17results about How to "Quick map" patented technology

The embodiment of the invention discloses an image display method and device based on auxiliary rendering, computer equipment and a medium, and the method comprises the steps: carrying out the construction of a display function region, so as to obtain a video memory rendering buffer region and a frame buffer region, constructing a display algorithm operation space according to the video memory rendering buffer area and the frame buffer area, and binding the video memory rendering buffer area and the frame buffer area according to the rendering base point; generating a first display image in the video memory rendering buffer area according to a pre-stored first image rendering strategy; mapping the first display image to a frame buffer area; performing auxiliary rendering on the first display image according to a pre-stored second image rendering strategy to obtain a corresponding second display image; and mapping the second display image to an image real-time display screen of the image processing display system based on the image memory address of the second display image. According to the method, through an auxiliary rendering strategy, rapid image generation and mapping are realized, a blocking phenomenon in a traditional process is avoided, and the image display speed is further accelerated.

The application provides a real-time conversion method for pixels and geographic latitude and longitude in low-altitude photogrammetry, which comprises the following three parts: unmanned aerial vehicle capability confirmation, real-time conversion service implementation deployment for pixels and geographic latitude and longitude in low-altitude photogrammetry, and GIS geographic information platform integration docking. Through real-time data collected by an unmanned aerial vehicle, combined with a computer vision algorithm and a spatial geometric transformation model, the specific pixel points in image data are associated with real geographic coordinates, so that accurate positioning and measurement of ground objects are realized. The application relates to the technical field of low-altitude photogrammetry, and through the cooperative work of real-time data collection by an unmanned aerial vehicle, real-time conversion service for pixels and geographic latitude and longitude in low-altitude photogrammetry, and a GIS geographic information platform, efficient mapping from a photographed image to a geographic coordinate is realized, and accurate and rapid technical support is provided for low-altitude photogrammetry.

The present invention relates to a method, device and equipment for designing a high-density memory chip packaging structure. The method: based on the current packaging structure parameter combination, a multi-chip stacking structure of a high-density memory chip is three-dimensionally modeled to obtain a packaging structure model; a finite element analysis is performed to obtain stress distribution data and a stress-strain curve; feature extraction and feature fusion are performed to obtain a fused feature vector; a structure optimization model is obtained based on multi-layer feedforward neural network training; dependency analysis is performed to construct a parameter tree structure and assign corresponding priority values; multiple packaging structure parameters are sorted and optimized one by one using the parameter tree structure and the priority value, and an adaptive penalty function method is used to process constraint conditions to obtain a target packaging structure parameter combination. The implementation of the present invention improves the design efficiency and performance of the high-density memory chip packaging structure.

This invention relates to the field of materials analysis technology, specifically disclosing a method and system for detecting the content of aroma active substances in grapefruit hydrosol flower tea based on spectroscopy. The method involves constructing a simulated matrix sample library and collecting its first component characteristic spectra and sensory attribute quantification values ​​to establish a baseline prediction model. Then, by collecting the second component characteristic spectra and sensory attribute quantification values ​​of real samples, an enhanced prediction model is obtained through feature distribution adaptation and transfer learning techniques. Finally, volatile component features are extracted from the sample to be tested, and the target component characteristic spectra are input into the enhanced prediction model to directly output the sensory attribute quantification values ​​as the detection result. This invention effectively solves the problem of aroma contribution evaluation distortion caused by matrix-removal analysis in traditional gas chromatography-olfactometry, achieving accurate mapping from chemical components to sensory attributes, and significantly improving detection efficiency while ensuring detection accuracy.

The application provides an antenna array beamforming method and system based on a radiation pattern, comprising a self-encoder network and a beamforming matrix; the self-encoder network comprises a self-encoder module and a vector-precoding module. The self-encoder network directly learns the nonlinear mapping relationship between the beamforming matrix and the target pattern, the network is trained by using data and the pattern features are extracted, so that the model can adapt to different hardware architectures such as full-digital beamforming, analog beamforming and hybrid beamforming, the fast mapping from the normalized pattern to the beamforming matrix is realized, the real-time deployment demand in a dynamic environment is met, the real-time performance, adaptability and prediction accuracy of array comprehensive beamforming are effectively improved, and a new technical path is provided for the wireless communication system to realize efficient and low-latency beamforming in a complex environment.

