26 results about "Newton's method" patented technology

The invention discloses an auxiliary power device modeling method based on fuzzy set intelligent optimization. The method comprises the following steps: firstly, establishing models of all parts of the APU according to an aerodynamic thermodynamic law, and constructing a common working equation set; then, the particle swarm optimization process is divided into four typical states of exploration, depth, convergence and local optimum, and the current state is identified in real time by using a fuzzy estimator. And on the basis, optimizing hyper-parameters such as inertia weight, cognitive coefficient and social coefficient are adaptively adjusted according to the recognition state. And finally, taking a residual weighted least square function with a quadratic penalty term as a fitness index, and driving a particle swarm to solve an equation set. According to the method, through the state recognition and parameter self-adaption mechanism, the defects that a traditional Newton method is high in dependency on an initial value and a basic particle swarm algorithm is prone to falling into local optimum and slow in convergence are effectively overcome, and efficient and steady solution of the APU model is achieved.

The application belongs to the technical field of power systems, and discloses an EIGD time-delay power system stability analysis method and device, wherein the method comprises the following steps: a linear model of the time-delay power system is established, and the differential equation in the model is converted into an abstract Cauchy problem by using an infinitesimal generator; a group of discrete points is selected for each time-delay interval of the time-delay power system, a discrete function space is established according to the discrete points, and the time-delay variable is discretized to generate a low-order partial infinitesimal generator discretization matrix; displacement and inverse transformation are performed on the discretization matrix to obtain an inverse matrix, and the characteristic value of the system is obtained according to the inverse matrix; the characteristic value is checked by using the Newton method to obtain the accurate characteristic value and the characteristic vector, and the stability of the time-delay power system is analyzed and judged. The method solves the problem of large matrix LU decomposition calculation amount in the existing EIGD time-delay power system characteristic value sparse calculation method based on the DDAE model.

The invention belongs to the field of machinery, and particularly relates to a tooth surface friction calculation method based on a mathematical programming algorithm. The objective of the invention is to solve the problem of low calculation efficiency of the existing numerical analysis technology for the gear contact problem. According to the tooth surface friction calculation method based on the mathematical programming algorithm, the problem scale is greatly reduced through substructure static condensation, and the high efficiency of the mathematical programming algorithm (the smooth Newton method) is combined, so that the leap of the calculation speed is achieved. In addition, according to the method, a mechanical problem is creatively converted into a mathematical programming problem, and a brand new technical path is provided. The method is not only suitable for straight teeth, helical teeth and herringbone gears, but also can be popularized to friction contact analysis of other mechanical connection pairs (such as splines and bearing raceways) in theoretical framework. The whole process from parametric modeling, data exporting to model solving can achieve high automation through scripts, human intervention is reduced, and the repeatability of results is guaranteed.

The invention discloses a load flow calculation method, system and device based on quantum singular value transformation and a medium, and belongs to the technical field of load flow calculation, and the method comprises the steps: obtaining the initial power parameter of each node of a power system and the given power of each node, and determining the power unbalance amount; constructing a node admittance matrix according to the initial power parameters, constructing a correction equation of Newton method load flow calculation, and converting the correction equation into a linear equation set for expression; coding the coefficient matrix into a unitary matrix by using block coding, and executing polynomial transformation based on quantum singular value transformation to construct a quantum circuit representing an inverse matrix of the unitary matrix; encoding the power unbalance amount into a quantum initial state, and enabling a quantum circuit to act on the quantum initial state and performing measurement; and determining the correction of the node voltage based on the measurement result, judging whether to iterate based on the convergence condition, and outputting a load flow calculation result. By utilizing the characteristics of quantum parallelism and quantum singular value transformation, the time consumption of large-scale power system load flow calculation is remarkably reduced.

This patent discloses a method for solving corridors in short vertical propulsion systems. Addressing the convergence problem caused by improper initial value selection during corridor solving, this method selects a known feasible control plan as the initial value, ensuring model convergence within this plan. Then, it gradually expands the search range to avoid non-convergence due to initial value selection. To address the slow solution speed of traversal and optimization methods, this scheme transforms the optimization problem into an equation-solving problem, utilizing the second-order convergence property of Newton's method to achieve high-precision and rapid solution of corridor boundaries.

