11results about How to "Quick map" patented technology

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.

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 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 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.

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.