40 results about "Web visualization" patented technology

The invention discloses an electric power communication network visual operation and maintenance method based on digital twinning, and the method comprises the steps: carrying out the coupling mapping of a global data mirror image and multiple sources, collecting data through a reconfigurable sensing array, and outputting a three-domain digital mirror image through time alignment; semantic topology reconstruction is carried out, and a dynamically growing semantic topology is generated by using a graph semantic engine; based on explainable causal chain fault tracing, an event-causal-countermeasure knowledge network is constructed; performing multi-target balancing operation and maintenance decision making, and screening an optimal strategy by using a three-dimensional Pareto model; immersive visualization and interactive intervention are performed, and a cross-platform engine is injected to realize multi-dimensional display. According to the method, through multi-source data accurate mapping, topology dynamic adaptation, causal interpretable traceability and scientific decision making, the problems of data islands, topology lagging and low decision making efficiency in existing operation and maintenance are solved, and the operation and maintenance accuracy and efficiency of the electric power communication network are improved.

The invention relates to a community structure discovery-oriented large-scale complex network visualization method. The method comprises the following steps: acquiring a large-scale complex network; extracting topological structure features of the large-scale complex network by using a representation learning technology to obtain a node representation vector set; performing dimension reduction processing on the node representation vector set by using PCA and t-SNE algorithms to obtain an output vector set; recursive clustering is carried out on the output vector set, each level in the hypergraph is divided, a community formed after clustering of each level is constructed as a super node, the relation between nodes in the community is combined as a hyperedge, and a hypergraph structure is constructed; and visualizing the hypergraph structure by using a diversified visualization algorithm. By adopting the method, the visualization effect of the complex social network can be improved.

The invention provides an electric power material detection system based on an improved association rule and a knowledge graph, and belongs to the field of electric power material detection. According to the system, an association analysis model for equipment detection is established by using an association rule algorithm, a hidden association relationship between unqualified detection items is mined, and a judgment basis for the disqualification of the related items is provided. In addition, in combination with information such as a material and equipment detection report and expert knowledge, knowledge such as entities, attributes and relationships is extracted from semi-structured data by adopting a natural language processing technology, a material and equipment detection management knowledge graph is constructed in a graph database Neo4j, a systematic material detection knowledge base is provided, network visualization is carried out, and the material and equipment detection management knowledge graph is established. And information query and management are facilitated. According to the invention, the detection efficiency of the electric power material equipment is improved, and increasing detection requirements are met.

The invention provides an interface display parameter adjustment method and device, electronic equipment, a computer readable storage medium and a computer program product, and relates to the technical field of artificial intelligence such as neural networks, visualization and automatic driving. The method comprises the following steps: determining a pupil diameter change rate according to an eye image obtained by shooting a riding object; according to the focal length of the camera shooting the eye image and the pupil diameter change rate, the eyeball focal length of the riding object is determined; determining a target visual range of the riding object on the display screen based on the eyeball focal length; and adjusting display parameters of interface contents presented by the display screen based on the target visual range. By applying the scheme, high-precision adjustment of the display parameters can be realized and personalized visual experience can be provided under the condition that manual operation or voice instruction issuing is not needed in the whole process, the efficiency and the convenience degree of obtaining information from the display screen in the riding process are improved, and the riding safety is improved.

The application relates to a network visualization method based on hierarchical layout and a clustering algorithm, and belongs to the field of data visualization.The method comprises the following steps: calling an API interface to obtain circuit data and processing the circuit data, using a dynamic clustering algorithm to perform clustering processing on the data, layering the data processed by the precondition clustering algorithm, each cluster serving as a layer, determining the sequence of each layer according to the structure of the clustering result, mapping the clustering result to hierarchical levels to form node sets of different layers, optimizing the node sequence of each layer to reduce the crossing of edges, calculating the coordinates of each node according to the layering and crossing reduction result, performing drawing according to the calculated node coordinates to convert the processed data into a topology diagram, and acquiring alarm data in real time, performing correlation analysis on the alarm data, and identifying potential fault causes.The method can efficiently process various complex network data and realize intuitive display and dynamic analysis of network structures.

Systems and techniques for read-write network visualization are described herein. A selected sub-region of a visual representation of a graph network may be displayed based on inputs received from a user. Boundaries for the selected sub-region of the visual representation of the graph network may be calculated. State data may be captured for a portion of the graph network associated with the selected sub-region using the calculated boundaries for the selected sub-region of the visual representation upon activation of an edit mode user interface control. A change to an element of the graph network may be identified. The graph network may be modified based on the change. A formula may be identified that is associated with the element of the graph network. The formula may be automatically recompiled and values for the element of the graph network, and nodes and edges that share a path with the element, may be automatically recalculated using the recompiled formula.