The application discloses an OTFS sensing integrated signal super-resolution target parameter estimation method for a synchronization error problem, which firstly establishes an OTFS time delay-Doppler domain sensing signal model considering timing offset and carrier frequency offset, and constructs a sparse observation model considering synchronization error; subsequently, a rough estimation of target time delay-Doppler parameters is completed through an ADMM algorithm, and the system synchronization error parameters are iteratively updated simultaneously by adopting an alternating minimization framework; then, multi-target interference cancellation is carried out based on the rough estimation result, and a Newton method is used to perform super-resolution fine estimation on target off-grid offset and synchronization error residual, so as to finally output fine parameters of target distance and velocity and a synchronization error estimation value. The application effectively solves the parameter estimation deviation problem caused by the synchronization error in the OTFS sensing system, and improves the estimation performance in the multi-target and closely adjacent target scene.

The application relates to a time-optimal three-axis reorientation method and device for an inertia-symmetrical rigid spacecraft, which determines an angular velocity analytical expression according to inertia symmetry of the spacecraft and a time-optimal control switch structure set in advance; through introduction of a new inertia axis coordinate system, the symmetry characteristic of a reorientation track is explicitly derived; a Radau pseudo-spectrum discrete method is used to discretize a quaternion dynamic equation, so that the time-optimal reorientation problem is converted into a nonlinear programming problem; through given two parameter values, the discretized quaternion dynamic equation is converted into a linear equation set and is solved, a discrete quaternion value sequence obtained through decomposition is used, a gradient method or a Newton method is used to optimize the two parameters, and a time-optimal reorientation track is determined according to an optimization result. The method does not need to perform numerical integration or solve a large-scale nonlinear programming problem, and the calculation efficiency is significantly improved, so that fast and accurate track generation of an inertial rigid spacecraft is realized.

The invention belongs to the technical field of aero-engine modeling, and particularly relates to an engine model solving method adopting Newton-Raphson and feedforward neural network methods. According to the method, a mixed algorithm of a feed-forward neural network agent model and a Newton-Raphson method is combined, and a rough value of an iteration independent variable is directly predicted by adopting a feed-forward neural network, so that meaningless and local extremal regions on an iteration path can be avoided to a great extent, and high-quality iteration variables are quickly provided for the Newton-Raphson method; the convergence capability of the Newton method is greatly improved, the iteration step number is reduced, and the calculation speed of the Newton method is improved. And a normalized training set processing mode is adopted, so that the training set scale and the network scale are greatly reduced, the network estimation precision is improved, and the application complexity of the hybrid solving method is reduced. According to the hybrid solving method, the simulation solving convergence of the violent dynamic process of the dynamic real-time model of the engine is remarkably improved, and compared with a gradient method, the calculation speed is increased.

The present application relates to the technical field of flood control optimal scheduling, in particular to a reservoir group flood control optimal scheduling method and system based on quadratic programming, the method comprising the following steps: according to the water conservancy facilities and hydrological elements in the basin, the system sorts out the spatial distribution of key nodes and their hydraulic connection, constructs a flood control scheduling topological network, and obtains a reservoir group flood control optimal scheduling topological graph; a reservoir group flood control optimal scheduling quadratic programming model is established according to the reservoir group flood control optimal scheduling topological graph; based on the MINOS library of GAMS, the least gradient method and quasi-Newton method are used to optimize and solve the reservoir group flood control optimal scheduling quadratic programming model. The present application couples the propagation of flood between reservoir groups in the mathematical equation set, avoids complex simulation sequential coding, is easy to model, has good universality, and the model is easy to seek an optimal solution, can balance the reasonable scheduling of the flood control capacity, peak shaving effect and reservoir storage capacity of the reservoir, and improve the accuracy and efficiency of flood regulation.

