1018 results about "Three dimensional visualization" patented technology

The invention discloses an urban green land carbon sink dynamic accounting method and system based on multi-source data fusion and spatial network modeling. The method comprises the following steps: collecting urban green space carbon sink original data and preprocessing the data, and constructing a space * time * feature structure carbon sink data cube; identifying green land source plaques based on the spatial dimension data; taking the source ground plaque as an initial node, constructing a resistance surface by using a dynamic resistance factor, simulating a carbon flow in combination with a circuit theory, and generating a carbon flow gallery and a carbon flow density grid; inputting multi-source data into the carbon density dynamic calibration model, and outputting a dynamic grid; constructing a multi-scale prediction engine, and outputting carbon density prediction results under different time scales; and combining GIS and BIM technologies, inputting a prediction result and an urban space structure into a three-dimensional visual platform, generating a carbon density thermodynamic diagram and a carbon flow gallery evolution diagram, and realizing carbon sink dynamic accounting. According to the invention, the precision and space-time continuity of carbon sink accounting can be obviously improved.

The invention relates to the field of measurement, in particular to a subway tunnel secondary lining section limit measurement method based on SLAM mobile scanning, which comprises the following steps: step 1, tunnel point cloud acquisition and target clustering point cloud acquisition; step 2, CPIII control point coordinate extraction; step 3, point cloud coordinate conversion; 4, performing point cloud processing, and removing noisy points and non-secondary-lining target point cloud data in the tunnel secondary-lining point cloud; and step 5, performing three-dimensional limit deviation analysis, performing spatial comparative analysis on the point cloud under the construction coordinate system and the subway secondary lining tunnel design three-dimensional model by adopting a voxelization deviation mapping algorithm, extracting a continuous deviation region through voxel clustering, and generating a three-dimensional deviation thermodynamic diagram. According to the method, the two-lining tunnel point cloud obtained by SLAM mobile scanning is accurately converted into a construction coordinate system by combining CPIII high-precision control points in the tunnel, rapid, visual and three-dimensional contrastive analysis with design of a three-dimensional model can be achieved, and visual and reliable data support is provided for line and slope adjustment, track laying and defect improvement.

The invention relates to the technical field of data processing, in particular to a multi-source data fusion side slope safety monitoring method, which comprises the following steps: acquiring a side slope surface three-dimensional model generated by three-dimensional laser scanning and a two-dimensional radar deformation cloud picture acquired by a side slope radar; extracting a cloud picture space feature vector through an encoder of the self-supervised deep learning model, and outputting three-dimensional heat map coordinate data through a decoder; screening topographic feature points of slope shoulders, scarps and crack areas from the vertexes of the triangular mesh based on a topographic curvature threshold; matching the three-dimensional heat map feature points with topographic feature points, and mapping to a three-dimensional model coordinate system through affine transformation to generate a dynamic three-dimensional deformation heat map with a timestamp; comparing each timestamp displacement value to calculate a displacement variation; and marking a displacement over-limit region on the three-dimensional model by using a color gradient and outputting a three-dimensional visualization result. According to the method, mapping from the two-dimensional deformation data to the three-dimensional space is realized, the positioning fuzziness of an existing two-dimensional cloud picture is eliminated, and the slope deformation position identification precision is improved.

The invention relates to the technical field of digital engineering, and particularly provides a BIM-based engineering construction dynamic three-dimensional visual management method and system, and the method comprises the steps: collecting construction multi-dimensional data, carrying out the correlation mapping with an initial BIM model component after preprocessing, and forming a structured construction element data set; dynamically reconstructing an initial BIM model based on the data set, generating a three-dimensional dynamic twinborn body, and dynamically displaying information such as superposition progress, quality, resources and environment; a prediction analysis model is called to generate progress prediction, quality early warning and resource optimization suggestions, and a final scheme is determined after visual simulation verification; and updating the data set and the twin according to an execution result, and iteratively optimizing the prediction model. According to the scheme, dynamic integration and visual management of construction total elements are achieved, the timeliness, accuracy and intelligent level of construction management are effectively improved through intelligent prediction and closed-loop optimization, the construction efficiency is improved, and the management cost is reduced.

