24 results about "Model equation" patented technology

Systems, methods, and computer-readable storage devices are disclosed for improving markerless motion analysis of an object in contact with a user. One method including: receiving position data of an object in motion captured by at least one camera; enhancing, using model equations, three-dimensional (3D) angular kinematic data of the position data of the object, wherein the enhanced 3D angular kinematic data includes increased measurement accuracy of the position data of the object; and providing the enhanced 3d angular kinematic data for display to evaluate motion performance of the object.

This invention provides a hybrid solution method for computational fluid dynamics software structural solvers. The method first determines whether some model equations employ a loosely coupled approach, specifying that the number of conserved quantities equals the number of tightly coupled conserved quantities. Then, it iteratively solves the problem block by block, successively solving both tightly coupled and loosely coupled equation sets. Finally, it merges the loosely coupled and tightly coupled conserved quantities until all grid blocks have been iteratively solved. This method simultaneously implements both tightly coupled and loosely coupled architectures within a single data structure, enabling the software to simultaneously achieve high solution accuracy, high efficiency, and scalability.

The present invention relates to a biological control method and system, a computer program product and a computer-readable storage medium relating to a given area, preferably a given agricultural area, wherein the aim of the invention is to determine the number of biocontrol agents to be introduced into the given area, the frequency with which the biocontrol agents are to be introduced into the given area, and the period during which the biocontrol agents are to be introduced into the given area, by means of a model equation, the model equation applying a mathematical relationship to at least one item of biological modelling data and to at least one item of ecological modelling data, the implementation thereof comprising the use of at least one item of user data.

A method for predicting electromagnetic performance of a three-dimensional structure unit cell configuration and an impedance matching design method, the prediction method comprising: experimentally measuring the basic electromagnetic parameters of the lossy material used in the three-dimensional structure unit cell configuration, assuming that the lossy material is an isotropic medium, and calculating the equivalent electromagnetic parameters of each layer of the configuration according to the duty cycle; calculating the fractal dimension of the whole three-dimensional structure unit cell configuration and determining the duty cycle and thickness of each layer of the three-dimensional structure unit cell configuration; constructing a structure resonance effect factor by using the basic electromagnetic parameters of the lossy material, the fractal dimension and the duty cycle, and then correcting the impedance gradient correction coefficient; and establishing a model equation of the macroscopic equivalent physical characteristic parameters of the structure interface, and calculating the interface wave impedance and surface reflectivity of the three-dimensional structure unit cell configuration by using the model equation. The theoretical and simulation calculation absorption peak frequency points are basically consistent, the macroscopic equivalent calculation method can accurately predict the absorption peak frequency point position, and the effectiveness of the calculation method is illustrated.

To provide a gaming information management system that can fairly evaluate each gaming establishment with different cost ratios. [Solution] The game information management system 1 is a system that includes a management server 1A that collects operational data from each game machine 2 installed in multiple game halls and creates game information, and a mobile terminal 5 that can access the management server 1A and view the game information. The management server 1A generates a model equation by multiple regression analysis using operational data and cost rates of each game machine 2 collected from game halls where gross profit amounts can be collected, and calculates an approximate gross profit that eliminates the influence of cost rates by substituting operational data and cost rates of each game machine 2 collected from game halls where gross profit amounts cannot be collected into the model equation, and creates game information related to the approximate gross profit.

An online system for predicting the removal rate of pollutants in sewage based on a subsurface infiltration process comprises a plurality of pollutant index front-end pages, and each page is composed of a measured data module, a prediction module, a response curved surface module, a data interaction module and a difference analysis module. The actual measurement data module records site physical parameters and pollutant removal rates in a form, and a pollutant model equation is constructed according to the site physical parameters and the pollutant removal rates; the prediction module is embedded into the model equation and realizes removal rate prediction through a parameter input window; the response curved surface module can adjust physical parameters and update a response curved surface diagram in real time; the data interaction module stores predicted and actually measured data and improves the data utilization rate; the difference analysis module generates an error analysis chart based on the stored data, and visually presents the difference between the actually measured data and the predicted data. According to the method, the pollutant removal rate in subsurface infiltration can be predicted, and the problems of difficulty in sampling and monitoring in actual engineering, imperfection of basic electric power facilities and low utilization rate of water quality monitoring data are solved.

