41 results about "Cloud simulation" patented technology

The invention discloses a map generation method, electronic equipment and a robot, and relates to the technical field of artificial intelligence. The method comprises the steps of generating a structured prior map representing an environmental space occupation state according to environmental geometric shape design data of a target physical task space; determining a simulation path of the intelligent mobile device moving in the passage area of the structured prior map, and performing simulation scanning operation on the virtual physical model of the target physical task space along the simulation path to obtain laser point cloud simulation data and motion state simulation data; and generating a navigation map based on a pose map according to the laser point cloud simulation data and the motion state simulation data. According to the method and the device, the problems of high dependence on manpower, time consumption and uncertain generation results during map generation in the prior art can be solved, the map with high accuracy can be efficiently and automatically generated at low cost, and the task execution efficiency and the task execution precision of the intelligent mobile equipment are improved.

The embodiment of the invention provides an automatic driving cloud simulation platform test method and device, and the method comprises the steps: obtaining multi-source data of an automatic driving cloud simulation platform, carrying out the classification and structural extraction of the multi-source data, obtaining corresponding knowledge fragments, and storing the knowledge fragments into a knowledge source database, according to the types of the knowledge fragments, vectorizing the knowledge fragments by adopting different language models to obtain a document vector set, a code vector set and a scene parameter vector set; receiving and vectorizing a test demand described by a natural language, performing vector retrieval in the document vector set and the scene parameter vector set according to a retrieval enhancement generation algorithm, and inputting a retrieval result into the artificial intelligence model to understand the scene demand of the test, so as to obtain test case logic output by the model, the test code template is retrieved in the code vector set according to the test case logic, the input parameters are injected into the test code template to obtain the test code for testing, and the efficiency and accuracy of automatic driving cloud simulation platform testing can be improved.

The invention discloses a spiral groove milling curved surface point cloud simulation calculation method based on intersection points, and the method specifically comprises the steps: firstly, constructing a tool general parameterized model; then, a cutter milling kinematics model is constructed and used for guiding the milling process, and the milling mode of the spiral groove is achieved; secondly, solving a spiral groove milling curved surface point cloud model based on an envelope principle; and finally, carrying out reconstruction calculation on the point cloud model through point cloud intersection point calculation and a point cloud selection principle, and carrying out comparison verification on the calculated spiral groove milling curved surface point cloud simulation model and a model after importing a cutter milling track and a geometric shape into Veicut to carry out spiral groove curved surface simulation. According to the method, high-precision visual display is carried out on spiral groove milling curved surface point cloud simulation, and correctness and effectiveness of related theories of the method are proved.

This application provides a testing method and apparatus for an autonomous driving cloud simulation platform. The method includes: acquiring multi-source data from the autonomous driving cloud simulation platform; classifying and structurally extracting the multi-source data to obtain corresponding knowledge fragments and storing them in a knowledge source database; vectorizing the knowledge fragments according to their types using different language models to obtain document vector sets, code vector sets, and scene parameter vector sets; receiving test requirements described in natural language and quantizing them; performing vector retrieval in the document vector set and scene parameter vector set using a retrieval enhancement generation algorithm; inputting the retrieval results into an artificial intelligence model to understand the test scenario requirements; obtaining test case logic output by the model; retrieving test code templates from the code vector set based on the test case logic; and injecting input parameters into the test code templates to obtain test code for testing. This application can improve the efficiency and accuracy of testing autonomous driving cloud simulation platforms.

This invention discloses a remote sensing cloud simulation method and apparatus based on a classification-guided diffusion model, belonging to the field of remote sensing image cloud and fog simulation. The method includes: acquiring and preprocessing multi-temporal remote sensing images to construct a dataset containing registered pairs of cloudless and cloudy images; pre-training a feature extraction network based on cloud mask data and performing unsupervised clustering using the cloud features extracted by the network to achieve automated cloud classification; training a pre-constructed cloud simulation diffusion model using the cloudless image and cloud classification results as input, and the corresponding cloudy image as the ground truth supervision signal, to learn the mapping relationship from cloudless to cloudy states; and inputting the target cloudless image and a specified cloud category into the trained cloud simulation diffusion model to generate a simulated cloud-containing remote sensing image. This invention effectively improves the realism of generated clouds and fog, the naturalness of integration with ground features, and the controllability of generating specific cloud categories, providing sufficient and realistic training samples for cloud-related data-driven models.