The invention discloses a multi-body virtual power plant collaborative optimization scheduling method, system and device and a medium. The method comprises the steps that related parameters of a virtual power plant system are acquired to construct a multi-body virtual power plant model; taking each subject in the virtual power plant system as an independent decision-making player through a state game potential algorithm, obtaining a state space, an action variable and a state transfer function of each subject, and constructing a state potential game model; and solving the state potential game model through a modified Newton method and a particle swarm algorithm, and carrying out continuous interactive iteration to obtain an optimal cooperative scheduling strategy of each main body of the final virtual power plant system. According to the method, multi-subject decision-making equality and privacy protection are realized, flexible load optimization is realized, unified optimization modeling of multiple types of subjects is supported, the algorithm is distinct in hierarchy and high in convergence, the collaborative regulation and control level of multi-type subject resources of the virtual power plant is effectively improved, double improvement of system economic benefits and scheduling fairness between subjects is realized, and the method is suitable for large-scale popularization and application. And technical support is provided for actual operation of the virtual power plant.

The application relates to an intelligent power regulation method and device based on temperature stability, wherein the intelligent power regulation method comprises the following steps: collecting temperature data of a device to be monitored at equal intervals in real time, calculating a stable temperature data proportion in a detection period, and if the stable temperature data proportion is less than a preset proportion, performing regression calculation on all power-temperature data in the detection period to obtain a power-temperature function F; obtaining a target temperature value T target constructing an iterative function f; according to the current power P N iterative root seeking is performed on the iterative function f to obtain a target power, and the device output power is adjusted according to the target power; based on the iterative idea of the Newton method, the application realizes fast approximation of the target power in the power regulation process, realizes high-precision control of temperature stability and power output, does not need manual intervention, and improves experimental efficiency and result stability.

The invention relates to the technical field of geophysics, in particular to a high-speed rail seismic source wavelet estimation method and system for full waveform inversion. The method comprises the steps that unit impulse response data and high-speed rail seismic source vibration data are acquired, and forward modeling calculation is conducted on the unit impulse response data and the high-speed rail seismic source vibration data through a finite difference method to obtain unit impulse response signals and high-speed rail seismic source vibration signals. According to the method, simplified modeling is carried out on a high-speed rail vibration source running on a viaduct, a train is equivalent to a plurality of moving point force sources excited at piers, a vibration source function formed by delay superposition of a plurality of axle load functions is constructed, and the spatial and temporal variation characteristics of high-speed rail vibration are accurately described. In the frequency domain, the Newton method is utilized to directly solve the real part and the imaginary part of the seismic source wavelet, and an objective function has a linear characteristic, so that an analytical solution can be obtained in one step, the iterative convergence problem is avoided, and the calculation cost is remarkably reduced.

The invention relates to a structure damage identification method of a quasi-Newton iteration nonlinear RCD class algorithm, and the method comprises the following steps: S1, extracting modal parameters of a structure before and after damage, and building a mathematical model of the structure according to the extracted modal parameters; s2, performing second-order sensitivity analysis on the structural model, analyzing the influence of structural parameter change on structural response, and establishing a nonlinear sensitivity equation based on a sensitivity analysis result; s3, constructing a linear optimization model for damage identification by utilizing the nonlinear sensitivity equation obtained in the step S2 and combining a sparse regularization method; on the basis of the constructed optimization model, proposing an optimization algorithm for solving the model; s4, solving an NIT omega-RCD theta algorithm based on the nonlinear optimization model in the step S3 in combination with a Broyden rank-1 correction Newton method and an RCD type rapid optimization algorithm; the problems that an existing linear model cannot fully consider the nonlinear characteristics of the structure, the recognition result is likely to be inaccurate, and the damage recognition reliability is affected are solved.

This invention relates to the field of evaporative cooling technology and discloses a method for calculating the circulating flow rate of a wind turbine evaporative cooling system. The method includes: simplifying the geometric structure of the wind turbine evaporative cooling system by equivalent means, reducing the multi-channel evaporative cooling loop to a closed loop composed of n parallel heating channels; establishing a two-phase fluid dynamics model based on a one-dimensional homogeneous equilibrium model to obtain the calculated relationships of pressure drop, frictional resistance, and two-phase flow parameters for each heating channel; expressing the pressure drop equilibrium condition of each heating channel as an implicit nonlinear equation set in the two-phase fluid dynamics model, and obtaining the mass flow rate solution using an iterative solution method; and employing a hybrid solution strategy combining particle swarm optimization (PSO) and Newton's method to calculate the circulating flow rate. This invention combines PSO and Newton's method to form a two-stage hybrid solution strategy, which is an effective way to solve the problem of multiple solutions for the circulating flow rate of evaporative cooling systems.

