1067 results about "Visualization methods" patented technology

The invention relates to the field of transportation visualization, in particular to a cold chain cargo transportation management visualization method and system. The method comprises the following steps of collecting cold chain cargo state parameters, performing cargo quality trend evaluation, and generating state data streams of a plurality of cargoes; performing dynamic positioning and tracking on the cold-chain transport vehicle, performing space-time mapping processing according to the state data flow, and constructing a real-time tracking trajectory flow; performing future aging deviation prediction on the real-time tracking trajectory flow to generate an aging deviation prediction result; carrying out transportation risk comprehensive assessment according to the aging deviation prediction result, and generating a transportation risk assessment report; and carrying out path planning calculation and client notification pushing according to the transportation risk assessment report so as to execute intelligent transportation management. According to the invention, the transportation energy consumption and time cost are reduced, the resource allocation efficiency is improved, and the cargo real-time tracking visualization effect is improved.

The invention discloses an urban building three-dimensional automatic modeling and visualization method, and belongs to the technical field of building three-dimensional modeling. The method comprises the steps that point cloud data, high-resolution images and geographic information system data of urban buildings are acquired, data cleaning, registration and alignment are carried out, and preliminary building digital representation is formed; accurately segmenting each building, and identifying the contour and main structural features of the building; based on the data integrity and the building complexity, adaptively selecting a proper reconstruction strategy to carry out three-dimensional reconstruction; in the reconstruction process, the geometric structure is analyzed and optimized in real time, and potential topological problems are repaired; automatically generating missing details based on a predefined architectural style library and a component library, and performing material inference and texture mapping; a graph structure is used for representing the relation between the buildings, and the positions and orientations of the buildings are adjusted through a global optimization algorithm; a rendering engine supporting multi-level detail switching is developed, and smooth visualization and interaction of a large-scale city scene are achieved.

The invention relates to the field of commodity visualization, in particular to a commodity display interaction visualization method and device. The method comprises the following steps: collecting a multi-azimuth image of a commodity, carrying out three-dimensional texture modeling, and constructing a three-dimensional texture mapping model; performing material light rendering on the three-dimensional texture mapping model to generate a material rendering result; collecting an environment detection image of a commodity display environment, and performing environment illumination adaptation compensation on a material rendering result to obtain an illumination compensation rendering commodity; carrying out attribute information visual layout on the illumination compensation rendering commodity to obtain a commodity visual space; and carrying out interaction response animation analysis according to the commodity visualization space, carrying out multi-target parallel rendering, and executing commodity interaction visualization operation. The form and surface details of the commodity in the real world are accurately restored, the visual reality sense is improved, and the interactive experience feeling of browsing the commodity by a user is enhanced.

The invention relates to the field of playing data visualization, in particular to a playing data visualization method and system. The method comprises the steps that at least one section of pedal data of at least one pedal is obtained, and the pedal data comprises a pedal value and a time stamp of the pedal value; generating at least one section of labeling track according to the pedal data; wherein the labeling track comprises a first simulation track and a second simulation track; correspondingly, the method comprises the steps that when the pedal value is larger than a first pedal threshold value, a first simulation track is generated according to the pedal value, and the first simulation track is displayed in a first labeling form; when the pedal value is larger than a second pedal threshold value and smaller than or equal to the first pedal threshold value, a second simulation track is generated according to the pedal value, and the second simulation track is displayed in a second labeling form; and generating a combined track according to the at least one section of labeled track, and displaying the combined track on the music score. According to the invention, the smoothness and integrity of pedal data display can be improved, and the user experience is optimized.

The invention belongs to the technical field of network security, and relates to a network attack behavior chain construction and active defense method and device and computer equipment, and the method comprises the steps: collecting full-flow data and a multi-source log from a network environment, and carrying out the preprocessing of the full-flow data and the multi-source log; storing the preprocessed full-flow data and multi-source logs, and establishing an associated index; through a deep learning algorithm and an unsupervised model, abnormal traffic and attack behaviors are identified from the full-traffic data and the multi-source logs; reconstructing the fragmented attack events into a complete behavior chain through a graph neural network and a visualization mode; based on the AI model, a dynamic defense strategy is generated, and a response action is automatically executed; through time sequence prediction and a deep learning model, a future attack trend is predicted, and active defense is realized. The method improves the unknown attack detection capability, optimizes the traceability efficiency, enhances the defense initiative, guarantees the real-time performance and accuracy of network attack prediction, and has compliance adaptability.