The invention provides a data processing method and device, equipment, a storage medium and a program product, and relates to application of a simulation data processing technology in the field of vehicles. The method comprises the following steps: acquiring driving data acquired by a vehicle; processing the driving data in a cloud simulation environment matched with the vehicle to obtain sensing result data; the cloud simulation environment matched with the vehicle is configured to be a simulation environment simulating an actual scene of a vehicle end; and outputting the sensing result data according to a structured format to be used as training data of an auxiliary driving model. According to the method, the cloud simulation environment equivalent to the actual scene of the vehicle end can be constructed, and the driving data acquired by the vehicle can be stably and reliably processed by utilizing the sufficient computing power of the cloud end, so that the complete, consistent and traceable high-quality sensing data can be obtained. The sensing result can be output according to a preset format to be used for assisting training of the driving model, more accurate and richer learning signals are provided for the model, and the processing capacity of the model on a real driving scene is effectively improved.

1. The name of the design product: cloud simulation detection system information management display screen panel. 2. The use of the design product: the interface can be used on electronic devices such as physical carrier mobile phones, notebook computers, desktop computers, tablet computers, etc., for cloud simulation scene arrangement and monitoring related information display. 3. The design points of the design product: the graphical user interface in the screen. 4. The picture or photo that best indicates the design points: front view. 5. The use of the graphical user interface: clicking the "deploy" button in the upper right corner of the main view interface can enter interface change figure 1, which is used as a simulation scene management interface; clicking the task icon in the middle of interface change figure 1 enters interface change figure 2, which is used as a simulation scene monitoring interface.

The invention relates to the technical field of simulation deduction, in particular to a cloud simulation deduction platform and method, and the platform comprises a core simulation engine sub-platform which is used for carrying out the online detection of a simulation node based on MQTT, and controlling a simulator plug-in to carry out the frame data updating based on a step length; the matched tool chain sub-platform is used for obtaining a standard digital prototype according to a model embedding framework and managing digital prototype information and mirror image files based on model management and mirror image management, and the platform control subsystem is used for receiving detection information sent by the core simulation engine sub-platform, so that an engine is hooked with the standard digital prototype meeting a preset rule and is used for performing simulation on the standard digital prototype. Carrying out simulation deduction by adopting a platform simulation deduction mode, a multi-platform joint simulation deduction mode or a multi-platform parallel simulation deduction mode; the blue army model system sub-platform is used for carrying out blue army model system management based on equipment categories, and carrying out command and control model configuration management and tactical rule setting. According to the invention, the transmission efficiency and accuracy can be improved, and the deduction delay can be reduced.

The invention discloses a remote sensing image thin cloud removal method based on self-supervised domain adaptation, and belongs to the technical field of remote sensing image thin cloud removal, and the method comprises the steps: inputting a remote sensing image to be subjected to thin cloud removal into a trained remote sensing image thin cloud removal model based on domain adaptation, and obtaining a remote sensing image subjected to thin cloud removal, according to the remote sensing image thin cloud removal model, a simulation data set serving as a source domain is obtained through a thin cloud simulation model giving consideration to cloud distortion and a spatial form, and on the basis, the problem that precision is reduced when a cloud removal model is applied to a real thin cloud image due to the fact that data distribution of a simulation thin cloud image and data distribution of the real thin cloud image are inconsistent is solved. The invention provides a remote sensing image thin cloud removal model based on domain self-adaption, and the thin cloud removal model belongs to a domain self-adaption method based on self-supervised learning, so that the generalization ability of the model is enhanced, and a good cloud removal effect can be achieved under the condition that no target domain label or few target domain labels are used.

The present application relates to cloud computing and clean room equipment operation and maintenance management technical field, specifically to clean room equipment operation and maintenance system based on cloud computing;Contain data access, cloud simulation processing and terminal execution module;The system constructs management benchmark model through collecting business plan and operation and maintenance rule data;Its core is to combine resource account to generate theoretical damaged data through abnormal disturbance simulation, and calculate the dynamic time warping similarity and time series cross-correlation value of actual and theoretical residual vector to generate state decision result;When outputting state decision, the system will issue corresponding operation and maintenance instruction work order, and dynamically correct the disturbance operator weight;The present application realizes the change from single judgment depending on fixed threshold to accurate distinction between normal load deviation and abnormal equipment degradation, which can reduce the false positive rate of unnecessary room inspection and the false negative rate of equipment out of control.