The invention discloses an electromagnetic performance prediction method and impedance matching design method of a three-dimensional structure unit cell configuration, and the prediction method comprises the steps: carrying out the experimental measurement of basic electromagnetic parameters of a loss material used by the three-dimensional structure unit cell configuration, supposing that the loss material is an isotropic medium, and calculating the equivalent electromagnetic parameters of each layer of material of the configuration according to the duty ratio; calculating fractal dimensions according to the whole three-dimensional structure unit cell configuration, and determining the duty ratio and the thickness of each layer of the three-dimensional structure unit cell configuration; constructing a structural resonance effect factor through the basic electromagnetic parameter, fractal dimension and duty ratio of the loss material, and further correcting an impedance gradient correction coefficient; and establishing a model equation of the macroscopic equivalent physical characteristic parameters of the structural interface, and calculating the interface wave impedance and the surface reflectivity of the unit cell configuration of the three-dimensional structure by using the model equation. The absorption peak frequency point position obtained through theory and simulation calculation is basically consistent, the absorption peak frequency point position can be accurately predicted through the macroscopic equivalent calculation method, and the effectiveness of the calculation method is explained.

The invention relates to an MOSFET mismatch parameter automatic extraction method, which belongs to the technical field of integrated circuit device simulation, and comprises the following steps: unifying a mismatch parameter expression in a model card, and establishing a mismatch model equation; determining a device model size sequence; sequentially arranging according to the area of the device model to obtain a device size array sequence; setting a mismatch parameter array sequence and mismatch parameters contained in each mismatch parameter array; and according to the sequence of the size array sequence and the sequence of the mismatch parameter array, extracting a final value of the mismatch parameter by adopting a global optimization simulation iterative algorithm. According to the method, the loss function is minimized by adjusting the mismatch parameters, so that the globally optimal solution is solved, the optimal mismatch parameters are extracted, the convergence efficiency is improved by adopting the global optimization method, and the operation overhead is reduced.

This invention provides an online dynamic load identification method based on a disturbance observer. First, a structural state-space equation is established based on the mass matrix, damping matrix, and stiffness matrix of the linearly loaded structure. Then, the state-space equation of the loaded structure is compared and combined with the model equations in the control domain to design and determine the form and parameters of the disturbance observer characterized by the state-space equation parameters of the system model. This observer is then applied to the real-time online identification of external dynamic loads on the structure. By observing the difference between the actual output response and the estimated output response of the system in real time, the observer gain k is gradually adjusted until the estimated value approximates the actual input dynamic load. This method eliminates the need for complex design and extensive calculations, enabling accurate real-time identification of random dynamic loads on single-point / multi-point linearly loaded structures. It solves the problems of large solution errors and slow computation caused by matrix inversion operations in existing dynamic load identification technologies.

The invention discloses a regional water body pollutant source analysis method and system, and the method comprises the steps: calculating a corresponding scene feature index based on the input of multi-dimensional data, and carrying out the scene type judgment. Then, constructing a steady-state fugacity model of a four-medium system comprising a water phase (W), sediments (S), land soil (L) and ambient air (A), and establishing a mass balance equation set of the steady-state fugacity model; and in combination with a scene classification result, solving the model equation by adopting a Bayesian inversion method, and simultaneously inverting the emission source intensity, the non-advection input flux and the advection input concentration of each medium on the basis of the migration matrix and the fugacity capacity of the model equation. The system comprises a data acquisition module, an index calculation module, a scene classification module, an equation construction module and an inversion module. By using the method, the flux of each medium discharge source and advection input is synchronously inverted, and pollution traceability is realized. The method can be widely applied to the field of pollution analysis.

The application discloses a method for generating NURBS curve and surface fairing in vehicle shell modeling. A model equation of a fitting parameter model is known, data points are obtained through data collection of reverse engineering of vehicle shell modeling, a node vector of the model equation is obtained after parameterization, initial control points are selected, and the fitting parameter model is generated from the control points and the node vector of the model equation; the fitting parameter model and the control points are iteratively optimized according to actual requirements of the fairing effect of the vehicle shell modeling, and the optimal fitting parameter model is obtained. The application realizes accurate fairing of the curve and surface by adjusting the fairing weight corresponding to the control points, and improves the flexibility and interactivity of the fairing operation. Meanwhile, the geometric iterative process ensures that the user can globally or locally modify the weight of the control points, the node vector or the data parameterization, etc. after each iteration.

The present invention relates to a method, a biological control system, a computer program product, and a computer-readable recording medium for a specific area, preferably a specific agricultural area. The object of the invention is to determine the number of biocontrol agents to be introduced into the specific area, the frequency of introduction of the biocontrol agents into the specific area, and the period of introduction of the biocontrol agents into the specific area by means of a model equation, said model equation applying a mathematical relationship to at least one biological modeling parameter and at least one ecological modeling parameter, said implementation including the use of at least one user parameter. Abstract figure: 1

The present application belongs to the vertical earthquake evaluation technical field, disclose a kind of vertical earthquake action evaluation method based on random effect method, including S1, the ground motion record dataset of southwest region is established;S2, determine as basic input seismic parameter;S3, determine the model equation capable of fully reflecting the V / H spectrum value variation law of target area;S4, the model equation in S3 is carried out multiple nonlinear regression fitting using random effect method;S5, according to the vibration data set established in S1 as training set, combined with the mixed effect expression fitting in S4 coefficient in S3, i.e. the V / H spectrum value model of southwest region is obtained;The present application takes magnitude, fault type, site condition, distance, focal depth as variable, and adopts random effect method to propose V / H spectrum value model suitable for southwest region, to reasonably evaluate the vertical earthquake action of the region.