The invention relates to a coal mining safety prediction visualization method and system, and the method comprises the steps: determining a sensor deployment scheme based on mine geological structure information and operation environment characteristics; collecting multi-modal monitoring data according to the sensor deployment scheme, and generating a fusion data set of time-space alignment; extracting corresponding spatio-temporal features, and generating a corresponding risk assessment matrix based on the spatio-temporal features; constructing a four-dimensional tensor field containing a time dimension, and generating a dynamic risk visual image based on the four-dimensional tensor field; in the dynamic risk visual image generation process, receiving a feedback instruction input by an expert, and updating the coal mine safety domain knowledge graph by adopting a fuzzy cognitive mapping mode based on the feedback instruction; and optimizing the space-time convolutional network, updating the dynamic risk visualization image, obtaining an updated risk visualization image result, and executing hierarchical early warning processing. According to the method, the richness and accuracy of coal mining safety prediction visualization can be improved.

The invention discloses a brain wave monitoring visualization method and system, and the method comprises the following steps: obtaining original brain electrical signals of a user at different time points and task scenes, and carrying out filtering, denoising and segmented cleaning to obtain a preprocessing data set; performing frequency domain analysis on the data set, and extracting waveband power distribution; generating thermodynamic diagram data based on the power value, dynamically superposing the thermodynamic diagram data to the visual field of the user through an augmented reality technology, and displaying the activity intensity of the brain area; and accumulating data for a long time to construct a personalized baseline database, comparing the current power with a scene threshold value in real time, generating warning feedback by associating the thermodynamic diagram when the power is abnormal, and optimizing the baseline database. According to the method, the abstract electroencephalogram signals are converted into the visual thermodynamic diagrams, personalized baselines and dynamic feedback are combined, the problems that traditional monitoring data is difficult to understand, depends on group threshold misjudgment and is lack of dynamic optimization are solved, and the intuition, accuracy and practicability of electroencephalogram monitoring are improved.

The invention relates to the field of optical nondestructive testing, and discloses a visualization method for detecting mango quality based on hyperspectrum, which comprises the following steps of: firstly, selecting mango samples, and simulating different mango ripening stages by dividing the mango samples into a plurality of groups of samples; acquiring a high-dimensional spectral image by using a hyperspectral imaging system, and measuring the hardness, the soluble solid content and the titratable acid content; correcting and extracting the high-dimensional spectral image to obtain and optimize the average reflection spectrum of the sample, and establishing a mango maturity classification model and a quality regression prediction model; performing characteristic wavelength contribution degree analysis and screening, and optimizing a quality regression prediction model by adopting a key wave band; the method is applied to each pixel point of a high-dimensional spectral image, a two-dimensional distribution diagram is generated, and mango quality visualization is achieved. The method solves the problems that in the prior art, rapid and lossless judgment of the mango ripening stage cannot be achieved, accurate prediction and visual distribution of key internal quality indexes cannot be achieved, and intelligent grading and quality control of picked fruits are not ideal.

The invention relates to the technical field of defect detection, and discloses an intelligent identification and distribution visualization method and system for weld defects, and the method comprises the steps: collecting a weld ray detection image, carrying out the denoising of the image, obtaining a smooth image, carrying out the multi-scale feature extraction, and obtaining a weld segmentation image through semantic segmentation; a convolutional neural network is adopted to classify different defect types, pixel labeling is carried out, and a defect labeling image is obtained; performing uniform grid division on the welding seam segmentation image, and filtering boundary pixels to obtain an optimized sub-region set; calculating a quantitative proportion of defect pixels and total pixels in the sub-regions, comparing the quantitative proportion with a preset proportion threshold value, then completing classification, and mapping the quantitative proportion to a two-dimensional matrix to obtain a density distribution matrix; the proportion values are aggregated in the length and width directions of the welding seam, and missing data points are filled to obtain a continuous proportion value sequence; and corresponding colors are distributed for the proportion values, and a defect distribution thermodynamic diagram is obtained after rendering. According to the method, high-precision detection and visual presentation of weld defects can be realized.