This invention discloses a nuclear power industry mechanism model platform architecture for integration with an industrial internet platform, comprising a runtime environment layer, a service layer, an interface layer, a view layer, and an application layer. The runtime environment layer abstracts the hardware, provides the necessary library files for the upper-layer environment, and handles inter-cluster scheduling and communication. The service layer includes AI models, real-time computing models, cloud simulation models, industrial cloud software models, auxiliary analysis tools, and integrated development and execution tools. The interface layer standardizes and uniformly manages the interfaces of the service layer. The view layer includes mechanism model library interfaces, an operation management module, a data management module, and an engineering management module. The application layer includes artificial intelligence application scenarios, real-time computing scenarios, cloud simulation scenarios, and cloud-based industrial software scenarios. This invention provides an integrated development and execution environment for nuclear power industry mechanism models.

The invention discloses a report management system, method, equipment and medium for virtual device cloud simulation, and the system comprises a storage server which is configured to store report content; a database configured to store report records; the report container is configured to query and modify the report record in the database, access the report content of the storage server according to the report record, and display and modify the report content; the virtual tester container is configured to manage starting, running and ending of the virtual device container and read reports in the virtual device container; the server is further configured to store the report content to the storage server and add or modify accessible report records in the database; and the virtual device container is configured to read the numerical value in the virtual tester container, simulate actual device operation and record an operation report. The technical framework of the container cloud platform can be met, the virtual device test report can be stored, checked and shared, and the simulation test efficiency and the user experience can be effectively improved.

The invention belongs to the field of artificial intelligence, computer vision and computer graphics, and discloses a VR real-time rendering method and system for low-bit-rate cloud rendering plug flow, and the method comprises the steps: obtaining a rendering frame image; a lightweight super-resolution model is constructed; inputting the rendered frame image into the lightweight super-resolution model to obtain a reconstructed 4K-resolution image; and performing real-time rendering and display on the VR equipment based on the reconstructed 4K-resolution image. According to the invention, high bandwidth pressure caused by direct transmission of the 4K video is avoided, and the hardware limitation that low configuration equipment cannot carry out complex rendering tasks is overcome. Through the combination of a scene customization model and video coding, high-quality and low-delay visual experience under limited resources is realized, and the method is suitable for various application scenes with relatively high requirements on image quality and real-time performance, such as large-scale cloud simulation, VR tourism and intelligent power grid monitoring.

The application discloses an intelligent control method and system of an electromagnetic oven based on an industrial cloud platform, and relates to the technical field of the industrial cloud platform. In the industrial cloud platform, a high-dimensional state tensor is input into a digital twin model, and an information neural network is combined to perform evolution deduction on an electromagnetic energy conversion process and a heat flow transfer field, and corresponding inversion results are output. The digital twin model and the industrial cloud platform are further controlled, and the accuracy of the inversion results is improved. The industrial cloud platform retrieves a matched cooking process baseline in a cloud knowledge base according to a refined working condition label; the cooking process baseline is taken as a constraint condition, and corresponding multi-target reward content is determined in combination with real-time working data of the electromagnetic oven; rolling time domain optimization is performed in a cloud simulation environment, so that corresponding adaptive control instruction sets are generated; and intelligent control events of the electromagnetic oven are further determined in combination with a current working sequence of the electromagnetic oven, so that the accuracy of the intelligent control events of the electromagnetic oven is improved.

The embodiment of the invention discloses a safety performance cloud simulation method and device of a building structure, equipment and a medium. The method comprises the steps that the method is applied to a cloud management platform, structural security analysis basic data uploaded by a user is received, and the structural security analysis basic data comprises building body model data, structural analysis category data and geographic data; utilizing the building body model data, the structure analysis category data and the geographic data to carry out target type structure safety performance analysis on a building body corresponding to the building body model data to obtain an analysis result; and after the analysis result is uploaded to the cloud, the user can browse the analysis result of the building interactively at the cloud and screen concerned key information, so that the structural safety is effectively judged. Through cloud computing, the process of structure safety performance analysis is completed at the cloud, and safety performance simulation analysis of the building structure can be realized without configuring high hardware and more resources locally.