In certain implementations, a computer system includes one or more processors and one or more non-transitory computer-readable storage media storing programming for execution by the one or more processors. The programming includes instructions to receive a request for a visualization of a communication network. The communication network includes network devices in a hierarchical arrangement that includes multiple hierarchical levels. The programming further includes instructions to access, in response to the request, network information for the network devices, and to generate, according to the network information, a network visualization of the communication network for display. The network visualization includes a center region and rings arranged in a concentric manner and extending radially from the center region. Each ring at least partially surrounds the center region and includes one or more ring segments that each represent a respective network device.

In accordance with an embodiment, described herein is a system and method for providing a network-visualization browser extension in an analytics environment. An analytic applications environment can be provided by, or otherwise operate at, a computer system providing access to a data warehouse, or data warehouse instance. The system is adapted for generating a network graph from analytic artifacts, including display of one or more dataflows as dataflow constellation visualizations that illustrates the dataflows and a lineage or other relationship information. The systems and methods disclosed herein can provide tools to provide insights for users of an analytics environment with regard to the users' analytic artifacts and relationships among the same.

The invention discloses an implementation method of an immersive dangerous working condition emergency drilling platform based on Web and VR equipment and the drilling platform, and belongs to the field of Web visualization and emergency management. And the common problems of high cost, high risk, poor immersion and insufficient flexibility of the traditional means are solved. The method comprises the following steps: constructing a Web front-end system, and integrating a Babylon.js engine to realize 3D scene rendering; loading and analyzing the industrial equipment model in the GLTF / OBJ format; a WebXR API (Application Program Interface) of Babylon.js is utilized to be in butt joint with the VR head-mounted display equipment; defining a drilling process through a configurable JSON / JS script; recording a user operation path, reaction time and operation sequence data, and generating a quantitative evaluation report; multi-person collaborative drilling is realized based on WebSocket, and an administrator is supported to monitor behaviors of participants through a background interface and perform remote intervention. The method is used in the emergency response drilling field.

This application provides a method for point cloud data management and rapid Web identification and visualization, relating to the field of point cloud data processing technology. The method involves establishing a point cloud database; performing point cloud similarity clustering on the point cloud database, and then performing adaptive denoising processing based on the similarity clustering results to establish a denoised point cloud set; establishing a scale-space pyramid, using the similarity clustering results to call and match the scale-space pyramid, and reconstructing a position multi-scale model based on the call matching results; performing feature extraction on the denoised point cloud set using the position multi-scale model to establish a tunnel structure feature set; and using the tunnel structure feature set to perform tunnel visualization fitting and create a Web visualization model. This application solves the technical problem in the prior art of low Web visualization quality due to the large amount of tunnel point cloud data and the presence of noise and redundant information, significantly improving the processing efficiency and rendering performance accuracy of tunnel point cloud data on the Web.

This invention discloses a Web 0Day vulnerability detection and mining method and platform based on a security agent, which relates to the field of network security. The method includes the following steps: collecting and preprocessing massive amounts of network security-related data; training a large security model for a vertical network security field; using the large security model as the core, in combination with a customized memory module, tool module, and planning module, and utilizing the agent characteristics of the large model to construct a security agent; building a Web visualization platform based on cross-language integration and front-end visualization technology in combination with the security agent; and implementing vulnerability analysis of Web page content, generation and verification of vulnerability test cases, and visual display of security professional knowledge questions and answers based on the Web visualization platform. The invention realizes in-depth dynamic analysis and multi-dimensional feature mining of Web applications, improving the mining capability and detection efficiency of Web 0Day vulnerabilities.

The invention discloses a multilevel eigenvalue layered rendering method for massive time series data of the Internet of Things. The method comprises the following steps: a back end predefines multi-stage time granularity, regularly calculates the maximum value and the minimum value of original data in each time window, and persistently stores the maximum value and the minimum value as a multi-layer characteristic value data set; the front end intelligently matches the optimal hierarchy according to the current view time span and requests the feature value of the hierarchy; and the front end draws a vertical line segment or an envelope line for rendering by using the maximum value and the minimum value of each window. And during user interaction, data hierarchies are dynamically switched to realize smooth drilling. Through the core technology of extreme value pre-calculation, on-demand matching and envelope line rendering, the fluctuation range and key event characteristics of data are completely reserved while front-end single-time rendering data points are strictly controlled within thousand levels, high-performance and high-fidelity Web visualization of ten-billion-level time series data is achieved, and the real-time performance of the system is improved. The technical problem that performance, precision and interactive experience cannot be achieved at the same time in a traditional scheme is solved.