A modeling method of a surface potential-based GaAs process pHEMT compact model comprises: establishing a surface potential-based GaAs pHEMT compact intrinsic model; establishing a surface potential-based GaAs pHEMT compact extrinsic model; combining the physical structure and behavior mechanism of the GaAs pHEMT device, and establishing a compact model and a model topological structure based on intrinsic and extrinsic model equation architectures; describing the surface potential-based GaAs pHEMT compact model by using a Verilog-A language; and giving a compact model parameter extraction method. The method solves the problems that the existing GaAs PHEMT model is difficult to describe the characteristics of a complex and non-uniform surface potential function, the approximate solution is inaccurate, and the channel charge model equation is discontinuous and cannot be used for nonlinear circuit simulation.

The invention relates to the technical field of fluid mechanics, in particular to a method for constructing a high-pressure fluid model, which comprises the following steps: acquiring multi-scale fluid data including molecular dynamics data, experimental scale data and in-situ detection data; migrating the medium-low pressure domain data to an ultrahigh pressure domain through a pressure grading migration learning network, and outputting a physical property parameter prediction value; receiving in-situ data in real time based on embedded hardware, and calculating a correction factor; dynamically reconstructing a fluid control equation source item based on the correction factor; and when the average relative error exceeds a threshold value, triggering a reinforcement learning optimizer to reconstruct a model equation. The invention aims to provide the construction method of the high-pressure fluid model, the computer equipment and the storage medium, solves many problems in the prior art, shows remarkable advantages in the aspects of accuracy, real-time performance and adaptability of the fluid model, and provides powerful technical support for research and application in related fields.

The present invention relates to a method for a data-based generation of time series for parameter optimization, wherein, for a crash test, a model equation is available which has several parameters and describes a physical measured quantity, relating to the behavior of a vehicle component subjected to the crash test.The vehicle component is adapted according to an optimization criterion by measuring the physical quantity to be described for the vehicle component by the model equation and storing it in a measurement data set; subjecting the measurement data set to a principal component analysis and limiting principal components to a number P; forming a multivariate probability function over the P principal components; generating P new principal components from the multivariate probability function using a predefined sampling procedure; back-transforming new time series using the P new principal components and storing them; and calculating the parameters of the predefined model equation based on the measured and the new time series.This reduces the variance of a model statement due to the increased number of time series and makes it more precise to adapt at least one vehicle component to the optimization criterion.

Systems, methods, and computer-readable storage devices for improving label-free motion analysis are disclosed. One method includes: receiving positional data of joint centers of a moving body captured by at least one camera device; enhancing the positional data of the joint centers of the body with three-dimensional (3D) angular kinematic data using model equations, wherein the enhanced 3D angular kinematic data includes increased measurement accuracy of the positional data of the joint centers of the body; and providing the enhanced 3D angular kinematic data for display to evaluate motion performance.

The application discloses a flow field parameter determination method, device and equipment for full-basin gas flow and a storage medium, relates to the technical field of full-basin axisymmetric flow calculation, and comprises the following steps: establishing and decoupling Boltzmann model equations to obtain each sub-equation, i.e., a nonlinear source term sub-equation, a convection motion sub-equation and an axisymmetric source term sub-equation; analytically solving the nonlinear source term sub-equation to obtain a molecular velocity distribution function value; taking the value as an initial value, solving the convection motion sub-equation by using a finite volume method to obtain a first distribution function value; taking the value as an initial value, solving the axisymmetric source term sub-equation by using the finite volume method to obtain a second distribution function value, integrating the second distribution function value to obtain a current flow field macroscopic parameter, and judging whether convergence is achieved; if convergence is not achieved, the nonlinear source term sub-equation is updated, and the above steps are repeated until convergence is achieved, so that the target flow field macroscopic parameter is obtained, and the efficiency of determining the full-basin axisymmetric flow field parameter is improved.