This application discloses a map generation method, electronic device, and robot, relating to the field of artificial intelligence technology. The method includes: generating a structured prior map representing the occupancy state of the environmental space based on environmental geometry design data of the target physical task space; determining a simulated path for the intelligent mobile device to move within the traversable area of ​​the structured prior map, and performing a simulated scanning operation on a virtual physical model of the target physical task space along the simulated path to obtain laser point cloud simulation data and motion state simulation data; and generating a pose-based navigation map based on the laser point cloud simulation data and motion state simulation data. This application can solve the problems of related technologies in map generation, which are highly dependent on manual labor, time-consuming, and produce uncertain results. It can efficiently, cost-effectively, and automatically generate highly accurate maps, improving the task execution efficiency and accuracy of intelligent mobile devices.

The application relates to a kind of super-high-speed collision space debris cloud simulation calculation method and device in aerospace technology field, the method comprises the following steps: establishing the three-dimensional geometric model of projectile and target plate, the model is meshed, each grid corresponds one SPH particle, reads initial parameter and assigns to the SPH particle, searches the particle adjacent to the SPH particle and the particle adjacent to the SDPH particle, calculates the update parameter of the SPH particle and the update parameter of the SDPH particle based on the search result, judges whether SPH particle is converted into SDPH particle or not;If not, the update parameter of SPH particle is used to update SPH particle parameter;If yes, the update parameter of the SDPH particle obtained by using the update parameter calculation method of SDPH particle is used to update the SDPH particle parameter, after the end of the above loop calculation, the debris cloud shape distribution and scale distribution can be visualized and displayed.The application reduces the amount of calculation, and has better accuracy.

Systems and methods are provided for implementing virtual cloud simulation within a public cloud network. In examples, a domain name system ("DNS") server in a virtual cloud network receives, from a service under test that is running within the virtual cloud network, a request to access a resource, the request including non-routable cloud configurations for the resource. A central configuration repository in the virtual cloud network maps the non-routable cloud configurations for the resource that are identified in the request from the service under test to public cloud configurations of the resource. A reverse proxy server in the virtual cloud network directs the request to a public cloud instance of the resource that is running in another portion of the public cloud network, directs return data traffic from the public cloud instance of the resource back to the service under test in the virtual cloud network.

The invention discloses a nuclear power industrial mechanism model platform architecture for industrial internet platform integration. The nuclear power industrial mechanism model platform architecture comprises an operation environment layer, a service layer, an interface layer, a view layer and an application layer, the operation environment layer is used for abstracting hardware, providing library files required by operation for an upper-layer environment and carrying out scheduling and communication among clusters, and the service layer comprises an AI model, a real-time calculation model, a cloud simulation model, an industrial cloud software model, an auxiliary analysis tool and an integrated development operation tool; the interface layer carries out standard packaging and unified management on interfaces of the service layer, the view layer comprises a mechanism model library interface, an operation management module, a data management module and an engineering management module, and the application layer comprises an artificial intelligence application scene, a real-time calculation scene, a cloud simulation scene and a cloud industrial software scene. According to the invention, an integrated development operation environment is provided for a nuclear power industrial mechanism model.

This invention discloses a radar echo simulation method based on layered chaff cloud simulation, constructing the chaff cloud as a layered mathematical model segmented according to vertical height. The relationship between the shape parameters of the chaff layers and the chaff scattering coefficient is studied, solving the problems of excessive chaff unit numbers and slow computation speed caused by traditional ellipsoidal modeling based on small cube equivalents. First, the chaff cloud is divided into chaff units at different heights according to its density; second, the relationship between the shape of the chaff unit and the radar scattering coefficient is considered; finally, the echo signal generated by the motion law corresponding to the chaff unit is modeled, and the signals of the overall chaff units are superimposed to obtain the final echo. This invention only requires estimating the shape and size of the chaff cloud, thus achieving fast and accurate simulation of radar echoes from chaff clouds.