The present invention discloses a zero-code system for object detection and a construction method. The system includes a presentation layer, a service layer, and an infrastructure layer. The presentation layer is a web visualization interface; the service layer includes a user login module, a camera management module, a data management module, a label management module, an online annotation module, a model creation module, a model management module, a model training module, a model verification module, a model application module, and a real-time monitoring module; the infrastructure layer includes cameras, databases, file storage servers, and algorithm deployment servers. The zero-code system supports a one-stop zero-code AI development process including data management, data annotation, model training, result display, and model deployment, directly putting the trained AI model into use with cameras, with zero code throughout the process, applicable to scenarios such as picture content retrieval, security monitoring, and industrial quality inspection, greatly reducing the threshold of artificial intelligence innovation and entrepreneurship and the procurement and customization costs of models.

The application relates to the technical field of fault prediction and health management, and particularly discloses a business-level network visual monitoring method for fault prediction and health management, which restores the round trip process of a business session through a bypass probe, splits network access time consumption into three parts of client transmission, server transmission and application processing, and identifies an abnormal delay position by using a historical baseline. For an abnormal session, instead of directly taking the CPU rise collected during diagnosis as fault evidence, a diagnosis disturbance instruction with calibrated resource consumption is first sent, and then the processor utilization deviation amplitude and recovery time length of the target device are observed to judge the pressure margin. Meanwhile, the system determines the fault direction in combination with indexes such as retransmission, zero window, packet loss and same-type business delay, outputs a unique root cause and confidence, and is visually displayed in a business topology.

Systems and methods that provide visualization of networks. Data is input into a table structure that represents any hierarchy of entities, relationships and their attributes. The content of the table is processed to extract the entities, relationships and their attributes. These are turned into nodes, edges and a visual representation of their attributes using color gradients, categorical colors, shapes, thickness, text labels, etc.

This invention discloses a method for building a digital twin visualization screen. By extracting and classifying family components from the BIM model, it achieves effective data organization and management. It establishes a link between the backend marker configuration library and the family library, enhancing data traceability and consistency. Combining the BIM model with IoT data, it uses GUID codes and device ID codes to achieve precise association, ensuring data integrity and accuracy. The UE engine is used to transform the BIM model into a highly realistic digital twin model. An interactive interface enhances user customization capabilities and ease of operation. Data interaction between the IoT platform and the WEB visualization frontend enables real-time updates and dynamic display, improving system usability and user experience. The BIM model undergoes lightweight transformation in the IoT platform, improving data processing efficiency and response speed. Lightweight mobile terminals for IoT and BIM enable automated data collection and storage. The backend IoT database integrates complete data, providing support for intelligent analysis and decision-making.

The invention relates to an ore scale key parameter estimation method based on quantum semantic entanglement. The method comprises the following steps: S1, selecting and storing sample data; s2, sample data are checked and preprocessed; s3, dividing the sample data into a training set and a test set; s4, carrying out encoding operation on the data; s5, performing hyper-parameter setting on the quantum semantic entanglement-based ore scale key parameter estimation system; s6, training an estimation system by using the training set until the loss function is converged; s7, estimating the thickness of the sample section in the sample data test set by using the trained estimation system; and S8, carrying out effect evaluation and verification on the estimation system through the test set. According to the method, accurate calculation of key parameters of ore sampling data is realized, and results are displayed in an explicit manner through Web visualization; compared with other existing systems, the method has the advantages that correlation gaps among multi-dimensional features are identified by using the advantages of quantum semantic entanglement, so that key parameters in sampling data are calculated.

The invention provides a heterogeneous network visual fault monitoring method and system, and the method comprises the steps: S1, finding a new device, carrying out the management of the new device to a management center, inputting basic information to a management database, and forming a traceable management log; s2, updating the global network topology according to the topological relation of the new equipment; s3, continuously collecting monitoring logs of all devices, and uploading the monitoring logs to a time sequence database; s4, setting a monitoring index, determining a safety threshold value of the monitoring index, and triggering an alarm and positioning a fault node when an out-of-control monitoring index is identified; and S5, converting the global network topology into a visual picture, dynamically displaying the visual picture at a visual front end, and synchronously marking the fault node. According to the method and the device, a traditional monitoring tool data island is broken through, the dependency relationship of the network topology is clarified, and real-time visual monitoring of the financial heterogeneous network is realized.