The invention provides a coal mine operation and maintenance monitoring method and device, electronic equipment and a storage medium. Environmental parameters and equipment state data are collected in real time through the Internet of all things deployed in an underground coal mine; preprocessing the environment parameters and the equipment state data by utilizing an edge computing node; the method comprises the following steps: acquiring point cloud data and a multi-view image of an underground coal mine, and splicing the point cloud data and the multi-view image to construct a three-dimensional scene model; the preprocessed data and the three-dimensional scene model are dynamically fused, and the equipment state features, the environment features and the risk early warning parameters are displayed in the three-dimensional scene model in a three-dimensional visualization mode in an overlapping mode; under the abnormal condition, abnormal data are received, maintenance steps or fault points are marked in a virtual interface of the monitoring center, data islands are broken, and multi-source data are deeply fused; and real-time guidance can be provided through interaction in modes of gestures, voice and the like, so that the maintenance efficiency is improved.

The invention relates to the technical field of electronic detection, and discloses an electronic component dispensing detection method. The method comprises the following steps: acquiring dispensing image data of the surface of the electronic component, and generating a standardized dispensing data matrix containing glue position, thickness and uniformity characteristics through standardized preprocessing; constructing a dispensing correction matrix based on an adaptive window frame, and performing spatial reference dynamic correction on the standardized data matrix to obtain a spatial correction dispensing data matrix; inputting the data into a multi-layer sensor fusion network for feature fusion, and outputting a multi-source fusion dispensing data set; constructing a multi-dimensional abnormal feature incidence matrix based on the data set, and identifying abnormal dispensing data nodes by using a dynamic threshold detection algorithm; performing parameter optimization iteration on the multi-source fusion data set by using a gradient descent optimization algorithm to generate an optimized dispensing parameter set; and finally, constructing a three-dimensional visual dispensing quality model, and establishing a dynamic mapping relationship between model parameters and glue physical characteristics. The method can more comprehensively detect the glue quality.

The embodiment of the invention discloses a mineral resource exploration data analysis method and device based on three-dimensional space modeling. The method comprises the steps that back-flushing pushing-covering structure feature information is extracted through structure interface occurrence measurement, lithology combination analysis and structure movement trace recognition and converted into geologic structure feature parameters; stratigraphic age data and lithology distribution information are integrated, and a three-dimensional stratigraphic model is constructed with a stratigraphic superposition relation as a constraint; geophysical data are imported to extract geophysical response characteristics of stratums with different depths, and lithologic boundary correction is combined to obtain deep fracture characteristic parameters; sedimentary system division is carried out on lithofacies paleogeographic information, and deep fracture characteristic parameters are fused to establish a fracture system three-dimensional model; the multi-feature association relationship is identified, the ore body prediction model is established, the spatial data is input to obtain the three-dimensional visual prediction result of the hidden ore body spatial distribution, and the exploration efficiency and accuracy in the deep phosphorite exploration process are improved.

The invention relates to the technical field of data processing, in particular to an integrated multi-mode culture resource intelligent data governance and management system. The system comprises a data acquisition module, an intelligent processing module, a data management module, a knowledge organization module and an interactive display module. Synchronous acquisition of videos, audios, images and three-dimensional point clouds is realized through camera equipment, audio acquisition equipment and a laser scanner, and cultural elements are extracted through action recognition, speech recognition model processing dialect transcription, image semantic segmentation and named entity recognition by adopting a convolutional neural network. The system realizes structured description and semantic mapping of data on the basis of non-abandoned domain ontology, and constructs a knowledge graph by means of a graph database and a graph neural network. And finally, realizing three-dimensional visual display of the cultural resources by combining a virtual reality technology. According to the method, the problems of non-abandoned multi-modal data processing splitting, insufficient semantic organization and weak display interactivity in the prior art are solved, and the digital governance level and the propagation capability of cultural resources are improved.

The invention belongs to the technical field of intelligent engineering management, and discloses an automatic monitoring and control method of an engineering management system based on the Internet of Things. According to the method, a four-layer Internet of Things architecture comprising a sensing layer, a network layer, a platform layer and an application layer is constructed, and the four-layer Internet of Things architecture is uploaded to a cloud platform through a 5G / narrowband Internet of Things dual-mode transmission channel. A digital twinborn technology is innovatively adopted to construct a three-dimensional visual engineering model, intelligent identification and prediction of abnormal working conditions are realized through a machine learning algorithm, and a multi-stage linkage control mechanism is established. And when construction deviation or equipment failure is detected, the system automatically generates an optimization control strategy and issues the optimization control strategy to the execution terminal, so that accurate regulation and control of the construction machinery and intelligent pushing of early warning information are realized. According to the method, a manual inspection mode of traditional engineering management is broken through, full-process automatic supervision is realized through data fusion analysis and closed-loop control, the construction quality supervision precision is effectively improved by more than 30%, the safety accident rate is reduced by 50%, and the engineering management efficiency is remarkably improved.

