82 results about "Multidimensional visualization" patented technology

The invention relates to the field of digital twinborn modeling, and discloses a digital twinborn visual modeling method and system based on a neural network, and the method comprises the steps: collecting the multi-dimensional perception data of a target physical system, carrying out the format unification and normalization processing of the original data of a sensor through a heterogeneous data fusion module, and obtaining a data fusion module; constructing a high-dimensional input feature set for neural network modeling by combining a structured embedding algorithm; carrying out stability pre-evaluation on the constructed input feature set, and screening core features by adopting a disturbance sensitivity analysis mechanism; a dynamic residual feedback mechanism is introduced to carry out enhanced training on the preliminary twin model, and modeling is carried out on the space-time dependency relationship of different components through a graph neural network; tracking a stability index of visual representation in real time in a model training process; and according to a multi-dimensional visualization result output by the final twin model, performing interpretation in combination with an industrial scene semantic rule base. The method has the advantage of improving the practicability of the twin model in the industrial scene.

A water pollution risk early warning and tracing method based on multi-source data fusion belongs to the technical field of water pollution monitoring and early warning, and comprises the following steps: step 1, constructing a multi-source heterogeneous data acquisition network and realizing real-time data transmission; 2, performing multi-source data fusion and feature enhancement processing based on space-time reference; 3, constructing a water pollution risk dynamic early warning system based on a WOA-LSSVM model; fourthly, reverse positioning of the pollution source is completed on the basis of a CNN-GRU-SE Attention model; and 5, carrying out development and emergency response on a multi-dimensional visual decision support system, and positioning a pollution source. Multi-source information such as water quality sensor data, unmanned aerial vehicle image data and geographic information data is fused, and an intelligent monitoring network is constructed; through multi-source data fusion and an intelligent algorithm, water pollution risk early warning accuracy and traceability efficiency are effectively improved, and the method has the advantages of high response speed, wide monitoring range, accurate positioning and the like, can be widely applied to the fields of urban water supply, drainage basin management and the like, and meets the requirements of water environment safety guarantee.

A system, method, and apparatus for displaying a fused reconstructed image with a multidimensional image are disclosed. An example imaging system receives a selection corresponding to a portion of a displayed multidimensional visualization of a surgical site. At the selected portion of the multidimensional visualization, the imaging system displays a portion of a three-dimensional image which corresponds to the selected multidimensional visualization such that the displayed portion of the at least one of the three-dimensional image or model is fused with the displayed multidimensional visualization.

The invention discloses a wind-solar complementary energy storage direct current charging method and system based on liquid cooling heat dissipation, and relates to the technical field of energy storage charging. Comprising the following steps: S1, collecting wind-solar complementary energy storage data in real time, and carrying out data preprocessing; s2, converting wind-solar power generation into direct current, judging the flow direction of wind-solar power generation energy, and performing corresponding wind-solar power generation energy transmission power supply; s3, judging the limit of the output power of the charging pile, and controlling and adjusting the output of the charging pile in stages; s4, quantifying the liquid cooling flow required by heat dissipation, and performing heat source heat dissipation on the energy storage system and the charging pile; and S5, carrying out coordinated regulation and control, strategy optimization and multi-dimensional visualization on the flow direction of wind and light power generation energy, charging pile output and heat source heat dissipation. The problems that an existing charging station is difficult to deploy in remote and power transmission difficult areas, high-power charging heat dissipation and energy efficiency bottlenecks are prominent, and the efficiency of traditional air cooling and alternating current conversion is low, so that efficient, safe and green energy supplementation is difficult to achieve are solved.

The invention provides a medical image visualization analysis system based on deep learning, and relates to the field of artificial intelligence. The objective of the invention is to overcome the defects of an existing system in the aspects of deep learning model interpretability, clinical interactivity and multi-modal data fusion. The system comprises an image data acquisition and standardization module, a deep feature extraction and representation learning module, a multi-task intelligent analysis module, an interpretability analysis module, a multi-dimensional visualization and interaction module, a clinical knowledge fusion and feedback learning module and a system management and integration module. Through the system, the diagnosis efficiency and accuracy can be improved, the trust of doctors is enhanced, the obstacle of a traditional black box model is overcome, and a new man-machine cooperation intelligent diagnosis normal form is constructed.