The application discloses a ship trajectory parallel kernel density visualization method based on a GPU shader, and the method comprises the following steps: obtaining original AIS data, and preprocessing the original AIS data to obtain target data; adopting a spatiotemporal convolution kernel density parallel calculation method to process the target data to obtain a spatiotemporal convolution kernel density processing result; and performing visualization processing on the kernel density processing result to obtain a Web visualization result of ship behavior patterns. The application embodiment improves the analysis depth of the ship behavior patterns, optimizes the interactivity and accuracy of data display, and can be widely applied to the computer technology field.

The application discloses a three-dimensional visualization system and construction method based on Ethereum big data, which classifies Ethereum blockchain big data according to entities, and constructs an Ethereum head ecological network model by using a Spark computing framework. The whole Ethereum network model is laid out by using a three-dimensional force guiding model, and the Barnes-Hut optimization algorithm extended to three dimensions is introduced in the graph layout process. The local part is laid out on the surface by using a spherical layout method. Finally, the WebGL, ThreeJS and other WEB three-dimensional graphics rendering technologies are used to realize the visualization display of the Ethereum head ecological network on the WEB side. The user can view the three-dimensional visualization model of the Ethereum transaction network in different ways, so that the user interaction process becomes more smooth, the details of the three-dimensional visualization model are controlled more deeply, and the search function in the model is provided, so that the user can quickly locate the node to be concerned.

The invention relates to an ore body or block economic value evaluation method based on quantum environment perception. The method comprises the following steps: S1, selecting an ore body or block economic evaluation data set and importing data; s2, dividing the price data into a training set and a test set according to a ratio of 7: 3; s3, carrying out encoding operation on the data; s4, constructing a graph structure; s5, quantizing the graph structure; s6, setting hyper-parameters of an economic value assessment model (QEM) based on quantum environment perception; s7, training the economic value evaluation model QEM by using the training set until the model loss function is converged; s8, evaluating the economic value of the ore body or the block section by using an economic value evaluation model QEM; and S9, performing test evaluation and verification on the economic value evaluation model QEM through the test set. According to the method, the mining value of the ore body or the blocks is estimated in real time, and the result is displayed in an explicit mode through Web visualization; compared with other existing systems, the method utilizes the compatibility of quantum state modeling to multi-dimensional feature data to promote the estimation of the economic value of the ore body or the block.

The present invention relates to the field of network technologies, and provides a network visualization processing method, apparatus, computer device, and storage medium. The method includes: displaying a network visualization interface; the network visualization interface is used for visualizing a wireless network, and the wireless network includes multiple device nodes, and the device nodes include forwarding nodes capable of communicating with a border router; in the network visualization interface, displaying a topological structure between each device node generated based on a neighbor table forwarded by each forwarding node through the border router; the neighbor table includes adjacent communication links existing between the device nodes and the corresponding forwarding nodes and signal strengths corresponding to each communication link; the topological structure includes communication status information between each device node in the wireless network. By visualizing the wireless network, the present invention can effectively improve the troubleshooting and network optimization of wireless networks including wireless Mesh networks.

A packet forwarding network may include switches that forward network packets between end hosts. A monitoring network may be coupled to the forwarding network. A controller may control switches in the monitoring network to forward network packets tapped from the forwarding network to one or more packet recorders. The packet recorders may store the tapped packets and the controller may query the stored packets at a later time. The controller may analyze queried packets to monitor the operation of the packet forwarding network and, if desired, to display graphical visualizations associated with the packet forwarding network. If desired, the controller may instruct the packet recorders to replay the tapped packets to network visibility tools through the monitoring network. The controller may coordinate storage and query operations across multiple packet recorders using the monitoring network so that the packet storage capacity and recording rate may be scaled up over time.

Described herein is a system and method for providing a network-visualization browser extension in an analytics environment. An analytic applications environment can be provided by, or otherwise operate at, a computer system providing access to a data warehouse, or data warehouse instance. The system is adapted for generating a network graph from analytic artifacts, including display of one or more dataflows as dataflow constellation visualizations that illustrates the dataflows and a lineage or other relationship information. The systems and methods disclosed herein can provide tools to provide insights for users of an analytics environment with regard to the users' analytic artifacts and relationships among the same.