The invention relates to the technical field of nondestructive testing, and discloses a bimetal composite pipe three-dimensional reconstruction method and system based on multi-source data fusion. The method comprises the following steps: acquiring magnetic flux leakage signals and thickness data of the bimetal composite pipe in a high-pressure environment, and preprocessing the magnetic flux leakage signals and the thickness data to obtain a clean multi-source signal data set; performing time domain and frequency domain feature alignment on the data set to generate a fusion data matrix; extracting a preliminary defect feature set through multi-layer convolution processing; performing classification training on the defect features to obtain a defect type classification result containing confidence scores; if the crack exists, depth fitting is carried out to quantify the crack depth; if the preset risk threshold value is exceeded, generating a three-dimensional defect distribution model and evaluating connectivity; and finally, outputting a quantitative evaluation report of the pipeline risk level. According to the method, efficient fusion of multi-source data, intelligent identification of defect types and three-dimensional visual reconstruction are realized, and the accuracy and evaluation efficiency of pipeline defect detection are remarkably improved.

The invention relates to the technical field of ocean engineering digital twinning and three-dimensional visualization, and provides a method and system for generating dredging terrain twinning based on a right-angle triangular mesh, and the method comprises the steps: obtaining regular grid elevation unified to an engineering plane coordinate system or preprocessed sampling height data, determining a covered space range, reading the space range and density parameters, and calculating the total row number and the total column number of the grids based on the space range and the density parameters; generating regularly arranged vertexes in the covered space, and constructing a topological structure of an isosceles right triangle grid; dividing the global grid into a plurality of Chunk blocks according to a fixed size by taking a vertex as a unit, establishing a triangular index mapping relationship between global rows and columns and the Chunk blocks, filling three vertexes of an isosceles right triangle and elevation / height data in each Chunk block in parallel, and generating local VBO, IBO and AABB; and performing batch rendering and coloring according to a height color table on all Chunk blocks to realize visualization of the terrain.

The invention provides a bridge structure damage monitoring method and system based on multi-modal data fusion in the technical field of bridge structure damage monitoring. The method comprises the steps that S1, a server obtains a large amount of historical bridge monitoring data and emergency simulation data and inputs the historical bridge monitoring data and the emergency simulation data into a finite element model; s2, performing structural mechanical simulation on the finite element model to obtain bridge structure damage simulation data, and labeling historical bridge monitoring data through the bridge structure damage simulation data and the emergency simulation data to construct a data set; s3, training the bridge structure damage identification model through the data set; s4, the server collects real-time bridge monitoring data and inputs the real-time bridge monitoring data into the bridge structure damage recognition model, and a bridge structure damage recognition result is obtained; and S5, mapping the real-time bridge monitoring data and the bridge structure damage identification result to the BI model, and outputting a three-dimensional visualization report. The method has the advantages that the accuracy and the real-time performance of bridge structure damage monitoring are greatly improved.

The invention provides an airspace simulation deduction method and system based on digital twinning, and belongs to the technical field of airspace simulation, and the method comprises the steps: integrating geographic bottom plate data and airspace element data, carrying out the meshing based on an airspace grid engine, and constructing an airspace digital twinning model; receiving at least one flight plan, and mapping the flight plan to the airspace digital twin model to generate a corresponding simulation aircraft entity; based on a preset simulation engine, driving the simulation aircraft entity to perform flight simulation in the airspace digital twin model, and calculating a simulation flight situation; in the simulation process, airspace conflict detection and early warning are carried out based on the simulation flight situation and the airspace digital twin model; and outputting a simulation deduction result, performing three-dimensional visual output on the simulation flight situation data and the early warning information, and generating an analysis report including conflict statistics and airspace evaluation. The airspace resource allocation is optimized, the flight safety is improved, and intelligent and efficient management is realized.

The invention discloses a die temperature field coordinated regulation and control method based on digital twinning, and relates to the technical field of die temperature control. The method comprises the following steps: constructing a mold temperature field digital twin model covering macroscopic, mesoscopic and microscopic scales; a distributed optical fiber temperature sensor is deployed to realize continuous temperature field sensing; physical-digital real-time synchronous mapping is established through ensemble Kalman filtering; performing model prediction control based on the digital twinborn body; three-dimensional visualization and multi-modal man-machine interaction of the temperature field are realized by adopting an augmented reality technology; and reinforcement learning is used to enable the digital twinborn body to have an autonomous optimization capability. Through deep fusion of a physical space and a digital space, precise sensing, real-time mapping and intelligent control of a mold temperature field are realized, and the temperature control precision and the self-adaptive capability of the system are remarkably improved.