The application discloses a multi-region power system scheduling method based on Newton method approximate dynamic programming, and comprises the following steps: S1, a multi-region power system scheduling model is constructed, a power system scheduling cost minimization is taken as an objective function, the multi-region power system scheduling model is divided into a plurality of regional sub-models, and a value function of each regional sub-model is determined; S2, the value function of each regional sub-model is subjected to second-order Taylor expansion based on the Newton method, and an approximate value function of each regional sub-model is obtained; S3, derivatives of the approximate value function of each regional sub-model in the multi-region power system scheduling model are calculated, and a second-order derivative matrix and a first-order derivative matrix of the approximate value function of each regional sub-model are obtained; S4, an approximate dynamic programming method based on the Newton method is adopted to update the approximate value function of each regional sub-model, an optimal scheduling strategy of the multi-region power system scheduling model is obtained, and the power system is scheduled according to the optimal scheduling strategy. The solving speed and accuracy are improved.

The application relates to an overhead line stress calculation method based on a hyperbolic function method, which comprises the following steps: constructing an overhead line stress state equation; calculating the value of an intermediate parameter through the overhead line stress state equation; when the intermediate parameter is greater than or equal to 0, converting the stress state equation into a hyperbolic sine function, further converting the hyperbolic sine function and obtaining a stress initial value, and then according to the stress initial value, using Newton's method to iteratively obtain a to-be-solved working condition stress value; when the intermediate parameter is less than 0, converting the stress state equation into a hyperbolic cosine function, further converting the hyperbolic cosine function and obtaining a stress initial value, and then according to the stress initial value, using Newton's method to iteratively obtain a to-be-solved working condition stress value.

The application provides a multi-point approximation method based on an approximate Hessian matrix for structure optimization, comprising the following steps: step 1, establishing a finite element model of a spacecraft based on an initial design of a spacecraft structure; step 2, performing mechanical prediction of the spacecraft, and the analysis mode comprises static analysis, modal analysis, buckling analysis and transient response; step 3, establishing a structure optimization mathematical model, namely, defining an optimization target, a constraint function and a design variable; step 4, establishing a sequence approximation problem considering second-order information to approximate the original problem; step 5, estimating the Hessian matrix of the multi-point approximation function by using a quasi-Newton method; step 6, selecting known points by using a neighborhood selection strategy based on the Euclidean distance; step 7, establishing convergence discrimination and an automatic optimization system; step 8, method comparison, analysis and iteration explicitness; and setting an optimization example to illustrate the flow from spacecraft design to analysis and then to optimization, and the effectiveness is verified by comparing the results of the optimization method with those of a commercial software.

The application discloses a multi-focus image fusion method and system based on a semi-smooth Newton method, and belongs to the technical field of image processing. The semi-smooth Newton algorithm is used for solving, a proximal operator and a generalized Jacobian matrix are introduced, and the optimization solving process is expanded into a deep network. An adaptive feature iterative reconstruction unit is designed, auxiliary variable updating, a learnable edge convolution, focus gradient perception and a multi-scale frequency enhancement structure are integrated, and iterative optimization is realized in combination with a feature reconstruction block, a multiplier updating module and a matrix updating module. The second-order optimization algorithm is introduced into multi-focus image fusion for the first time, has physical interpretability and strong feature learning capability, and has better fusion effect than existing methods, and has important application value in high-precision imaging fields such as microscopy and remote sensing.