The invention discloses a historical observation and forecast fusion-based meteorological disaster risk estimation method and system, and belongs to the field of meteorological disaster risk assessment, and the method specifically comprises the steps: obtaining long-time series rainstorm observation data and rainstorm forecast data of a target region through a dual-thread data collection channel, and carrying out the preprocessing of the data, and then carrying out the prediction of the rainstorm observation data and the rainstorm forecast data; constructing a rainstorm disaster initial estimation model by using a machine learning algorithm; during a medium-and-long-term forecast effective period, according to a meteorological monitoring network layout and disaster sensitivity, setting a time interval, collecting and comparing rainstorm observation data and forecast data in real time, and once a deviation is found, immediately starting an intelligent fusion and dynamic correction algorithm to correct a pre-estimation result; and at the end period of forecasting, performing multi-dimensional visual output on the corrected rainstorm disaster estimation result, and generating a text report, thereby realizing dynamic optimization.

The invention discloses a power load time sequence anomaly detection method and system based on a Mama and LSTM hybrid network, and belongs to the technical field of power system data analysis and artificial intelligence, and the method comprises the steps: inputting the preprocessed power load and related factor time sequence data into a Mama-LSTM hybrid encoder; performing time sequence data reconstruction and anomaly probability prediction in parallel by using depth features output by an encoder, and performing model training by jointly optimizing reconstruction error loss and anomaly detection loss; calculating a comprehensive abnormal score based on the trained model, and judging an abnormal point by adopting a dynamic threshold value; and outputting an anomaly detection result and providing an analysis report containing an unsupervised evaluation index and multi-dimensional visualization. Through deep series fusion of Mama and LSTM, long-term dependence and complex modes in a power load sequence are effectively captured, and the accuracy, robustness and interpretability of anomaly detection are significantly improved in combination with a joint training strategy and an unsupervised evaluation system of the system.

Systems and methods are disclosed for multidimensional visualization of data and using the visualization in any of a number of applications to result in visualization configurations usable for a variety of purposes. The system includes one or more processors, one or more databases, at least one graphical user interface (GUI), and control technology for a user to control a display, where the display typically is visualizable through the GUI.

The invention discloses a natural resource asset checking management system and method based on a cross-platform architecture, and relates to the technical field of resource management, and the system comprises a cross-platform adaptive architecture module, a real-time data synchronization and verification module and an intelligent analysis and multi-dimensional visualization module. The cross-platform adaptive architecture module carries out fragmentation preprocessing on collected data through a uniform interface abstraction layer, a dynamic adaptation layer, a cross-platform rendering engine and a platform difference compensation mechanism and the real-time data synchronization and verification module, and the transmission efficiency is optimized through multi-link transmission and dynamic path selection. And the timeliness and accuracy of data synchronization are ensured in combination with block chain hash check and conflict detection. According to the system, through cross-platform adaptation, efficient data synchronization and intelligent visual analysis, the efficiency and scientificity of natural resource asset checking management are remarkably improved.

The invention relates to the technical field of data visualization, and provides an operation and maintenance data visualization method and system based on a smart power grid, which are used for improving the efficiency and the intelligent degree of power grid operation and maintenance visualization so as to improve the timeliness of power grid operation and maintenance decision management, and the method comprises the following steps: collecting a multi-source heterogeneous operation and maintenance data set in the smart power grid in real time; performing cross-modal cleaning and time alignment processing on the operation and maintenance data set to generate a preprocessed data set; executing dynamic feature fusion and correlation analysis on the preprocessed data set to generate an equipment state feature set and an equipment-environment interaction feature set; based on the equipment state feature set and the equipment-environment interaction feature set, generating an interactive visualization element set through a multi-dimensional visualization strategy; performing dynamic rendering and layout optimization on the interactive visual element set, and outputting a power grid operation and maintenance visual interface updated in real time; the power grid operation and maintenance visual interface is configured with a user operation priority response mechanism used for processing interaction conflicts.