The invention relates to a land space planning and surveying and mapping engineering collaborative measurement method, which comprises the following steps: collecting multi-source surveying and mapping data of a target area, and constructing a live-action three-dimensional semantic model bearing ground feature semantics through fusion processing; key planning elements are extracted based on the model, the spatial relation of the key planning elements is quantified, and a spatial relation graph with geometric entities as nodes and the spatial relation as edges is generated; the planning management and control terms are formalized into computable logic assertions, and a machine executable planning rule base is constructed; performing collaborative traversal and logical reasoning on the spatial relation graph based on the rule base, automatically comparing and identifying violation situations, and generating a planning conflict report; and carrying out fusion mapping on the report and the three-dimensional model to generate a three-dimensional visual review layer for intuitively indicating the position, type and degree of the violation. According to the method, deep fusion of surveying and mapping data and planning rules is realized, planning conformity review can be automatically and intelligently completed, and the problems that the prior art depends on manpower, and is low in efficiency and different in standard are effectively solved.

The invention relates to the technical field of big data analysis, and discloses a prospecting target area positioning method and system based on big data, and the method comprises the steps: collecting multi-source exploration data in real time through distributed nodes, completing coordinate normalization, semantic alignment and time synchronization through a spatial heterogeneous data flow engine, and generating a standardized incremental data block; performing local feature sensitivity analysis based on the historical model library, identifying a newly added feature dimension, and performing parameter increment updating by adopting a sliding window gradient descent method; inputting the updated model into a target evolution model driven by a Bayesian space-time probability field, and dynamically calculating the metallogenic probability of each space grid in combination with a stress field, an element migration path and historical verification data; and generating high, medium and low three-level target area maps according to probability sorting, and pushing the high, medium and low three-level target area maps to a three-dimensional visual decision terminal. According to the method, minute-level dynamic response of the target region under triggering of newly-added data is realized, computing resource consumption is reduced to be less than 5% of that of an original system, and prospecting efficiency and abnormal region identification timeliness are improved.

The invention belongs to the technical field of geological engineering monitoring and multi-physics field intelligent sensing, and discloses a separation grouting slurry migration monitoring method and system, and the method comprises the steps: constructing an acoustics-optics-electricity-electromagnetism multi-physics field coupling monitoring system; a grouting hole and a monitoring drilling hole array are arranged in a target stratum, a distributed optical fiber sensor, a drilling hole ultrasonic imager, a resistivity measuring device and a transient electromagnetic detection device are installed, and a three-dimensional monitoring network is formed; synchronously acquiring sound field, light field, electric field and magnetic field data; four-field monitoring data and overlying strata multi-parameter observation data are fused, a coal seam mining three-dimensional overlying strata separation model is constructed, and a slurry diffusion three-dimensional visualization model is generated through numerical simulation; and based on the four-field monitoring response difference of the separation space before and after grouting, in combination with a monitoring frequency domain correction model of multiple indexes of grout diffusion, the diffusion range, compactness and filling effect of the grouting grout are evaluated, and abnormal early warning is triggered.

The invention provides a three-dimensional visualization analysis method for a real scene of an ancient earthquake exploring groove, which belongs to the technical field of seismic geological survey and comprises a data acquisition module used for acquiring point cloud data of target exploring grooves in different regions. And the model building module is used for carrying out scene format conversion on the point cloud data of the target exploring grooves in different regions, and carrying out exploring groove three-dimensional model building by utilizing the converted SLPK file. And the visualization module is used for carrying out live-action three-dimensional display on the three-dimensional models of the target probe grooves in different regions through a three-dimensional scene Web server based on the SLPK files in different regions, and rendering node data of different detail levels of the probe grooves according to user requirements. The ancient earthquake event can be better understood, and a reliable three-dimensional digital file and a new shared analysis normal form are provided for the ancient earthquake.

