264 results about "Simulation based" patented technology

One embodiment sets forth a technique for fine-tuning a machine learning model to perform physical reasoning. According to some embodiments, the method can include the steps of obtaining simulation annotations that describe interactions among simulated objects within a physics-based environment and one or more question templates, each question template defining a different parameterized reasoning query; generating, based on the simulation annotations and the one or more question templates, a plurality of question-answer pairs that represent physical reasoning examples; formatting the question-answer pairs into natural-language data compatible with the machine learning model; and fine-tuning the machine learning model based on the natural-language data.

The application provides an ADAS controller test method, device, terminal and storage medium. The method comprises the following steps: based on setting environment information and setting target information, generating simulation target information required by a target test scene of a to-be-tested ADAS controller installed on a real vehicle; sending the simulation target information to each vehicle body CAN interface of the real vehicle, and receiving control information of the to-be-tested ADAS controller updated based on the simulation target information and / or first vehicle state information of the real vehicle; and generating a test report of the to-be-tested ADAS controller about the target test scene according to the control information and / or the first vehicle state information. The application can avoid collision caused by extreme working conditions, reduce collision risk, reduce test cost and improve test efficiency when testing the real vehicle function of the ADAS controller.

This invention discloses a method for assessing the quality of carbon emission data, relating to the field of carbon emission data quality assessment. The method employs sensitivity analysis to determine the main parameters affecting total carbon emissions; it scores the quality of these main parameters across four dimensions: numerical accuracy, source reliability, evidence standardization, and the degree of digitization of evidence, converting the scores into parameter uncertainty U-values; it performs two rounds of Monte Carlo simulations based on the parameter uncertainty U-values ​​to construct the likelihood function corresponding to the current observation; it calculates historical uncertainty U-values ​​based on multi-period historical carbon emission data and fits the prior probability distribution of the uncertainty; and it applies a Bayesian update formula to fuse the likelihood function corresponding to the current observation with the prior probability distribution, deriving the posterior distribution of the current carbon emission data uncertainty to determine whether the current carbon emission data meets quality requirements. This method improves the scientific rigor, transparency, and operability of carbon emission data quality management.

This invention belongs to the field of oil supply, lubrication, and cooling technology for aero-engine bearings. It provides a method for temperature control and parameter optimization design of under-ring lubricated bearings. The method includes: generating sample data on total heat generation, bearing element temperature, and oil slingering temperature of the bearing through experiments or simulations based on bearing structural parameters and operating condition parameters; constructing a predictive model with the parameters as input and thermal-fluid performance as output; quantifying the influence of input parameters using global sensitivity analysis, screening key design parameters, and constructing a multi-objective optimization model with the objectives of minimizing bearing element temperature control accuracy and total heat generation; solving the model to obtain the Pareto optimal solution set, and determining the optimal combination of structure and oil supply parameters that satisfies the oil slingering temperature safety constraint and bearing thermal reliability requirements while achieving optimal overall performance. This invention is applicable to the refined design of high-speed bearings in rotating machinery such as aero-engines, enabling precise temperature control and coordinated energy consumption optimization.

The application discloses a kind of hardware-in-the-loop test of automatic driving domain controller, comprising: real-time processor and graphics workstation;Graphics workstation is used to generate simulation traffic scene information, simulation sensor information is generated based on simulation traffic scene information, first simulation sensor information in simulation traffic scene information and simulation sensor information, simulation traffic scene information and simulation sensor information are transmitted to automatic driving domain controller, second simulation sensor information in simulation sensor information is transmitted to real-time processor;Real-time processor is used to transmit second simulation sensor information to automatic driving domain controller, receives the vehicle control information that automatic driving domain controller feedback.This application provides the hardware-in-the-loop test system, device, storage medium of automatic driving domain controller, can avoid the problem that scene information and sensor perception information do not match when hardware-in-the-loop test, improves the accuracy of test.