The invention provides a social network hierarchical visualization method and system based on a structure entropy and a coding tree, and the method comprises the steps: obtaining graph data, building the coding tree based on the graph data with the minimized structure entropy, and enabling the coding tree to be used for capturing a hierarchical community structure of a graph; constructing a minimum entropy priority queue, adaptively selecting non-leaf nodes for division by adopting the minimum entropy priority queue, and distributing a current structure entropy value as a weight for a cross-community edge; force-oriented layout based on structure entropy and layout entropy is used, attraction is adjusted based on edge weight, standard repulsive force is kept, and a force model is established; solving a layout entropy maximization target for the force model to calculate a layout result; and for the calculated layout result, outputting and rendering a layout result with a clear community separation effect as a final visualization result.

The invention provides an intelligent data consanguinity tracking and visualization method based on graph calculation, and the method comprises the steps: carrying out the data structure analysis and metadata extraction of original data assets, so as to generate a standardized data asset package; performing graph node attribute definition on the data entities in the standardized data asset package, and performing graph edge attribute definition on the association relationship between the data entities to generate a first data blood relationship model; performing blood relationship path mining on graph nodes and graph edges in the first data blood relationship graph model to obtain a basic blood relationship path set, and performing quantitative calculation and feature labeling on path association strength in the basic blood relationship path set to generate a second data blood relationship graph model; and performing visual rule mapping on graph node attributes and graph edge attributes in the second data blood relationship graph model to construct a standardized visual data set and generate a data blood relationship visual interaction interface according to the standardized visual data set.

The invention relates to a method for constructing and visualizing a knowledge graph of a secondary virtual loop of an intelligent substation, which solves the problems of incomplete visualization, incomplete relevance, poor readability and the like in the prior art, and adopts the technical scheme that the method comprises the following steps of: acquiring an SCD configuration file and an optical fiber link table of the intelligent substation; reading and analyzing the SCD configuration file, and obtaining virtual loop configuration information of the whole station; matching the virtual loop with the soft pressing plate based on the configuration information of the virtual loop of the whole station; matching the physical loop with the virtual loop based on the total station virtual loop configuration information and the optical fiber link table; constructing a knowledge graph based on the total station virtual loop configuration information; and constructing a total station secondary equipment virtual loop configuration database based on the knowledge graph. The method has the advantages that the configuration information of the virtual loop of the whole station can be completely presented in a graphic form, the visualization degree of the secondary virtual loop of the intelligent station is effectively improved, and the working efficiency of on-site technical improvement, defect elimination, verification and the like is improved.

The invention relates to the field of medical image processing and pathological diagnosis, aims to solve the problems that brain glioma multi-modal image fusion precision is low, heterogeneity feature and pathological association is weak, and visualization readability is poor, and provides a visualization method and device. The method comprises the steps of multi-modal image preprocessing and registration, regional adaptive multi-modal fusion, pathology association type heterogeneity feature quantification, multi-dimensional pathology visualization, and result verification and optimization. Images are rigidly registered and aligned through mutual information, features are enhanced by adopting a regional differentiation attention fusion algorithm, features are quantified through an improved LSSVM, pathological gold standards are associated, and a three-dimensional visualization model is constructed to visually present heterogeneity information. The device comprises a memory and a processor and can execute the method. According to the method, the heterogeneity evaluation accuracy and clinical readability are improved, treatment scheme optimization is assisted, and the method is suitable for accurate diagnosis and treatment scenes of brain glioma.

The invention relates to the technical field of artificial intelligence, and provides a tower crane multi-dimensional data dynamic analysis and visualization method and system and terminal equipment. The method comprises the following steps: acquiring multi-dimensional monitoring data of the tower crane; establishing a synchronous monitoring model of the tower crane by adopting a digital twin technology based on the multi-dimensional monitoring data, and synchronously displaying the synchronous monitoring model in a user interface; based on a viewing instruction of a user to the synchronous monitoring model, matching a target display dimension for the user, synchronously setting a folding dimension which is not matched with the viewing instruction, and hiding model display information corresponding to the folding dimension in the synchronous monitoring model; calling a preset analysis model matched with the target display dimension, extracting target monitoring information from the synchronous monitoring model, and performing tower crane dynamic analysis on the target monitoring information through the preset analysis model; and updating the dynamic analysis result of the tower crane into the synchronous monitoring model to update model display information matched with the target display dimension in the synchronous monitoring model, thereby improving the operation and maintenance decision efficiency and accuracy.