The present application relates to the field of AI. The present application specifically relates to a point cloud simulation model training method and a related device. The method comprises: acquiring a plurality of pieces of first point cloud data at a plurality of different positions in a target scene; on the basis of the plurality of pieces of first point cloud data, constructing an initial point cloud simulation model, and determining a plurality of pieces of pose information of a target object, parameters of the initial point cloud simulation model comprising the reflection intensity and loss rate of a Gaussian sphere corresponding to a point in a point cloud, and the target object is an object in the plurality of pieces of first point cloud data; on the basis of camera intrinsic parameters, respectively converting the plurality of pieces of first point cloud data into a plurality of first depth maps; and training the initial point cloud simulation model on the basis of the plurality of pieces of pose information and the plurality of first depth maps, so as to obtain a target point cloud simulation model. Real-time rendering of point clouds can be achieved, and rendering precision of point clouds can be improved.

The application discloses a kind of city emergency management simulation method, device, electronic equipment and storage medium.The present application includes: obtaining the emergency knowledge and emergency data corresponding to emergency task;According to the emergency knowledge and the emergency data determine emergency role;The nested execution pair of the emergency role is constructed;According to the nested execution pair, the system requirement of the emergency role is extracted, and the emergency system analysis template is generated according to the system requirement;Task decomposition is carried out on the emergency task using the emergency system analysis template, and the task decomposition result is obtained;Interactive logic modeling is carried out using the task decomposition result, and the logic flow is formed;The logic flow is used to generate Agent execution graph;Executable simulation model of the Agent execution graph is generated, and the executable simulation model is combined with cloud simulation model.

The invention discloses a rapid expansion cloud chamber environment simulation method and system based on artificial intelligence, and the method comprises the steps: obtaining the experimental data and experimental conditions of a to-be-simulated expansion cloud chamber, carrying out the structural classification based on the experimental data according to the experimental conditions and expansion stages, and obtaining the feature vector of each stage, meta learning is carried out through a neural network according to the feature vectors, a cloud simulation model and simulation errors are obtained, a cloud chamber working condition interval is identified based on the simulation errors and experimental data, an output result of the cloud simulation model in a high-deviation interval is obtained according to the working condition interval, and an interval result is corrected through a CFD equation based on the output result. And obtaining a cloud room environment simulation result. According to the method, the cloud expansion stage is split, the fog drop growth process is fitted, CFD local correction is carried out on the simulated high-deviation interval, the prediction error control precision is improved, the prediction and collaborative analysis efficiency of the fog forming process in the complex environment is improved, and meanwhile good interpretability is achieved.

The invention relates to the field of AI. The invention particularly relates to a point cloud simulation model training method and related equipment. The method comprises the following steps: acquiring a plurality of pieces of first point cloud data of a plurality of different positions in a target scene; constructing an initial point cloud simulation model based on the plurality of pieces of first point cloud data and determining a plurality of pieces of pose information of the target object, wherein parameters of the initial point cloud simulation model comprise reflection intensity and loss rate of a Gaussian ball corresponding to a point in the point cloud; the target object is an object in the multiple pieces of first point cloud data; converting the plurality of first point cloud data into a plurality of first depth maps based on camera internal reference; and training the initial point cloud simulation model based on the plurality of pose information and the plurality of first depth maps to obtain a target point cloud simulation model. The real-time rendering of the point cloud can be realized, and the rendering precision of the point cloud can be improved.

This invention provides a structured hierarchical management method, device, and server for cloud simulation data, relating to the technical field of industrial simulation applications. The method includes: performing hierarchical storage processing on cloud simulation result data based on access popularity and usage demand information, storing the cloud simulation result data according to corresponding data storage structures to obtain multi-level result data; preloading simulation animations in the multi-level result data using a preset animation preloading switch, and independently indexing and rendering components in static cloud maps within the multi-level result data to obtain target multi-level result data; and performing automated screenshot processing and screenshot validity verification on the target multi-level result data to obtain a target simulation report. This invention can significantly reduce storage costs and improve the accuracy of displayed results by optimizing the storage and display process of cloud simulation data.

