid area into multiple sub-regions and constructing multiple local coordinate systems; analyzing the power grid equipment to be acquired and determining at least one matching local coordinate system; configuring a visual data acquisition task template, performing data acquisition to obtain at least one set of equipment modeling data; constructing a multi-region coordinate system transformation model, performing coordinate system transformation to obtain at least one set of equipment modeling transformation data corresponding to the equipment modeling data, and generating visual modeling simulation results for the data acquisition task. This invention solves the technical problem in existing technologies where, in the process of low-voltage power grid data modeling, a large, unified global modeling coordinate system is typically established for data acquisition or modeling of all power grid equipment. While this achieves a unified effect, it is not accurate enough, affecting the true reflection of power grid data and its application effectiveness.

The application discloses a facies intertidal zone sessile organism investigation method based on visual modeling, first, the low tide period of spring tide day is determined in combination with the data of the tidal station, the orthographic image and three-dimensional model of the investigation area are acquired by using the RTK unmanned aerial vehicle, the accurate investigation range is demarcated and the entry and exit paths are planned through the geographic information system processing. The slope parameters are calculated by using the digital land surface model and the personnel equipment configuration is optimized, the ground control points are laid on the site, and the geodetic coordinate system reference is established. The double route oblique photography mode is adopted, the image shooting sampling is carried out at a 45-degree visual angle, a 0.4m object distance and a 70% image overlap rate, the high-precision three-dimensional ecological model is generated through the point cloud reconstruction in combination with the morphological identification result of the species, and the parameters such as the habitat density, interspecific competition and light adaptability of the sessile organism are efficiently investigated.

This invention discloses a planning method and system for a hydrogen-containing integrated energy system. The method includes: constructing equipment instance models of various energy types in the system by configuring parameters; wherein the equipment includes electrolyzer equipment; constructing a load model in the system by configuring the load demand of the area to be planned, the load demand supporting configuration at multiple time scales; obtaining the energy price model of the area to be planned and completing the energy price configuration; constructing a system topology by graphically associating the equipment instance models, load models, and energy price models through a visual configuration interface, and configuring constraint rules on the system topology; wherein the constraint rules include start-up and shutdown optimization constraints for the electrolyzer; transforming the system topology with configured constraint rules into a mixed-integer linear programming model and performing optimization to obtain the configuration scheme and operation strategy of each device in the system. This invention solves the problems of insufficient characterization of equipment operating losses and low modeling efficiency in existing planning methods by introducing refined electrolyzer start-up and shutdown constraints and a visual modeling process, thus achieving efficient and accurate planning for hydrogen-containing integrated energy systems.

The invention relates to the technical field of information, in particular to an official document information extraction method and system based on visual modeling. The system comprises an official document image conversion module, a visual feature extraction module and a key information extraction module, and the official document image conversion module is used for converting an input official document into an image according to pages; the visual feature extraction module is used for extracting visual features in the converted official document image; the key information extraction module is used for identifying and extracting key information fields in the official document image. According to the official document information extraction method and system based on visual modeling, on the basis that visual feature modeling is carried out on official documents of different formats and types, simple, efficient and accurate information extraction is carried out according to visual features of extracted content fields.

The present invention relates to the field of geographic model technology, and more particularly to a method and system for visual modeling of road projects based on BIM technology. The present invention obtains a complete road surface range based on the splicing results of multiple measured depth images; then, combining the construction status and terrain complexity of different areas within the road surface range, the degree of modeling accuracy required for different areas is obtained, thereby adjusting the model accuracy of different areas, achieving dynamic matching of road models and construction progress, effectively retaining detailed information, and improving modeling accuracy.

This invention discloses a SysML-based visual modeling workflow configuration method, comprising the following steps: creating system design stages and sub-stages through a visual interactive interface, and setting operation items for each sub-stage; establishing a dynamic association mapping relationship between operation items and system modeling language model elements based on the semantic association method of the system modeling language, and converting it into an independent configuration file; automatically analyzing the upstream and downstream dependencies of operation items based on the configuration file; monitoring the execution status of each operation item in real time, and dynamically updating the execution status of sub-stages and stages according to the status; automatically providing recommended views and model elements for operation items, and generating design deliverables; automatically performing semantic association analysis of data conflicts; and recording the modification history of model elements for traceability management of design results. This invention provides an efficient, flexible, and traceable modeling workflow configuration method, significantly improving the accuracy and collaboration efficiency in the system design process.