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

The invention discloses an electric power cross-operation dynamic risk prediction and early warning method, system, equipment and medium based on multi-modal data fusion, and relates to the technical field of intelligent electric power systems, and the method comprises the steps: collecting multi-source data of a cross-operation site in real time, including personnel spatial position data, equipment state data, environmental parameters and operation flow information; performing multi-modal fusion processing on the multi-source data, and constructing space-time risk association features; constructing a dynamic risk factor matrix, performing fusion calculation on the static risk reference value and the dynamic correction value, and dynamically updating the weight of each factor along with time; predicting a risk change trend based on the combination of a time sequence prediction model and a graph structure modeling method; and generating a three-dimensional visual risk thermodynamic diagram based on a prediction result, and triggering a multi-level early warning mechanism when a risk value exceeds a threshold value. The image is reconstructed through multi-modal fusion processing, and key edge features can be recovered in complex environments such as low illumination, high dynamic range and fast motion.

The application discloses a smart community management service system, and particularly relates to the field of service management, comprising a perception layer module, a communication layer module, a data processing layer module and an application layer module; the application realizes global intelligent management through the collaborative architecture of the perception layer module, the communication layer module, the data processing layer module and the application layer module; the perception layer is deployed with multi-source heterogeneous sensors, and data preprocessing is conducted in combination with edge computing; the communication layer adopts multi-protocol fusion transmission, supports 5G+NB-IoT dual-channel redundancy and end-to-end encryption; the data processing layer is based on a cloud-edge collaborative architecture, uses Kalman filtering denoising, D-S evidence theory fusion conflict information, LSTM-Attention prediction device failure, and constructs a digital twin simulation optimization energy consumption; the application layer provides a three-dimensional visual management and control platform, integrates security linkage, air conditioner group control strategy driven by reinforcement learning and convenient service scheduling, and supports cross-platform access and RBAC permission management.

The invention discloses a heart image processing method and device, a storage medium and computer equipment, and relates to the technical field of nuclear medicine image processing and quantitative analysis. The method comprises the steps that a heart image to be processed is acquired, four cavities of the heart image are segmented based on a pre-trained segmentation model, segmentation masks are obtained, and the heart image is a CT image or an MR image; aligning the heart image into a PET space, so that the segmentation mask is mapped to a PET image corresponding to the heart image, and a PET segmentation image is obtained; and cutting the PET segmented image based on the segmentation mask to obtain a PET target anatomical region, and performing three-dimensional rendering on the PET target anatomical region to obtain a dynamic rendered image of tracer agent distribution. According to the method, the segmentation precision of the myocardial subregion can be improved, and the three-dimensional visualization effect of the heart image and the processing efficiency of the heart image are improved.

The invention provides a coal face mining auxiliary method based on visual and point cloud data fusion modeling, and the method comprises the steps: collecting the visual image data of a coal face, collecting the three-dimensional point cloud data through a point cloud sensor, and obtaining the motion state information through an inertial sensor; based on internal and external parameters and IMU data of joint calibration, mapping point cloud data to an image plane, establishing a geometric mapping relationship between three-dimensional points and pixels, generating an attribute point cloud model containing geometry, color and semantics, and generating a high-precision global three-dimensional digital twinning model; and identifying and tracking equipment instances in the digital twinborn model, and resolving motion parameters of key components based on a URDF kinematics model and a principal component analysis algorithm to support remote control decisions. According to the invention, high-precision real-time sensing and three-dimensional visualization of the working space size, the equipment connection relation and the movement position of the coal face can be realized, and the remote control precision and the response efficiency of unmanned mining are remarkably improved.

The invention discloses a side slope anchor rod grouting amount three-dimensional visual monitoring method, and relates to the technical field of anchor rod grouting quality monitoring, and the method comprises the steps: collecting real-time grouting parameter data based on a grouting parameter sensor arranged in a side slope anchor rod construction area; the method comprises the following steps: constructing a three-dimensional geometric model of a side slope anchor rod, generating three-dimensional grouting amount distribution data, and generating a real-time dynamic side slope anchor rod grouting amount three-dimensional visual monitoring image by adopting a three-dimensional visual rendering technology; based on a trained image anomaly judgment model, analyzing the three-dimensional visual monitoring image, judging whether an anomaly occurs or not, and outputting abnormal data; and outputting abnormal data based on the image anomaly judgment model, and outputting an anomaly type and anomaly prediction time by using the trained abnormal data analysis model. The slope anchor rod grouting amount full-process intelligent monitoring system is constructed, and the limitation of a traditional monitoring method on data precision, space presentation and abnormal response is broken through.