The application relates to a cloud simulation computing resource prediction method, device and equipment based on ranking learning, which comprises the following steps: acquiring a feature data set of a simulation application on a cloud computing node; the data in the feature data set comprises pre-operation parameters and runtime parameters of the simulation application; relevant feature data which significantly affects the running time of the simulation application is extracted from the feature data set based on a SHAP feature extraction method; the relevant feature data is input into a constructed ranking learning model to predict the priority ranking of different cloud computing resource usage; and the cloud computing resource usage with the highest ranking output by the ranking learning model is taken as an optimal cloud simulation computing resource prediction result. The relevant feature data which significantly affects the running time of the simulation application is extracted as model input by using the SHAP explainability-based feature extraction method, and the ranking learning model is used to predict the cloud computing resource usage with the highest ranking, so that the resource prediction performance is greatly improved.

The utility model discloses an automatically-controlled cloud simulation structure, and belongs to the technical field of outdoor solar testing devices. An automatically-controlled cloud simulation structure comprises a cabin body; the lamp is fixedly connected to the cabin body; the guide rail is fixedly connected to the cabin body; the support is slidably connected to the guide rail; the mounting frame is fixedly connected to the bracket; the filter screen is fixedly connected to the mounting frame; the filter screen is located under the lamp. A hanging wheel is connected in the guide rail in a sliding manner and is fixedly connected with the bracket; the cabin body is fixedly connected with a mounting frame, the mounting frame is connected with an electric push rod, and the electric push rod is connected with the support; according to the utility model, the electric push rod arranged on the cabin body drives the support to slide so as to drive the filter screen on the support to move, and the filter screen moves at different positions, so that sunlight can be shielded and not shielded, the filter screen does not need to be manually replaced and disassembled, and the test time is saved.

The application provides a wheel dual-axis performance evaluation method and device based on numerical calculation and a server, relates to the technical field of cloud simulation application, and comprises the following steps: according to wheel dual-axis performance evaluation requirements, associating and building each functional component to generate a wheel dual-axis simulation application process; obtaining available supercomputing calculation resource information at the current moment, combining the available supercomputing calculation resource information with to-be-executed component queue information and component dependency relationship information corresponding to the wheel dual-axis simulation application process into scheduling state information, performing decision processing on the scheduling state information through a reinforcement learning model to generate a target component execution sequence; calling each functional component according to the target component execution sequence, generating a dual-axis equivalent loading model based on a wheel three-dimensional model, and performing dual-axis performance evaluation processing on the dual-axis equivalent loading model to obtain a wheel dual-axis performance evaluation result. The application can significantly improve the wheel dual-axis performance evaluation efficiency and evaluation accuracy.

Systems and methods are provided for implementing virtual cloud simulation within a public cloud network. In examples, a domain name system (“DNS”) server in a virtual cloud network receives, from a service under test that is running within the virtual cloud network, a request to access a resource, the request including non-routable cloud configurations for the resource. A central configuration repository in the virtual cloud network maps the non-routable cloud configurations for the resource that are identified in the request from the service under test to public cloud configurations of the resource. A reverse proxy server in the virtual cloud network directs the request to a public cloud instance of the resource that is running in another portion of the public cloud network, directs return data traffic from the public cloud instance of the resource back to the service under test in the virtual cloud network.

The invention relates to an experimental system for simulating solar radiation, which comprises a test chamber, a control device, a cooling device and simulation test light source units, and is characterized in that the simulation test light source units are sequentially arranged at the top of the test chamber, and each simulation test light source unit comprises a light source lamp holder, a plurality of sets of independently distributed irradiation light sources and a hoisting mechanism; an infrared displacement sensor and a tilt angle sensor are respectively mounted on the light source lamp holder, the irradiation light source adopts a metal halide light source for simulating solar radiation spectral characteristics and irradiation intensity, the irradiation light source is connected with a cloud simulation mechanism, and the light source lamp holder is mounted at the top of the test chamber through a hoisting mechanism. A temperature sensor and a humidity sensor are arranged in the test chamber, and the test chamber is respectively connected with the control device and the cooling device. The device has the beneficial effects that the irradiation lamp source is provided with the cloud simulation mechanism, so that 50W / m < 2 > low-irradiance irradiation can be realized. The method is suitable for simulating the solar radiation heat and optical effect bearing capability of vehicles and large-scale products and evaluating the reliability of the products.