The invention discloses a VR panoramic flood disaster analysis method and system combining a knowledge graph and a visual large model, belongs to the technical field of disaster information intelligent analysis, and particularly relates to technologies such as virtual reality panoramic images, knowledge graphs and visual large models. The method is suitable for automatic extraction, structured analysis and visual expression of disaster information in a flood scene, and solves the problems that in the prior art, a unified disaster information recognition rule is lacked, accurate extraction and spatial mapping of disaster parameters and scene objects are affected, and automatic recognition and dynamic labeling of flood disaster elements of VR panoramic images cannot be achieved. According to the method, a vertical vision large model of a flood disaster scene constrained by a knowledge graph is constructed and trained; and performing automatic identification and risk labeling on disaster information in the preprocessed VR panoramic image based on the trained vertical vision large model, and performing multi-dimensional visualization after labeling. The method is used for VR panoramic flood disaster analysis.

The invention discloses an old building health evaluation method based on an optimization order priority method. The method specifically comprises the steps of S1, constructing a multi-dimensional old building health evaluation index system and a building health level; s2, data acquisition and preprocessing; s3, calculating a correction factor by using a Pearson's correlation coefficient, dynamically adjusting index weight sorting, and constructing an OPA-C mathematical model; s4, solving the mathematical model; and S5, carrying out model self-updating on the real-time data of the old building. By constructing a multi-dimensional evaluation index system of first-level indexes and second-level indexes, on the basis of a traditional order priority method, the importance order of the first-level indexes is adjusted through Pearson's correlation coefficients, index weight distribution of the traditional order priority method is optimized, the scientificity and accuracy of evaluation are improved, and the evaluation efficiency is improved. The method supports BIM system integration and multi-dimensional visual analysis, provides a scientific quantitative basis for old building reconstruction, city updating and low-carbon transformation, and has remarkable engineering practicability and social benefits.

The invention discloses an RAG and knowledge graph question-answering method and system for security classification and grading of cross-border data, and belongs to the crossing field of big data security management, artificial intelligence and compliance technologies. The method comprises the following steps: step S101, receiving and preprocessing user input; step S102, performing question analysis and semantic intention recognition; step S103, intelligent scheduling control decision making; step S104, reasoning and executing the knowledge graph; step S105, performing RAG generation reasoning execution; step S106, performing intelligent fusion and decision traceability; step S107, carrying out multi-dimensional visual display; step S108, audit record and report generation; and S109, updating the dynamic knowledge. The method has the advantages of intelligent question and answer, multi-source fusion, sustainable evolution, traceability of the whole process and the like, and can be widely applied to compliance management and intelligent decision-making scenes related to data cross-border flow, such as enterprises, governments, finance, medical treatment and the like.

The invention relates to the technical field of building intelligent management and operation control, and discloses a solid building data visualization and simulation analysis system, which is characterized in that dynamic monitoring data is acquired by constructing a building three-dimensional model and deploying multiple types of sensors, and a tensor structure is generated through standardization and three-dimensional index fusion; mapping the tensor into a three-dimensional model to realize regional data visualization; historical sequence modeling and strategy-driven future simulation prediction are carried out based on a sliding window; a user can control system behaviors through model interaction, the system automatically monitors index changes and triggers strategy simulation and visual dynamic updating in a linkage mode, and visual analysis and intelligent response control of the building state are achieved. Through fusion of three-dimensional model mapping, tensor construction and strategy response prediction, building state multi-dimensional visualization, continuous intelligent prediction and dynamic feedback control are realized, and innovative technologies such as sliding window modeling and interactive strategy driving are provided.

The invention relates to the technical field of distributed electric energy, in particular to a distributed electric energy electricity consumption summary settlement system, which comprises an electricity consumption data acquisition module, a multi-source heterogeneous data processing module, a dynamic verification module, a cross-regional settlement module, a block chain evidence storage module and a visual interaction module. By configuring a multi-channel acquisition circuit, parallel acquisition of power utilization characteristic data of distributed energy nodes is realized; performing cross-protocol fusion and noise reduction on the received data, and endowing credibility weight; finishing verification of timestamp precision + / -1ms by using a block chain intelligent contract mechanism; dynamically adjusting settlement parameters according to the verification weight, and generating a dynamic settlement list in combination with an electricity price gradient model; hash evidence storage is carried out through the alliance chain node, finally, multi-dimensional visual rendering is completed in combination with an evidence storage result, and a traceable and auditing settlement report is generated. The system has the advantages of data fusion intelligence, settlement result credibility, account book record compliance and report interaction transparency.