The invention relates to a port water area ship navigation risk distribution calculation and visualization method and device based on AIS and GIS data fusion, and the method comprises the following steps: 110, obtaining ship AIS data, and carrying out the preprocessing of the ship AIS data, thereby obtaining the preprocessed ship AIS data, and the preprocessing comprises the standardization, feature extraction and abnormal point detection; step 120, carrying out port water area grid construction, and carrying out grid mapping and legality screening on the preprocessed ship AIS data; step 130, performing port water area static risk assessment, port water area dynamic risk assessment and port water area propagation risk assessment on the port water area, and performing port water area comprehensive risk assessment on the basis to obtain an assessment result; and step 140, drawing a port water area risk thermodynamic diagram based on the evaluation result to realize risk distribution visualization. According to the invention, efficient and scientific decision support can be provided for port safety management.

The invention provides a construction progress visualization method and system. The method comprises the following steps: constructing a virtual building model of a construction project; obtaining a plurality of construction areas of the construction project, and constructing a plurality of task consumption areas in the virtual building model based on the plurality of construction areas; generating task particles in the virtual building model in response to distribution of construction tasks of the construction project; based on the quantity-price information of the construction task, generating the work content of task particles; obtaining entry and exit data of the construction site, and visually presenting task particles in the task consumption area based on the entry and exit data; and obtaining work recording information of the construction task, updating the work content of the task particles based on the work recording information, and generating a visual construction progress in the virtual building model based on the change value of the work content. The amount-price information is directly associated through the work content of the task particles, the project progress can be associated with the virtual building model, and a visual basis is provided for cost progress management and control.

The invention discloses a user risk coefficient calculation process visualization method and system. The method comprises the following steps: acquiring user behavior data, and constructing a risk assessment dimension system; determining node types of non-leaf nodes, and constructing a rule tree structure; performing risk assessment on behavior characteristics of the user behavior data by using the risk prediction model, and extracting risk factors; analyzing the risk factors by using an SHAP model, determining feature influence relation data and a high-risk rule combination between the risk factors, and filling non-leaf nodes with non-leaf node attributes; determining node weights of non-leaf nodes to update attributes of the non-leaf nodes; based on leaf node attributes and updated non-leaf node attributes, breadth-first traversal is carried out on the rule tree structure, and a risk scoring result of a traversal path is calculated by adopting a bottom-up backtracking mechanism; and carrying out visual display on the risk scoring result of the rule tree structure and the traversal path. The risk identification accuracy can be improved.

The invention discloses a visualization method and system for an oversized in-situ filling space under a composite roof, and belongs to the technical field of information processing. The method comprises the following steps: performing multi-angle data acquisition on a filling space under a composite roof structure to obtain original point cloud data; obtaining complete three-dimensional point cloud data based on the original point cloud data; preprocessing the three-dimensional point cloud data to obtain standard point cloud data; performing boundary contour recognition based on the standard point cloud data to obtain space boundary contour data; obtaining a spatial three-dimensional geometric model based on the spatial boundary contour data; performing section slicing based on the space coordinate range of the space three-dimensional geometric model, and obtaining size distribution data based on the obtained contour size parameters of the section; obtaining a total volume and a segmented volume of the filling space based on the size distribution data; and obtaining a three-dimensional visual model of the filling space based on the total volume and the segmented volume. The method provides reliable technical support for mine filling design and resource evaluation.

The invention discloses an administration agent in-vivo release and absorption visualization method based on a CFD-PBM coupling model. The method comprises the following steps: constructing a CFD model of a physiological environment of an injection site; establishing a population balance model (PBM) of the drug particles; the PBM is embedded into a CFD model solver, multi-scale coupling simulation is carried out, and a CFD-PBM coupling model is obtained; the three-dimensional visualization engine dynamically displays drug concentration distribution and particle behaviors; reversely adjusting preparation prescription parameters by using a multi-parameter optimization algorithm; and calibrating model parameters, and generating a key data report. According to the method, the prediction precision and the research and development efficiency can be remarkably improved, and the method is suitable for development of long-acting preparations such as microspheres and implants.