The invention discloses a visual modeling and analysis method for in-situ fluidized mining of coal containing a fault structure, and relates to the technical field of numerical modeling and analys.The method comprises the steps that firstly, a Z-shaped progressive fluidized mining configuration is configured, and a multi-physics field coupling numerical simulation system is constructed; geologic structure parameterization is realized through multi-source geologic data fusion, a geomechanical prototype is constructed, and constitutive parameter mapping is completed; then, a three-dimensional geology-engineering integrated model is built and imported into a numerical platform after fine grid division, the whole mining process is simulated, and mechanical response data are collected; finally, the critical state of goaf instability is identified through multi-criterion coupling, and a basis is provided for filling opportunity and strength design. Accurate coupling of complex geology and dynamic mining is achieved, asymptotic damage of surrounding rock of the goaf can be actively monitored, safety and efficiency of deep coal resource mining are effectively improved, and powerful technical support is provided for intelligent and unmanned mining.

The present invention relates to a visual modeling method based on intelligent semantic understanding, comprising the following steps: a user inputs a modeling task goal, performs word segmentation processing, and obtains a word segmentation result; a user inputs a source data set, and obtains the characteristics of the source data set; a test model range is determined based on the word segmentation result; m test data are selected from the source data set to test the test model range, and a model test result is obtained; n preset algorithm models are selected from the preset algorithm models as alternative solutions, and corresponding n groups of algorithm model hyperparameters are determined; the n preset algorithm models and their corresponding n groups of algorithm model hyperparameters and the characteristics of the source data set are subjected to neural network learning; after learning, the n preset algorithm models are sorted and recommended according to model evaluation indicators. The present invention provides a form of recommended algorithm models in the form of intelligent recommendation for the modeling task goal given by the user, and provides users with a variety of model solutions that can directly solve their task goals.

The application discloses a PLC program reverse analysis method and device. The method comprises the following steps: obtaining a to-be-processed file; performing structural analysis processing on the to-be-processed file to obtain program entry address information and memory initialization information; performing subprogram identification processing on the to-be-processed file according to the program entry address information and the memory initialization information to obtain program flow feature data; performing identification processing on the program flow feature data based on a library function signature to obtain standard function block data; performing parameter extraction processing on the program flow feature data to obtain control behavior parameter data; and performing visual modeling processing on the program entry address information, the memory initialization information, the program flow feature data, the standard function block data and the control behavior parameter data to obtain reverse analysis result data. The automatic and structured control program reverse reconstruction capability is realized.

The invention relates to automatic testing for visual verification of generated images and videos. Various examples, systems, and methods related to a visual modeling pipeline are disclosed. A first computing system may receive visual data and a first prompt corresponding to a context of the visual data through a visual language model (VLM). The first computing system may determine at least one description of the visual data using the VLM and based at least in part on the visual data. The first computing system may determine a second cue based at least in part on the at least one description. The first computing system may convert the at least one description into a file format using a large language model (LLM). The first computing system may use at least one description of the file format for at least one automated test.

The invention discloses a visual modeling-script programming-brain graph type test case design system and method oriented to an embedded system, and belongs to the technical field of embedded systems. The method comprises the steps of receiving a user instruction, selecting and entering a design mode, and performing test case design in the selected design mode: if the design mode is a visual modeling mode, completing case design by dragging components, configuring parameters and establishing logic connection lines; if the mode is a script programming mode, script codes are written by calling a special function library, and case design is debugged and completed; if the mode is the brain map mode, using case design is completed by creating hierarchical nodes and carding test scenes and steps; and the data management module is used for storing the designed test case, and supporting exporting as a standard document or switching to other modes for secondary editing and data intercommunication. According to the method, three design modes are fused, the test case design efficiency and logic definition are remarkably improved, and team cooperation convenience is greatly enhanced.