The invention relates to an electric power resource adjustability resource multi-dimensional analysis and visualization method, which comprises the following steps of: selecting four dimensions of response time, service time, adjustable capacity and credibility in electric power resource adjustability characteristic indexes as a rating system, and drawing an electric power adjustability resource adjustability characteristic radar map; and constructing a power adjustable resource characteristic cube by taking the power adjustable resource adjustment characteristic radar map as a bottom surface and taking the corresponding scale capacity as a high surface to represent the adjustable characteristic characteristics of the source network load power resources. Compared with the prior art, the multi-dimensional visualization of the adjustment performance of the power adjustable resource is realized by constructing the characteristic cube, the adjustable characteristic characteristics of the source network load power resource can be comprehensively and accurately represented, and a large number of, multiple and dispersed flexible resources can be aggregated to participate in system adjustment.

Systems and methods are disclosed for multidimensional visualization of data and using the visualization in any of a number of applications to result in visualization configurations usable for a variety of purposes. The system includes one or more processors, one or more databases, at least one graphical user interface (GUI), and control technology for a user to control a display, where the display typically is visualizable through the GUI.

A method and a system for online integrated environmental monitoring, assessment, and impact visualization of projects are disclosed. The method includes receiving project site data representing the geographical boundary of a project in a virtual environment and collecting real-world environmental data from fixed and mobile monitoring devices. Model data, modeling parameters, and digital ground data associated with the project are retrieved and unified through a unified connector interface to form a unified input data. The unified input data is processed through one or more impact modeling entities to assess environmental impacts, including air quality, noise, water quality, and ecological effects. Visualizations of the environmental impact determined are transmitted to an environmental assessment planner interface for display. The method and the system provide for real-time integration, efficient impact modeling, and multi-dimensional visualization, enabling stakeholders to evaluate and monitor environmental effects with enhanced precision and accessibility in a seamless digital environment.

The invention relates to the field of intelligent data management and analysis, in particular to a multi-dimensional data integrated work file tracing method and system. The method comprises the following steps: acquiring work file data; extracting a first archive feature, a second archive feature and a third archive feature; obtaining a tracing path and a confidence score; judging a first-level condition, a second-level condition and a third-level condition; and in combination with an improved space-time coupling multi-dimensional visualization technology, starting a tracing optimization process, and realizing tracing of the work file. According to the method, through multi-source data fusion and feature extraction, entity association, time sequence abnormity and dynamic risks are accurately quantified; by constructing a multi-dimensional model for comprehensively evaluating the reliability of a tracing path and combining a three-level intelligent judgment and self-adaptive optimization mechanism, the accuracy and the service fitting degree of a tracing result are remarkably improved; through visual presentation and knowledge precipitation, full-link intelligent tracing of the work file is realized, and efficient decision support is provided for safety audit and risk management and control.

The invention relates to the technical field of intelligent investment advisers, and discloses an intelligent investment adviser interaction and asset allocation visual decision-making system based on augmented reality, and the system comprises an augmented reality display device; the user interaction module is used for capturing an input instruction of a user; a data acquisition module; intelligent investment advisor and commissioning; a visualization processing unit; a decision execution module; a system control center; a user identity authentication module; a data storage module; a network communication module; and a calculation acceleration module. According to the intelligent investment adviser interaction and asset allocation visual decision-making system based on augmented reality, by integrating augmented reality display equipment and a multi-dimensional visual processing unit, an abstract asset allocation scheme, a market trend and risk information are overlaid in a real environment in visual forms such as a three-dimensional hologram and a spectrogram; the understanding efficiency and decision immersion of the user on the complex financial data are remarkably improved, and the problems that traditional two-dimensional interface information is not visual in presentation and poor in interaction experience are solved.