The invention discloses a remote ultrasonic probe attitude synchronization and closed-loop control method based on inertial navigation, which integrates an inertial sensor technology, an attitude resolving algorithm, a three-dimensional visual interaction interface and a multi-mode control mechanism, and aims to realize accurate operation synchronization between a remote ultrasonic expert and a local ultrasonic inspection object. Therefore, the accuracy, the stability and the usability of remote ultrasonic examination are improved, the dependence on the skill level of a local operator is reduced, and the service range and the clinical efficiency of ultrasonic experts are expanded.

The invention relates to the technical field of intelligent vocational ability analysis, and discloses a dynamic planning method for a vocational ability genetic map based on multi-modal data and federal learning. The method comprises the steps that multi-source heterogeneous data in occupational activities is collected, and a multi-modal data set is formed through data cleaning and standardization processing; a graph neural network technology is utilized to construct a correlation topology between capability elements, spatio-temporal context information is fused, a dynamically evolved vocational capability gene map is established, and the accuracy and interpretability of vocational capability analysis are improved. Multi-node cooperative training is realized by adopting a federated learning framework, data privacy security is ensured in combination with a differential privacy technology, and the problem of data islands is solved. A capability evolution path is simulated based on a three-dimensional visualization and digital twinning technology, an occupational development scheme is generated through an intelligent recommendation algorithm, and a real-time feedback optimization mechanism is established. According to the method, dynamic, visual and personalized vocational ability analysis is realized, and accurate decision support is provided for vocational planning.

The invention discloses a series ultrahigh frequency sensing GIS three-dimensional positioning and monitoring system and method, and belongs to the technical field of high-voltage equipment state monitoring. The system comprises a sensing layer, a processing layer, a transmission layer and an application layer, wherein the sensing layer synchronously collects ultrahigh-frequency electromagnetic signals, sound wave vibration signals and SF6 gas state parameters through a plurality of serial multi-physical-quantity sensing nodes; the processing layer eliminates interference based on signal homology verification, calls an intelligent response model to dynamically compensate propagation path errors in combination with a GIS three-dimensional structure model and real-time environment data, outputs accurate three-dimensional coordinates of the partial discharge source by adopting a progressive time difference of arrival positioning algorithm, and identifies fault types and risk levels by fusing multi-dimensional features; the transmission layer encrypts and uploads the diagnosis report; and the application layer maps defect positions in the three-dimensional visual model and automatically generates an operation and maintenance work order according to risk levels. According to the invention, high-precision positioning, multi-source fusion diagnosis and closed-loop operation and maintenance are realized, and the accuracy and intelligent level of GIS equipment monitoring are remarkably 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 discloses a multi-source information real-time identification and positioning method for a coal mine rock burst risk area. The method comprises the following steps: integrating a micro-seismic system, a rock noise system, a stress system and a geological system to construct an acquisition network; extracting multi-source characteristic indexes and carrying out space-time unification; establishing a dynamic weighted risk fusion model to calculate a comprehensive risk index RI of a three-dimensional grid unit, wherein the weight of the comprehensive risk index RI is dynamically and adaptively adjusted along with mining; based on the RI value, a high-risk area is identified and positioned through three-dimensional visualization, and graded early warning information is generated; according to the invention, a time-space synchronous multi-source information acquisition network is constructed, and uniform preprocessing and feature extraction are carried out on four types of data of microseism, rock noise, stress and geologic structure, so that deep fusion and collaborative analysis of multi-source information are realized, and an information island phenomenon existing in traditional monitoring is overcome; and the judgment on the rock burst risk is more comprehensive.

The invention discloses an urban inland inundation prevention and control method based on water conservancy dispatching and pipe network cooperation, belongs to the technical field of urban inland inundation prevention and control, and aims to solve the problem of poor inland inundation prevention and control effect caused by independent operation of water conservancy facilities and drainage pipe networks and lack of cooperation in the prior art. A monitoring sensing network is constructed, and multi-source data are collected in real time and transmitted to a data processing center; a waterlogging prediction model is established through data cleaning and fusion processing in combination with big data and machine learning; according to the prediction result and the real-time water regimen, a water conservancy facility scheduling scheme is made, and meanwhile a drainage pipe network real-time monitoring and scheduling system is built to achieve cooperation of the two; emergency response is triggered automatically when waterlogging occurs, and decision support is provided by using GIS and three-dimensional visualization technology; continuously optimizing each system and scheme through a feedback mechanism; the method breaks the situation of'respective politics', optimizes resource allocation, improves drainage system efficiency and waterlogging prevention and control capability, effectively prevents and relieves waterlogging disasters, and guarantees life and property safety of urban residents and normal operation of cities.