This invention relates to the field of training data construction technology, and discloses a method, system, terminal, and storage medium for generating intelligent agent training data based on high-fidelity dynamic interactive assets. The method includes: constructing a high-fidelity simulated scene and establishing a decoupled structure between the interactive assets, the visual representation layer, and the physical proxy layer; loading a high-fidelity virtual human as the interactive demonstration subject in the scene; parsing and planning natural language tasks to generate a structured sub-task sequence, and completing instantiation mapping in conjunction with the interactive assets; performing physical simulation based on the action sequence, collecting multimodal observation data and object state changes, and aligning multi-dimensional data under a unified time reference to form dynamic interactive assets and high-reliability training data. This invention achieves the unification of high-fidelity rendering and physically consistent interaction, and can automatically generate replayable, searchable, and combinable dynamic interactive data, thereby significantly improving data generation efficiency, realism, and cross-scene transfer capabilities.

This application relates to the field of quantum computing technology, and in particular to a method and apparatus for accelerating quantum circuit simulation based on decision graphs. The method includes: acquiring a decision graph corresponding to the matrices of several ordered quantum logic gates in a quantum circuit to be simulated; calculating the simulation computation cost corresponding to the matrices based on the decision graph; performing a phased fusion optimization process on the matrices of the several quantum logic gates according to the simulation computation cost to generate one or more fused equivalent quantum logic gate matrices; and performing quantum circuit simulation computation using the fused equivalent quantum logic gate matrices. This application uses gate fusion to reduce the number of matrices that need to be loaded into memory, thus reducing memory access latency. Gate fusion also reduces the number of MVM operations; for example, after fusion of k quantum logic gates, only m MVM operations are required, where m < k, significantly improving the speed of quantum circuit simulation.

The method for simulating the pack forming of a plunger slipper assembly of the application comprises the following steps: establishing a pack forming simulation model of the plunger slipper assembly; obtaining the inner contour characteristic parameters of the pack forming simulation model of the plunger; performing a pull-off simulation based on the pack forming simulation model of the plunger slipper assembly to obtain the axial clearance of the pack forming simulation model of the plunger slipper assembly; performing a rotation simulation based on the pack forming simulation model of the plunger slipper assembly to obtain the swing angle of the pack forming simulation model of the plunger slipper assembly; establishing a mapping database of the process parameters, the axial clearance of the pack forming simulation model of the plunger slipper assembly and the swing angle of the pack forming simulation model of the plunger slipper assembly; and establishing a multiple regression model of the inner contour characteristic parameters of the pack forming simulation model of the plunger, the axial clearance of the pack forming simulation model of the plunger slipper assembly and the swing angle of the pack forming simulation model of the plunger slipper assembly. The method can reduce the cost of raw materials and the cost of tests.

The system according to this embodiment aims to enable users to practice effective proposal methods and negotiation strategies in advance, based on the characteristics of their clients' representatives. [Solution] The system according to the embodiment comprises a reception unit, a learning unit, a generation unit, a simulation unit, and a feedback unit. The reception unit inputs information of the contact person of the business partner. The learning unit learns based on the information input by the reception unit. The generation unit generates advice and suggestions based on the data learned by the learning unit. The simulation unit performs a dialogue simulation based on the advice and suggestions generated by the generation unit. The feedback unit inputs feedback on the dialogue performed by the simulation unit.

Techniques are described herein for evaluating and tuning parameters for controlling the behavior of an autonomous vehicle in or near intersections controlled by traffic signals. A planning component of an autonomous vehicle may use a set of traffic signal parameters to compute trajectory costs for the vehicle associated with traversing an intersection controlled by a traffic signal in a non-permissible state (e.g., a red light). A parameter tuning system may execute driving simulations using the planning component and a candidate set of parameters to control the behavior of a simulation vehicle within a training data set of traffic signal intersections. The parameter tuning system may determine performance metrics based on the behaviors of the simulated vehicle and may execute a search algorithm to determine modified (e.g., optimal) parameter sets for controlling vehicles during real-world driving scenarios having intersections controlled by traffic signals.

This invention relates to the field of permanent magnet synchronous motor (PMSM) design technology, and discloses a method and device for integrated collaborative optimization design of the rotor magnetic circuit of a PMSM. The method includes: collecting time-series data of multi-source vibration and electromagnetic load under heavy-load conditions of forklift operation, and constructing a dynamic excitation phase space mesh for the rotor interface; performing multi-field coupled response simulation based on the mesh to drive a parameterized rotor model, generating a structural eddy current coupled simplex complex; constructing a combined constraint and sub-mode gain model for robust magnetic circuit optimization based on the complex, generating a geometrically reinforced candidate solution set; performing multi-objective collaborative convergence and three-dimensional model generation under the constraints of the candidate solution set, and outputting an anti-disturbance optimized rotor structure. This invention solves the problem that existing technologies cannot cope with dynamic multi-field positive feedback under complex forklift operating conditions, leading to decreased efficiency and low reliability of the motor during continuous operation, thus enabling the motor to adapt to forklift operation requirements.