The invention discloses a Python-based power transmission line electromagnetic field finite element automatic modeling and analysis method in the field of electromagnetic field finite element simulation and power system analysis. A Python script language is combined with a finite element calculation engine, information is analyzed through programming, and the precise spatial position of each hanging point of the power transmission line in a global coordinate system is obtained through automatic conversion of coordinates; based on the obtained parameters, script programming is used for completing three-dimensional geometric modeling of the wire, and then automatic modeling and parameterized definition are achieved; then, script programming is used for achieving calculation domain setting, boundary condition setting, voltage and current giving, phase sequence setting and other setting of a line section to be calculated, and three-dimensional finite element simulation calculation of an alternating current electric field and a magnetic field of the designated line section is completed; and performing multi-dimensional visual display on the electric field and magnetic induction intensity in combination with a Python visual library. According to the system, automatic processing from GIM data to an electromagnetic field calculation result is achieved, electromagnetic field calculation of complex lines such as mixed voltage and cross crossing can be completed, modeling efficiency and calculation precision are remarkably improved, and an efficient simulation means is provided for electromagnetic environment evaluation and equipment optimization arrangement of the power transmission line.

This invention discloses a DC charging method and system for wind-solar hybrid energy storage based on liquid cooling, relating to the field of energy storage charging technology. It includes the following steps: S1, real-time acquisition of wind-solar hybrid energy storage data and data preprocessing; S2, conversion of wind and solar power into DC power, determination of the energy flow direction, and corresponding energy transmission and power supply; S3, determination of the charging pile's output power limit, and phased control and adjustment of the charging pile's output; S4, quantification of the liquid cooling flow required for heat dissipation, providing heat source cooling for the energy storage system and charging pile; S5, coordinated control, strategy optimization, and multi-dimensional visualization of the wind and solar energy flow direction, charging pile output, and heat source cooling. This solves the problems of difficult deployment of existing charging stations in remote and power transmission-difficult areas, prominent bottlenecks in heat dissipation and energy efficiency for high-power charging, and low efficiency of traditional wind cooling and AC conversion, which hinder efficient, safe, and green energy replenishment.

The application discloses a data simulation method based on data visualization, and relates to the technical field of data analysis, comprising: constructing a distributed stream processing framework, performing parallel preprocessing on a target data set to be simulated to generate a time sequence characteristic stream; converting the time sequence characteristic stream into a multi-dimensional visualization model through an adaptive mapping layer, and realizing dynamic rendering in a visualization interface; triggering a simulation engine to execute real-time simulation based on the multi-dimensional visualization model, and jointly optimizing the visualization parameters and the simulation parameters through a feedback optimization mechanism. Through the introduction of a dynamic calculation method of the job level correlation coefficient and the space-time overlap degree, the design of the time-varying adjustment factor and the hierarchical attention mechanism, and the construction of a novel data processing and visualization framework, the application realizes the accurate identification of the talent development path across different levels, the timeliness optimization of data preprocessing, and the effective sharing of the best practices among departments.

The invention relates to the technical field of building energy consumption monitoring, and discloses an industrial building operation stage energy consumption monitoring system and method.The system comprises a data acquisition layer, a data processing and storage layer, an energy consumption analysis layer and an application layer which are electrically connected in sequence; the data acquisition layer acquires total energy consumption, environmental parameters and production activity data, the processing layer realizes data cleaning, quality closed-loop management and space-time alignment storage, the analysis layer constructs a dynamic energy consumption reference model containing an equipment aging coefficient, calculates a two-dimensional production intensity coefficient, completes energy consumption double-layer decomposition and normalized energy efficiency evaluation, and performs energy consumption analysis and energy efficiency evaluation. The application layer realizes multi-dimensional visualization, intelligent report generation and graded alarm. The method is executed according to the steps of data acquisition, processing, modeling, coefficient calculation, energy consumption decomposition, energy efficiency evaluation and application display. According to the method, the problems of energy consumption and production coupling deficiency, reference static state and the like are solved, objective energy efficiency evaluation and accurate energy consumption positioning are realized, and support is provided for industrial building energy saving.