This invention relates to the field of intelligent route selection technology, and particularly to a progressive optimization method, medium, and device for railway route schemes in densely constrained environments. The method includes: constructing a multi-constraint fused geographic grid model that integrates spatial constraints and auxiliary data of the research area; generating an initial route search graph network including vertex and edge sets based on the multi-constraint fused geographic grid model; using spatial conflict as the driving force, progressively optimizing the network based on the initial route search graph network and the set of active edges to obtain a final candidate route graph network; and using a breadth-first search method to search for candidate paths based on the final candidate route graph network, and ranking each candidate path according to cost indicators to output the top N candidate paths as the preferred scheme group. This invention effectively solves the problems of existing methods in constrained and coupled scenarios, such as difficulty in systematically evaluating conflicts, exhaustively exploring feasible solutions, and easily causing repeated rework of schemes.

The present invention proposes an artificial intelligence automobile automatic question-answering method and system, which belongs to the fields of artificial intelligence, natural language processing and human-computer interaction; the automobile question-answering knowledge base of the knowledge graph used in the method enables the relationship between entities to be quickly mapped to the corresponding position of the knowledge graph, and can quickly generate results, which improves the response speed compared with text retrieval; when analyzing data information, a deep learning model and a general large model question-answering system are combined to generate accurate relationships between entities, and a method for in-depth analysis and determination of the relationships between entities is given to ensure that the generated relationships between entities are accurate and reliable; the relationships between the generated entities are mapped to the knowledge graph automobile question-answering knowledge base, and the results generated by the knowledge graph automobile question-answering knowledge base are fed back to the car owner; therefore, the method will be more accurate in identifying data information, and the information fed back to the car owner will be more precise.

The invention relates to the technical field of water pressure mapping, in particular to a water pressure mapping method and analysis method based on slice grids and structural grids, and the water pressure mapping method comprises the following steps: obtaining a three-dimensional model, slicing the three-dimensional model to obtain a plurality of slice units, and performing grid division on each slice unit; calculating the speed potential of the grid center of each slice unit based on a source sink method, and calculating the pressure data of the grid center of each slice unit according to the speed potential; performing mesh division on the three-dimensional model to obtain a finite element model, acquiring coordinates of a mesh center of each slice unit and coordinates of a mesh center of the finite element model, and interpolating and mapping pressure data of the mesh center of each slice unit to the mesh center of the finite element model by using a radial basis function, and obtaining pressure data of the grid center of the finite element model. According to the method, the accurate transmission of the hydrodynamic grid pressure data to the structural grid is realized, and powerful data support is provided for subsequent fluid-structure interaction analysis.

The invention provides an instruction analysis and assembly method and device. The method comprises the steps that a static instruction template corresponding to an instruction type is determined, the static instruction template is a constant array, elements of the static instruction template are arranged according to the declaration sequence of members in a structural body corresponding to the instruction type, and each element comprises the byte offset position of the member in the structural body and a data type identifier; based on a static instruction template corresponding to the instruction type, filling data in the instruction frame into a structural body corresponding to the instruction type according to the byte offset position and the data type of each member; and based on a static instruction template corresponding to the instruction type, splicing data corresponding to each member in a structural body corresponding to the instruction type according to the byte length corresponding to the data type of the member and the byte offset position of the member to obtain a byte array, and packaging the byte array according to an instruction frame format. According to the method provided by the invention, the accuracy and efficiency of instruction analysis and assembly are improved.

The invention belongs to the technical field of computational fluid mechanics and artificial intelligence crossing, and particularly relates to a supersonic speed tail flame flow field rapid calculation method based on a physical information neural network, and the method comprises the following steps: S1, constructing a profile spectrum parameter data set and a tail flame flow field sample data set of a rocket engine; constructing a physical information neural network model; constructing a total loss function of a physical information neural network model, taking the profile spectrum parameter data set as an input data set of the neural network model, and normalizing the tail flame flow field data to serve as an output data set of the neural network model; training and testing the neural network model to obtain a trained neural network model; obtaining profile spectrum parameters of a rocket engine to be measured, inputting the profile spectrum parameters into the trained neural network model, and outputting a corresponding tail flame flow field distribution prediction result; the problems that an existing rocket engine tail flame flow field calculation method is high in calculation cost, physical information is lost, and large-scale efficient calculation requirements are difficult to support are solved.

This invention discloses an adaptive rapid modeling method for tunnels based on the fusion of inspection and monitoring data and design data. The method utilizes numerical simulation to construct a multi-source heterogeneous dataset containing tunnel geometry, physical properties, and an optimal mesh size field. A geometric reconstruction neural network is built and trained to transform tunnel inspection and monitoring point cloud data into implicit geometric representations. A semantic parsing module extracts key physical elements from the design data and establishes a standardized information set. A feature fusion mechanism combines physical elements with geometric representations, inputting the data into a trained adaptive field prediction network to predict the posterior error distribution after structural stress. This predictor then calculates the target mesh size field, including absolute size references and local refinement features, directly generating a finite element model. This invention overcomes the shortcomings of traditional modeling methods, such as geometric-physical separation and reliance on manual experience for mesh generation, through multi-source data fusion and deep learning technology, achieving high-precision and high-efficiency automated modeling of tunnel structures.