The invention provides a GIS (Geographic Information System)-based optical cable and machine room association query processing method and a GIS-based optical cable and machine room association query processing system, and relates to obtaining geographic data of a target region through an OGC standard interface, generating a region unit with a unique identifier by using a grid division method and establishing an R-tree index to realize structured storage of a spatial relationship between an optical cable and a machine room. The system supports dual modes of area query and line query, wherein the area query obtains accurate data through space intersection calculation and tolerance band cutting, and the line query locates a fault section based on a topology database. The two embodiments respectively verify the application values in urban new district planning and long-distance optical cable fault positioning scenes, and compared with a traditional scheme, the efficiency is improved, and technical support is provided for communication network visual management and cost optimization.

The geological iterative matching technology based on machine learning assistance is characterized in that a convolutional neural network is used for capturing feature data of a geological image for extraction. Data cleaning standardization is carried out on the extracted data, so that the quality and consistency of the data are ensured, and the accuracy of a subsequent machine learning model is improved. A vector machine (SVM) learning algorithm is utilized to establish an association between the geological data and the model to match the geological model and the actual data. Iterative optimization processing is carried out by using a gradient descent method, and the accuracy and performance of the model are improved step by step. Finally, a neural network visualization algorithm is utilized, the geological data and the result of the model are presented in a visual and understandable mode, and the combination of the geological iteration matching technology based on the machine learning auxiliary algorithm technology helps experts in the geological field to better understand the geological data, recognize the geological mode and improve the geological performance. And optimizing the geologic model to match the actual data.

The present invention discloses a method for laying out an interpersonal social dynamic network based on node position constraints, which is characterized by including the following steps: Step S1, process the interpersonal social dynamic network data set and convert it into a continuous network graph G0, G1... G T ; Steps S2 to S3, for the network graphs G0, G1... G T , create initial positions; Step S4, add static constraints to all node pairs in all network graphs; Step S5, add node position constraints to non-new nodes in all network graphs; Step S6, iteratively obtain the resultant force of the constraints between nodes, move the nodes along the direction and magnitude of the force, and finally obtain the final positions of the nodes, completing the layout of the interpersonal social dynamic network. It solves the problems that the prior art cannot smoothly display the change trend of social groups in the interpersonal social dynamic network and cannot accurately display the change of social relationships of highly influential roles.

The invention discloses a zoo monitoring method and system based on lightweight multi-target tracking and self-adaption, and the method comprises the steps: setting a detector and a tracker, and carrying out the real-time multi-target detection and tracking in a zoo; light-weight trajectory prediction is carried out by using a light-weight gating cycle unit GRU network as a prediction model; constructing a real-time 3D semantic map containing a static environment and dynamic obstacles; an online Testtime-Training self-adaptive mechanism is introduced, so that continuous online self-adaptive learning of the model is realized; and setting an early warning rule, performing early warning on animal abnormal behaviors, and configuring a visual interface for real-time display. According to the scheme, the functions of multi-target tracking, trajectory prediction, 3D semantic map construction, abnormal behavior early warning (including electronic fence) and Web visualization are integrated, the application scene is wide, and deployment and maintenance are easy.

The invention discloses a supply chain network visualization method and system, electronic equipment and a storage medium, and the method comprises the steps: collecting node data and edge data of a supply chain network, and forming an initial real-time data flow; performing optimization processing on the initial real-time data stream, dynamically adjusting a data updating strategy to adapt to a data change rate and a system load, and outputting a structured data stream; mapping nodes and edges of the supply chain network into a three-dimensional space for real-time visual rendering based on a graphic hardware acceleration rendering technology and the structured data stream; adopting an intelligent layout algorithm based on a service scene to optimize the node space positions mapped into the three-dimensional space; and carrying out anomaly detection on the running states of the nodes and the edges of the supply chain, and carrying out visual prompt in a three-dimensional space. The basic defects of a traditional supply chain management system in the aspects of real-time performance, intuition and intelligence are thoroughly overcome, and the technical span from passive response to active management and control is achieved.

The present invention relates to the field of software technology, and specifically provides a Redis Web visualization client, which is a Redis visualization client adopting a BS architecture and consists of a front end, a back end, and a Redis client. The front end is separated from the back end, and the back end provides interfaces. When in use, the front end first inputs the Redis address, port, and password to connect to the Redis server. Compared with the prior art, the present invention can be accessed and used by anyone, providing another way for developers or operation and maintenance personnel to access Redis and making the operation more convenient.