The application discloses a kind of environment simulation method and system based on binocular stereo vision measurement, it is related to scene simulation technical field, and its technical solution points are: the method includes by constructing the physical imaging model in left and right optical elements in binocular stereo vision camera, and left and right view is obtained based on the physical imaging model;Determine the disparity map between the left and right view, determine scene depth image based on the disparity map;Three and more scene depth images generated by three and more different binocular stereo vision cameras corresponding to the scene are acquired, and the three and more scene depth images are fused, to construct the three-dimensional simulation model corresponding to the scene based on the depth image after fusion.The application can accurately reflect the depth level and spatial relationship of scene, and the three-dimensional simulation model finally constructed is more realistic, and can strongly support virtual reality, three-dimensional measurement and other applications.

This invention discloses a supply chain management method and system based on adaptive optimization using traceable containers. The method collects multi-dimensional supply chain data in real time using standardized traceable containers, including inbound volume, outbound volume, inventory, transportation location, environmental parameters, and carbon emission estimates; calculates data volatility and reliability to determine the importance of data collection time; integrates target smoothing parameters and uses reinforcement learning to correct predicted demand; generates multimodal transport schemes using K-D tree matching and the dragonfly algorithm; optimizes production and transportation scheduling based on simulated annealing algorithm, embedding carbon footprint constraints to minimize total green costs; and forms an adaptive closed loop through container feedback to improve system robustness. This method achieves real-time tracking, adaptive optimization, and sustainable development of the supply chain, and is suitable for complex and ever-changing supply chain environments.

This application discloses an adaptive error correction method for cloth penetration, its system, electronic device, and storage medium, relating to the field of computer graphics processing technology. The method includes: when simulating the current frame image, performing physical calculations on the acquired initial data of the current frame image and the first simulation result of the previous frame image to obtain the initial physical simulation position of each cloth vertex in the current frame image; determining the penetration status of each cloth vertex by performing a heuristic detection-based state judgment based on the initial physical simulation position and character skeleton data; performing adaptive error correction compensation based on the penetration status of each cloth vertex and the initial physical simulation position to obtain the target physical position of each cloth vertex; and performing rendering simulation based on the target physical position of each cloth vertex to output a second simulation result of the current frame image. This method can improve penetration detection efficiency, reduce penetration detection cost, and improve the real-time simulation effect of cloth.

The present application relates to the technical field of flue gas waste heat recovery of thermal power generation, and provides a low-low-temperature coal economizer flue gas waste heat recovery device and system, which comprises a collection module for processing sensor signals to generate preprocessed data packets; a twin module for performing simulation based on the data packets to output a flow field atlas; an analysis module for evaluating the atlas to output a flow field uniformity index and a wear and corrosion risk distribution map; a coordination module for optimizing calculation with the three indexes as targets to output a set of deflector angle adjustment instructions; a regulation and control module for driving a deflector array to perform angle adjustment; and a monitoring module for identifying leakage based on humidity data and controlling an isolation valve. Through the construction of a main control closed loop of "perception-simulation-optimization-execution" and an independent leakage safety closed loop, dynamic shaping of the flue gas flow field, coordinated inhibition of the wear and corrosion risk, and rapid isolation of sudden leakage are realized, thereby improving the system operation reliability.

The application provides a simulation analysis method for compression deformation characteristics of a rubber pad, and relates to the field of rubber pad product testing. The application constructs a finite element grid model based on geometric parameters and initial material parameters of the rubber pad, identifies geometric singularity regions with displacement gradient mutation; applies a test loading load on the model, extracts displacement path curvature and performs gradient correction on material parameters, and constructs a local material constitutive relation; performs compression deformation simulation based on the local constitutive relation, analyzes strain energy accumulation sequence and determines an energy transmission control region; determines a dominant constraint mode in combination with the spatial corresponding relationship between the energy transmission control region and the geometric singularity region, and performs incremental correction on the simulation result, so as to realize accurate prediction of non-uniform compression deformation characteristics of the rubber pad.