The invention provides a large-scale knowledge graph visualization method and system, and relates to the field of knowledge graph visualization. The method comprises the following steps: acquiring knowledge graph data, and clustering the knowledge graph data through a modularity-based discovery algorithm; obtaining each sub-graph corresponding to the clustered knowledge graph data, and for each sub-graph, selecting a representative node based on a PageRank algorithm or a Leader Rank algorithm; carrying out force-oriented layout on the clustered knowledge graph data through a tree diagram space filling technology; and for the knowledge graph data subjected to the force-oriented layout, distributing priorities and use times of a Barnes-Hut algorithm and a random vertex sampling algorithm according to a preset mode, and dynamically displaying a visualization result in a layered manner through an affine transformation technology. According to the method and the device, the problem that the structural expression clarity of the drawn knowledge graph is greatly reduced due to the fact that semantic clusters and hierarchical organizations in the graph are difficult to accurately present in a traditional visualization method is solved.

The invention discloses an AR-based optical fiber loop virtual-real linkage visualization method and system. The method comprises the following steps: acquiring configuration data of an optical fiber loop, and constructing an optical fiber loop knowledge graph; sLAM processing is carried out on the collected live-action image data, a three-dimensional space map is constructed, equipment positioning identification is realized, and an AR basic scene is generated; the optical fiber loop knowledge graph is converted into a three-dimensional optical fiber model, spatial registration and superposition rendering are carried out on the three-dimensional optical fiber model and an AR basic scene, and virtual-real fusion visualization is achieved; receiving a voice instruction and a gesture operation of a user, and performing query processing based on the knowledge graph to realize bidirectional tracing from a physical entity to a logic entity; collecting multi-dimensional state parameters of an optical fiber loop to form a multi-parameter time sequence data snapshot, and realizing optical fiber state anomaly detection through multi-marginal random flow matching; and finally, integrating an abnormal detection result with an AR visualization system, displaying the state of the optical fiber loop in an AR interface, and generating state early warning information. The efficiency of optical fiber loop management and maintenance is improved.

The invention relates to the technical field of disease identification, in particular to a road disease distribution visualization method and system, and the method comprises the following steps: obtaining a road inspection image of a cross section structure layer, extracting edge points, recognizing direction offset and curvature mutation features, constructing a structure layer buffer graph, matching disease marks, and marking structure information. And calibrating passing attributes and adjusting positioning coordinates, constructing a coverage layer structure, counting multi-cycle disease changes and generating a path layer. According to the method, a disease distribution task of a multi-structure combined road is processed, a boundary buffer graph is constructed based on an edge direction vector and a structure cross-section coordinate interval, and the trans-boundary characteristic of a disease boundary between structure layers is dynamically identified in combination with the position of a curvature mutation point; the influence of structural dislocation, annotation distortion and periodic noise interference on layer expression is avoided, and graphic expression and trend evolution description of a road disease distribution result under a complex structure road are supported.

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

The invention discloses a port avionics hub digital twin multi-level simulation model construction and visualization method, which comprises the following steps: obtaining a multi-view RGB image of a target port area, obtaining a camera attitude of each view by using an SfM algorithm, and reconstructing a sparse three-dimensional point cloud; constructing an LOD2 shell model with a semantic mark; an LLO3 model with holes is constructed; the LOD0-LOD3 model is serialized into a glTF 2.0 binary format and transmitted to a client side through HTTP / 2, the client side calls WebGL 2.0 through a browser to complete decompression, uploading and PBR rendering, and interactive plug-in-free visualization is achieved; constructing an eight-fork-two-fork-four-fork mixed spatial index, and performing multi-stage division and persistence on the LOD < 0 >-LOD < 3 > tiles, so that a client locates visible tiles within constant time based on node numbers; visual cone cutting and screen space error judgment are adopted to execute progressive loading on visible tiles, LOD0 is loaded at first, then LOD1-LOD3 is subjected to incremental superposition, low-level tiles in the same area are replaced with the LOD3 in a cross fading mode at the ultra-close distance (the Euclidean distance d from the center of a camera to the center of a target tile is smaller than or equal to 100 m), and smooth visual experience is obtained in a browser.

The present disclosure relates to a dental lesion detection method and a system to which the method is applied. A dental lesion information visualization method according to the present disclosure includes the steps of acquiring data of a lesion analysis model which outputs data on the type and location of a lesion included in a panoramic image obtained by capturing an image of the oral cavity of a patient, and inputting a panoramic image into the lesion analysis model to output data on the type and location of a lesion and a lesion detection confidence score.