The invention provides a network optimization method and device, a medium and a product, relates to the technical field of Internet, and aims to solve the problem that quick mapping between simulation network modification and to-be-simulated network modification cannot be realized by a universal technology. The network optimization method comprises the following steps: acquiring network configuration information of a to-be-simulated network in a plurality of time periods; in response to a network simulation request for a first time period in the plurality of time periods, simulating a to-be-simulated network according to the network configuration information of the first time period to obtain a simulated network of the first time period; and in response to the optimization operation on the simulation network in the first time period, optimizing the to-be-simulated network according to the optimization operation.

The invention provides a construction method and application of a power device electro-thermal coupling simulation agent model, and relates to the technical field of power electronic device simulation. The method comprises the following steps: establishing a finite element simulation model of a power device based on geometric structure parameters of the power device and multi-physical field coupling parameters required by electro-thermal coupling simulation; physical field simulation data is obtained through an electro-thermal coupling finite element simulation model on the basis of electrical parameters of a power device and serves as a training data set of an agent model constructed by a deep neural network model architecture, and rapid and high-precision mapping from input parameters to multi-physical field distribution is achieved. Rapid prediction of a three-dimensional electric field, a temperature field and a stress field in the power device is realized, the calculation efficiency is remarkably improved, and meanwhile, the precision level equivalent to that of finite element simulation is kept. The model can be embedded into an online monitoring system, an unmeasurable physical field in a device is inversed in real time, and dynamic identification and life prediction of a thermal stress concentration area are supported.

A kind of spent fuel assembly disassembly cutter performance evaluation device and evaluation method, for the sawing machinability of nuclear grade material of irradiated spent fuel assembly in dry condition without lubrication is carried out system test and quantitative evaluation, the device includes: main test table, including main rack, main work platform, main drive mechanism, transverse drive mechanism, vertical drive mechanism, cutter and spent fuel assembly clamp, cutter is connected with main drive mechanism;Sub-test table is set in the side of main rack corresponding to main drive mechanism;And control system, for controlling main drive mechanism, transverse drive mechanism and vertical drive mechanism, and real-time detection torque, current, vibration, noise and cutter temperature of main drive mechanism output, real-time monitoring cutter tooth wear and the cutting topography of being cut object, collect and store test data, and construct dry sawing reliability feature database.The present application also provides spent fuel assembly disassembly cutter performance evaluation method.

The embodiment of the invention provides an audio processing method and platform, a computing device and a storage medium. The audio processing method comprises the steps that dynamic interaction data of a user and a virtual character in an interaction scene and initial audio of the virtual character are acquired; based on the dynamic interaction data, multi-dimensional audio features of the virtual character in the interaction scene are mapped and generated; performing audio decoding on the initial audio to obtain a multi-dimensional audio parameter of the initial audio; based on the multi-dimensional audio features, adjusting the multi-dimensional audio parameters to obtain adjusted multi-dimensional audio parameters; and performing audio coding on the adjusted multi-dimensional audio parameters to obtain a target audio of the virtual character. The audio of the virtual character can respond to the change of the dynamic interaction data in the interaction scene, the immersion of the user is improved, and the method can be widely applied to the fields of digital culture product manufacturing software and the like.

A data governance method, system, medium and device based on multi-source data, relating to the field of data governance technology. The method comprises: when a target file to be governed is obtained, matching a user-defined target template corresponding to the target file; parsing the target template to obtain parsed template data; matching the parsed template data with the data columns in the target file to obtain a matching result; filtering the matching result based on a preset filtering rule to obtain a filtering result; and data governing the filtering result to obtain a governance result. Implementing the technical solution provided by the present application can improve the versatility of the template-based data governance solution.

The invention discloses a model prediction control method and system for a totem-pole PFC circuit, and belongs to the technical field of totem-pole PFC circuits, and the method comprises the steps: monitoring the input voltage of an AC power supply, the bus voltage of the totem-pole PFC circuit, and load demand information in real time; determining that the totem-pole PFC circuit works in a boost mode or a voltage-multiplying mode and driving signal distribution logic of each switch tube in the bridge circuit; calculating an optimal modulation ratio based on a model prediction control algorithm according to an error between the target bus voltage and the currently detected bus voltage; generating a first SPWM signal with a corresponding duty ratio and a complementary second SPWM signal according to the optimal modulation ratio; and distributing the first SPWM signal and the second SPWM signal to corresponding switch tubes to realize control of the bus voltage. According to the method, the SPWM duty ratio is dynamically adjusted through model prediction control, and rapid, accurate and stable control over the totem pole PFC bus voltage is achieved.