One embodiment of a method for training a machine learning model to control a robot includes causing a model of the robot to move within a simulation based on one or more outputs of the machine learning model, computing an error within the simulation, computing at least one of a reward or an observation based on the error, and updating one or more parameters of the machine learning model based on the at least one of a reward or an observation.

This invention provides a general optimization method and system for water supply scheduling of parallel reservoir groups. By acquiring system operation data of the parallel reservoir group and its water supply network, a multi-level, multi-attribute generalized directed graph model is constructed. Based on this model, the dynamic operating state of the water resource network is dynamically generalized, and multiple objective functions and constraints are dynamically configured. Simultaneously, scheduling decision variables are identified and the degree of constraint violation is quantified, forming a generalized optimization problem definition. Different optimization algorithms are supported, and the optimization problem is solved in multiple cycles through a scheduling decision evaluation module. The TOPSIS method is used to select representative solutions, obtaining the optimal release decision for each reservoir in each scheduling cycle. Finally, the performance of the scheduling scheme is evaluated based on simulation results, and a detailed operation report is generated. This invention can effectively improve the scientific and economic efficiency of water supply scheduling of parallel reservoir groups, providing important technical support for regional water resource optimization scheduling and refined management.

The application provides a memristor measurement matrix determination method, device, equipment, storage medium and product. The method comprises the following steps: determining the maximum value of the candidate measurement matrix bit width according to the conductance deviation characteristics of the target memristor and the target compression ratio; obtaining the target bit width interval based on the least significant bit width corresponding to the target memristor and the maximum value; generating the candidate measurement matrix corresponding to each bit width in the target bit width interval based on the statistical distribution characteristics of the original measurement matrix; performing signal reconstruction simulation based on the preset noise simulation model corresponding to the target memristor and each candidate measurement matrix to obtain the signal reconstruction accuracy corresponding to each candidate measurement matrix; and taking the candidate measurement matrix with the highest signal reconstruction accuracy as the measurement matrix of the memristor array corresponding to the target memristor, so as to enable the memristor array to perform compressive sensing. The measurement matrix used can meet the actual situation of the operation of the target memristor, and overcome the negative influence of the device characteristics on the reconstruction accuracy of compressive sensing.

This specification provides a method, apparatus, device, medium, and program product for rendering flexible objects. The method includes: acquiring reference pose information for each bone point in the skeletal chain of the flexible object, wherein the constraint pose information of the endpoint bones is determined based on the pose of the connected objects of the endpoint bones; determining endpoint pose information based on the reference pose information of each endpoint bone; performing physical simulation based on the reference pose information of intermediate bones to obtain intermediate pose information, wherein the intermediate bones are bone points located between the endpoint bones; and rendering the flexible object based on the endpoint pose information of each endpoint bone and the intermediate pose information of the intermediate bones. This solution differentiates the processing of endpoints and intermediate bones, balancing precise control with physical realism, achieving accurate and natural flexible simulation. It can be widely applied to digital cultural products in the next-generation information technology fields such as games and virtual reality.

The present disclosure relates to methods, systems, and apparatus, including computer programs encoded on computer storage media, for simulating magnetic data. An example method includes obtaining electrical data of an organ of a subject. The method further includes generating current data corresponding to a current source based on the electrical data of the organ of the subject. The method further includes generating simulated magnetic data of the organ of the subject based on the current data corresponding to the current source. The method further includes taking an action based on the simulated magnetic data.

This invention provides an information processing device, an information processing method, and an information processing program that can provide a diverse virtual space participation-based mobility environment that takes into account the prediction of human behavior in relationships with others, i.e., interactions. [Solution] The information processing device comprises a measurement unit that measures the movement simulations of multiple users in real space and reflects the measured movement simulation results in a virtual space; a storage unit that stores the movement status of multiple users; a model generation unit that generates simulation model data based on the movement status and stored data; and a simulation execution unit that executes a simulation based on the model data reflected in the virtual space when multiple users participate in the virtual space using different means of transportation.