Systems and methods are described for generating an immersive experience for designing a physical space using multi-dimensional visualizations and sharing the design process in real-time. A system may system may identify a user and access a project associated with the user. The system may identify an input token placed on a touchscreen of an interaction device and a stored object associated with the input token. The system may access information about and a visual representation of the stored object. The system may generate, for display via the touchscreen, a two-dimensional view of the physical space and / or the information about the stored object. The system may generate a three-dimensional view of the physical space that includes the visual representation of the stored object. The system may transmit the three-dimensional view for display via one or more display devices that are independently housed from the interaction device.

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

The invention discloses a vehicle track perception and analysis system based on MR data of vehicle-mounted communication equipment, which comprises a data processing module and a visual display module, and is characterized in that the data processing module is used for access, analysis, analysis and track generation of the MR data of the vehicle-mounted communication equipment; the visual display module is used for multi-dimensional visual display of the vehicle track and the network quality, and the data processing module and the visual display module work cooperatively to realize high-precision perception of the vehicle track and deep analysis of the network quality; the data processing module comprises an MR data access unit, an MR cleaning and latitude and longitude backfilling unit, a vehicle state identification unit, a track smoothing and denoising processing unit, a road adsorption and track generation unit and an output structured track unit, and has the capabilities of high-precision track restoration, network quality fusion display and intelligent segmentation identification; the method can effectively support fault positioning and user experience analysis in the operation and maintenance scene of the Internet of Vehicles, and has the advantages of high automation degree, high positioning precision, friendly visual interaction and the like.

The invention relates to the technical field of data analysis, in particular to a logistics navigation method and device for catering businesses, and the method comprises the steps: analyzing the identification information, submitted by logistics personnel, of meal delivery customers, and extracting the attribute features of the meal delivery customers from the identification information; according to the attribute characteristics of the meal delivery customers, positioning node paths associated with the meal delivery customers to generate meal delivery sequence chains in the node paths, allocating weight values to the meal delivery sequence chains, and generating a weighted meal delivery sequence chain list; calculating navigation route time consumption of meal delivery sequence chains in the weighted meal delivery sequence chain list, identifying potential route accident points by using an anomaly detection algorithm, and generating a navigation route report containing a navigation route time consumption result and the route accident points; and drawing a comprehensive navigation route map by using a multi-dimensional visualization algorithm to obtain a navigation route view, and generating a navigation route relieving strategy.

The invention discloses an artificial intelligence-based natural disaster damage intelligent assessment method and system. The method comprises the following steps of: acquiring a restoration period image and a disaster sensitive factor through a satellite remote sensing technology; performing land utilization type intelligent interpretation and generating a grid map layer, and automatically extracting geological disaster stress factors at the same time; innovatively coupling an InVEST ecological environment quality evaluation model and an AI disaster loss evaluation engine, synchronously calculating an ecological environment quality index and a disaster loss risk index, and generating an ecological quality thermodynamic diagram and a disaster sensitivity dynamic map; analyzing an evolvement rule of an ecological quality spatial pattern by adopting a space-time diagram convolutional network, and quantifying a synergistic effect in combination with a natural disaster damage degree-disaster resistance incidence matrix; and finally, multi-dimensional visual deduction of the natural disaster damage degree and the disaster resistance capability is realized on a three-dimensional digital twinborn platform, and an ecological restoration-disaster toughness double-target intelligent evaluation closed loop is formed.

A system, method, and apparatus for guiding an astigmatism correction procedure on an eye of a patient are disclosed. An example apparatus includes a photosensor configured to record a pre-operative still image of an ocular target surgical site of the patient. The apparatus also includes a real-time, multidimensional visualization module configured to produce a real-time multidimensional visualization of the ocular target surgical site during an astigmatism correction procedure. The apparatus further includes a data processor configured to determine a virtual indicium that includes data for guiding the astigmatism correction procedure. The data processor uses the pre-operative still image to align the virtual indicium with the multidimensional visualization such that the virtual indicium is rotationally accurate. The data processor then displays the multidimensional visualization of the ocular target surgical site in conjunction with the virtual indicium.