The invention provides a conversion method of a five-dimensional radar map for voice emotion analysis and related equipment, and relates to the technical field of emotion analysis, and the method comprises the steps: obtaining input voice data, carrying out the preprocessing, carrying out the dual-mode feature extraction of the preprocessed voice data, obtaining a fusion feature vector, inputting a preset VAD emotion recognition model, and obtaining a VAD emotion recognition model; outputting a three-dimensional emotion space vector; and calculating a five-dimensional psychological index based on the three-dimensional emotion space vector and the fusion feature vector, performing normalization processing to generate radar map coordinate data and visual parameters, transmitting the radar map coordinate data and the visual parameters to a terminal, and dynamically rendering and displaying a five-dimensional radar map on a terminal interface of the terminal. Through adaptive normalization processing and radar map visual modeling, five-dimensional psychological indexes can be presented in a unified scale, and structural plotting is realized through radar map coordinate data and visual parameters, so that the problems of rough emotion description, insufficient data dimensions and limited visual ability in the existing scheme are solved.

The invention discloses a security risk assessment method and system based on attack chain deduction, relates to the technical field of network security, and solves the problem that security risks are difficult to comprehensively and accurately assess in the prior art. According to the embodiment of the invention, by establishing the asset-vulnerability-attack stage mapping relationship, the whole-process visual modeling of the attack chain from initial reconnaissance to target achievement is realized, the specific effect of the vulnerability in the attack chain is determined, and the problem that the vulnerability linkage effect is neglected in traditional assessment is solved, so that more comprehensive risk assessment is realized; in addition, the mapping relation can be updated in real time according to asset change and new vulnerability discovery, accurate basic data support is provided for attack path generation, and dynamic construction of an attack surface panoramic view is achieved. Besides, by introducing path selected probability parameters, subjective strategy preferences of the attacker are brought into quantitative evaluation of the risk, so that total risk evaluation better fits real attack decision logic, and a more accurate evaluation result is obtained.

The invention discloses a three-dimensional visual modeling method for a docking mechanism envelope space. The three-dimensional visual modeling method comprises the following steps: defining a characteristic coordinate system and a nominal position type of a docking mechanism; acquiring an envelope space boundary condition of the docking mechanism; simplifying geometric envelopes of the docking mechanism and a connecting assembly thereof, and establishing a virtual prototype standard envelope model of the docking mechanism; according to the virtual prototype standard envelope model of the docking mechanism and the boundary conditions of the envelope space, establishing a three-dimensional visual virtual prototype simulation model of the envelope space of the docking mechanism; and outputting a three-dimensional visual virtual prototype simulation model of the docking mechanism envelope space. According to the three-dimensional visual modeling method for the envelope space of the docking mechanism, the problems that in the prior art, a data description mode of the envelope space of the docking mechanism is not visual, and a visual modeling method for the envelope space of the docking mechanism is lacked are solved.

The invention discloses a logistics system visual modeling and simulation method and system based on deep learning, and the method comprises the following steps: collecting various types of logistics data, including transportation, traffic, storage and environment information, and constructing an adjustable modeling mechanism; an improved neural differential equation model is adopted, so that the system state continuously changes along with time, and a manifold regularization kernel regression method is introduced for dynamic adjustment. The system also utilizes a specific data structure to learn and restrain control input, keeps the modeling process stable and consistent, trains each module through a unified optimization strategy, and realizes dynamic simulation and visual output of the operation state of the logistics system. The invention aims to improve the modeling efficiency and response capability of the logistics system in a complex environment.

The invention relates to the technical field of warehouse management, in particular to a visual modeling method and system for warehouse products, and the method is characterized in that the method comprises the following steps: S1, obtaining order data of products; s2, preprocessing the order data to generate net data; s3, constructing a grouping processing module, and grouping the products by the grouping processing module based on the net data to generate a product packet; s4, constructing a stacking module, and performing stacking calculation on the products in the product package by the stacking module based on the net data and the product package to generate a stacking scheme of the product package; and S5, a three-dimensional modeling module is constructed, the three-dimensional modeling module carries out three-dimensional modeling on the product package based on the stacking scheme, and a visual three-dimensional model is generated. The method has the advantages of being independent of manpower, adaptive to diversified orders and capable of automatically generating the visual model.