This invention relates to sales activity management and digital risk control technology, and discloses an intelligent early warning and control system for sales activity risks, enabling real-time, accurate, and automated insight and intervention in sales activity risks. The system includes: a data acquisition and processing layer, used to access multi-source heterogeneous sales-related data, perform standardized processing based on a predefined ontology library, extract entities and relationships, and construct and maintain a dynamic risk knowledge graph; a rule engine and intelligent analysis layer, used to perform graph neural network anomaly detection, adaptive threshold rule judgment, and risk diffusion simulation based on the dynamic risk knowledge graph, and output risk analysis results; an early warning triggering and grading layer, used to generate tiered early warning information based on the risk analysis results; and a visualization and interaction layer, used to visualize information and provide risk control configuration and query interaction entry points.

This application provides a Saber-based inverter simulation method, which includes: generating an initial simulation test circuit; performing time-domain simulation based on the initial simulation test circuit to obtain the total loss, switching loss, and conduction loss of the power device model; transforming the initial simulation test circuit to obtain a replacement simulation test circuit, and performing sensitivity testing on the obtained replacement simulation test circuit based on the total loss, switching loss, and conduction loss of the power device model to obtain the sensitivity of each initial curve; and adjusting the power device design based on the obtained total loss, switching loss, conduction loss of the power device model, and the sensitivity of each original curve. This method can guide the design of power devices and other parameters in the circuit, effectively improving R&D efficiency and quickly achieving the goals of improving inverter efficiency, reducing losses, and meeting system efficiency requirements.

This invention relates to the field of computer-aided design technology, and more particularly to a method and system for constructing wind dams for concentrated wind energy capture. The method includes the following steps: acquiring multi-source wind field data; processing the multi-source wind field data to obtain wind field structure data; generating a guiding structure from the wind field structure data to obtain wind dam geometric structure data; performing fluid-structure interaction (FSI) simulation based on the wind field structure data and the wind dam geometric structure data to obtain FSI data; and performing multi-constraint dynamic optimization on the FSI data to obtain construction control strategy data. This invention achieves proactive guidance and efficient matching of the wind dam structure to airflow convergence behavior, improving the efficiency of concentrated wind energy capture and the reliability of structural design. By using a surrogate model and multi-constraint dynamic optimization, the highly complex simulation process is transformed into a rapidly reasoning-based decision-making process, effectively reducing computational costs.

This utility model discloses a novel shaftless pump-driven river algae experimental device, relating to the field of aquatic ecological simulation and early warning prediction technology. It includes an experimental water tank, a propulsion pump, and vortex-generating impellers. The experimental water tank has a ring-shaped structure, with a filling space at the bottom for filling with substrate and a water passage at the top. The propulsion pump is installed inside the experimental water tank to circulate the water within the passage. Multiple vortex-generating impellers are installed inside the experimental water tank to generate vortices in the water within the passage. This device can effectively simulate the hydrodynamics and aquatic environment of a real river in a closed loop, and is compatible with river ecological physics simulations based on water level differences. It offers advantages such as realistic simulation environment, minimal bubble turbulence, low background noise, and long-term algal survival friendliness, making it particularly suitable for experimental research on algae simulation, regulation, and early warning prediction.

This invention relates to a method for constructing a machine learning potential energy model based on hierarchical active learning, comprising the following steps: constructing a database of background solvent molecules and lithium salt molecules; initializing a machine learning potential energy model committee; outer active learning automatically exploring the chemical species composition space of the electrolyte, generating electrolyte formulations and initial structures; determining whether a structure needs to be included in the labeling range based on uncertainty calculations; automatically constructing a liquid phase environment based on classical force field simulation methods; performing high-precision simulations based on first-principles calculations and labeling the energy and force values ​​of the structures; inner active learning driving the machine learning potential energy model to explore the configuration space and label the energy and force values ​​of structures with high uncertainty; obtaining a first-principles structure database of the real liquid phase environment through several iterations; and training to obtain the final high-performance machine learning potential energy model. This invention systematically and comprehensively samples the chemical species composition space of the electrolyte and the molecular simulation configuration space based on hierarchical active learning, thereby ensuring the predictive performance and simulation accuracy of the machine learning potential model on unknown and complex electrolyte systems.