The invention provides a ferroelectric field effect transistor modeling and simulation method, device, equipment and medium, and the method comprises the steps: building a coupling equation system for describing a key physical quantity incidence relation among ferroelectric layer polarization, interface trapped charges and potential distribution, and enabling the equation system to comprise a charge conservation equation introducing a trapped charge density item; when charge trapping occurs in an interface trap and trap trapped charge evolution is caused, a charge conservation equation is fed back to act on the ferroelectric layer, redistribution of effective field intensity in the ferroelectric layer is caused, and change of polarization overturning dynamics is induced; setting fixed parameters of adapter device characteristics, and configuring simulation pulse waves including the whole process from pre-pulse and covering device writing to reading; and according to the set simulation parameters, on the basis of the constructed model equation, the configured pulse waveform and the fixed parameters, through a self-consistent iterative algorithm in combination with charge conservation conditions, determining the relationship of source-drain current changing with grid voltage, and realizing electrical property simulation of the FeFET device.

A method includes generating, by a SEM, sets of frames corresponding to regions of a microfabrication pattern, for each set of frames, estimating feature data representing edge positions, linewidths, or centerline positions of one or more features of each region of the pattern, and computing a preliminary estimate of a roughness parameter from the feature data. The roughness parameter is indicative of a line edge roughness, a linewidth roughness, or a pattern placement roughness of the one or more features. The method further includes fitting a model equation to the preliminary estimates of the roughness parameter using a model parameter dependent on the number of frames of each set of frames, the model equation relating the model parameter to the roughness parameter; and computing a final estimate of the roughness parameter as an asymptotic value of the fitted model equation.

This invention relates to a method for identifying parameters of a second-order model of a decentralized electric heating load. Its key feature is that it obtains the wall temperature T for model parameter identification through a second-order equivalent thermal parameter model equation. e (t) and indoor temperature T i The calculation formula for (t) was derived, and model parameters were identified. Through the determination and acquisition of model parameters, setting constraints and initializing model parameters, calculating fitness, and updating the particle swarm population, the globally optimal parameters were determined. This model has the advantages of good stability and high accuracy, and can obtain relatively accurate model parameters in a short time. It establishes a decentralized electric heating load model that can accurately predict users' indoor temperatures, providing a good model foundation for decentralized electric heating loads to participate in grid regulation.

Provided in the present invention is a maintenance resource global configuration optimization method for a cross-domain multi-level safeguard network. The method comprises: on the basis of the topological structure of a safeguard network and the relationship, distance and traffic time between sites, proposing a maintenance resource inventory optimization mathematical problem; defining input and output parameters of the optimization mathematical problem; on the basis of the input parameters, constructing model equations for a maintenance resource transfer system, and providing mathematical expressions for the output parameters; when there is one resource in the system, calculating a site at which the resource should be configured; and repeating such calculation, confirming an optimal site of a k-th resource after the configuration of a (k-1)th resource has been completed, until the total number of resources reaches an input value of the system, ending the configuration, then providing a graph indicating that the total delayed delivery quantity decreases as the total inventory quantity increases, and confirming the optimal total inventory quantity. In the present invention, the number of maintenance resources between sites can be allocated on the basis of a safeguard network, so as to ensure that the overall time and cost of resource scheduling of the entire safeguard network are optimal when a fault occurs randomly.

The invention relates to the technical field of motor control, in particular to a model-free self-adaptive motor control method for reinforcement learning driving, which comprises the following steps: firstly, acquiring three-phase current of a motor, converting to obtain dq-axis current, calculating feedback rotating speed through an observer, filtering, and outputting q-axis reference current through PI regulation; a model equation is reconstructed and discretized, an observation gain coefficient is determined, dq-axis reference voltage is calculated and subjected to delay compensation correction, and the dq-axis reference voltage is input into an SVPWM module to generate PWM waves to drive a motor; and meanwhile, a discretization state space, an action space and a reward function are constructed, and control parameters are dynamically optimized through collaborative updating of the strategy network and the Q network. According to the method, parameter dependence is greatly reduced, parameter adaptive optimization is realized, rotating speed tracking speed, current harmonic suppression and energy consumption saving are considered, scenes such as a frequency conversion base station and a small and precise air conditioner are adapted, and control stability and batch adaptation efficiency are improved.

This invention relates to the field of fluid mechanics, specifically to a method for constructing a high-pressure fluid model. The method includes: acquiring multi-scale fluid data, including molecular dynamics data, experimental-scale data, and in-situ detection data; transferring data from the low- and medium-pressure domains to the ultra-high-pressure domain using a pressure-gradient transfer learning network, and outputting predicted values ​​of physical property parameters; receiving in-situ data in real time using embedded hardware and calculating correction factors; dynamically reconstructing the source terms of the fluid control equations based on the correction factors; and triggering a reinforcement learning optimizer to reconstruct the model equations when the average relative error exceeds a threshold. The purpose of this invention is to provide a method, computer equipment, and storage medium for constructing a high-pressure fluid model, solving many problems in the prior art and demonstrating significant advantages in the accuracy, real-time performance, and adaptability of the fluid model, providing strong technical support for research and applications in related fields.