The invention relates to the technical field of engineering structure health monitoring and artificial intelligence, and discloses an offshore wind turbine tower drum base three-dimensional stress distribution prediction and visualization method, which comprises the following steps: generating batch working conditions by presetting a bending moment range and an interval, and calling a finite element software automation script to execute static analysis; node stress values are extracted and integrated into a structured training data set; customizing neural network training: constructing a full-connection network, and training a model by adopting a standardized preprocessing and early stop mechanism; generating an interactive cloud picture: generating a 3D stress cloud picture HTML (Hypertext Markup Language) file supporting rotation / zooming / data query based on a spatial interpolation algorithm and a Plotly tool, and automatically marking the coordinate and the numerical value of a maximum stress point; and end-to-end system deployment: packaging as a Flask Web application, and inputting a bending moment value by a user to generate an interactive cloud picture in real time. The stress analysis period is greatly shortened, the engineering application threshold is reduced, and rapid evaluation and remote cooperation of the offshore wind turbine tower drum base can be efficiently supported.

The invention discloses an intelligent chart visualization method based on a model control protocol. The method comprises the following steps: step 1, establishing connection between a visual rendering client and an intelligent analysis server; 2, receiving a natural language visualization instruction of a user, and obtaining source data; 3, intention recognition is conducted on the natural language visualization instruction, and feature extraction is conducted on source data; 4, determining an adaptive visual chart type; 5, generating a model control protocol instruction packet; 6, receiving and analyzing a model control protocol instruction packet; and step 7, constructing a three-dimensional grid model, and submitting the three-dimensional grid model to a graphic processing unit for rendering display. According to the method, an artificial intelligence natural language understanding technology and a three-dimensional graph programming visualization technology are combined, and the method has the advantages of chart self-adaption, visualization and scene fusion, real-time and efficient rendering and the like.

The invention provides a self-defined graph node visualization method based on dynamic rendering of service attributes, which comprises the following steps of: receiving and verifying node style configuration in a JSON format, and analyzing the node style configuration into an internal model containing graph definition, style, rule and position; dynamically evaluating whether graphic elements are displayed or not according to rules in combination with node service data, and generating a to-be-rendered set; and finally, performing layered rendering: firstly drawing a basic shape and a style, and then rendering dynamic elements meeting conditions according to a sequence to finish node drawing. According to the method, a user only needs to set rules and styles through a configuration interface, drawing codes do not need to be written, the system can automatically and dynamically render nodes with rich visual elements according to the service data, and the expressive force and development efficiency of graph visualization are greatly improved.

The invention discloses a multi-dimensional graph series-parallel and visualization method for telecommunication network fraud cases based on a graph database. According to the method, intelligent series-parallel analysis across time-space cases is realized by constructing a knowledge graph containing various entities such as cases, personnel, accounts and equipment and deeply fusing a hard association matching algorithm and a soft similarity graph algorithm. The system has the functions of white list filtering, time sequence behavior analysis, NLP information extraction and the like, and can effectively identify criminal gangs, track fund flow directions and mine crime modes. And finally, dynamic visual display is carried out through a plurality of interactive views such as a force-oriented graph, a time axis and a mulberry-based graph, and clue intelligent pushing and report automatic generation are supported. According to the method, the case association mining depth, the serial-parallel analysis efficiency and the interpretability of a complex network are remarkably improved, and an efficient technical support is provided for the public security organization to fight against telecommunication network fraud.

The present application relates to the technical field of geological model, especially to a three-dimensional geological model dynamic visualization method, system, equipment and storage medium for underground engineering. The technical scheme comprises the following steps: data acquisition and integration: obtaining geological data through various exploration methods, and performing standardized and fusion processing to obtain unified three-dimensional coordinate geological data; three-dimensional geological model initialization construction: constructing a stratigraphic framework based on the integrated data, and accurately embedding geological structures therein to form a complete three-dimensional geological model framework; model dynamic visualization rendering: setting specific lighting and material properties for the constructed three-dimensional geological model. The present application constructs a high-precision model through multi-source data fusion, optimizes the visualization effect and interactivity, realizes real-time monitoring and continuous optimization of the model, provides accurate geological basis for underground engineering, enhances decision accuracy, ensures safety, improves construction quality and economic benefits.