A model prediction-based control method for grid forming of multi-port autonomous reconfigurable solar plants includes: estimating and predicting system parameters by establishing a multi-port autonomous reconfigurable solar plant and a dynamic model of a synchronous generator model; converting an objective function into an unconstrained optimization problem, using Newton's method to achieve minimum computational burden within each calculation time step to find a solution in real time for obtaining an optimal angular frequency; based on results of the optimal angular frequency, updating an output voltage and a dq-axis current of the multi-port autonomous reconfigurable solar plant, and changing an arm modulation index of the plant, thereby realizing the plant's inertia and primary frequency modulation support. The model prediction-based control method provided by the present invention achieves rapid prediction during operation and improves frequency response, rapidity and system stability.

The disclosed 2-D resistance tomographic imaging method optimizes computation speed for performing electrical impedance tomography using a model-space with a minimal number of orthonormal polynomial basis functions to describe discernable features in the 2-D resistance tomographic image, determining a minimal number of contacts to take fewer measurements than available information based on the number of basis functions, selecting a subset of rows of a matrix of calculated sensitivity coefficients to form a square Jacobian matrix for a linearized forward problem to be solved and inversion of the linear forward problem, and solving an inverse problem based on the square Jacobian matrix by performing at least one iteration of a Newton's method solve.

The application discloses a kind of complex ventilation network solving method and solving device, it is related to mine ventilation technical field;In the method of the application, node wind pressure equation set and its auxiliary equation, fan wind pressure characteristic function etc. are unified as a generalized matrix equation, the composition of the equation, independent variable and dependent variable vector, jacobian matrix etc. are defined, so as to realize direct solution using Newton method, and the amount of programming is small;Since the number of equation and the number of independent variable are not limited by the method, as long as the number of the two is related, therefore, by adding fan wind pressure characteristic function, direct solution of wind network can be realized when fan operating point is not fixed;By adding auxiliary equation reflecting the parameter relationship of multiple inlet and outlet of wind network, direct solution of multiple inlet and outlet wind network can be realized.

The invention relates to a method for separating a nonlinear trend in a TWSA time sequence. Comprising the following steps: firstly, constructing an objective function containing a data fitting term and a joint smoothing penalty term based on original TWSA time sequence data; then, minimizing the objective function by adopting a Newton method to obtain a nonlinear trend curve; then, the non-linear trend curve is removed from the original TWSA time sequence data, and a trend-removed time sequence is obtained; and finally, performing spectral analysis on the detrending time sequence, and performing Fourier transform identification to obtain a periodic signal and a residual signal. Through a data-driven optimization framework, a globally continuous and high-order derivable nonlinear trend curve is directly extracted from an original TWSA time sequence, so that an artificial linearization hypothesis on the trend in the prior art is avoided. On the basis, the residual signals are further decomposed, high-precision trend, period and residual components are finally obtained, and high-quality input is provided for TWSA data reconstruction.

The invention discloses an electromagnetic transient packaging model interface calling method and a related device thereof, and the method comprises the steps: reading a to-be-simulated power system example input file, and reading the input and output port information of an electromagnetic transient packaging model interface from the file; the initialization stage function is operated, and initialization operation of the electromagnetic transient packaging model is called; an electromagnetic transient simulation program is started, and a control system equation is obtained according to the input and output relation of all elements of the control system; performing assignment according to the state matrix and the simulation initial value of each variable to obtain a control system overall solution equation standard formula, and calling a calculation stage function to construct a packaging model solution equation standard formula; an improved Newton method is adopted to solve the packaging model resolving equation standard formula, an output port signal value of the electromagnetic transient packaging model is updated according to a solving result, a termination stage function is called to release a memory, a log is updated, and operation of an interface of the electromagnetic transient packaging model is ended. According to the method, the calculation speed is increased, and the simulation time consumption is reduced.

The invention discloses a load flow calculation method, system and device based on quantum fast inversion and a medium, and belongs to the technical field of load flow calculation, and the method comprises the steps: obtaining the initial power parameters of each node of a power system and the given power of each node, calculating the power value of each node based on the node parameters, and combining with the given power to determine the power unbalance amount; constructing a node admittance matrix according to the initial power parameters, constructing a correction equation of Newton method load flow calculation, and converting the correction equation into a linear equation set for expression; coding the coefficient matrix into a unitary matrix by adopting block coding, and constructing a quantum circuit for representing an inverse matrix of the unitary matrix based on a quantum fast inversion method; encoding the power unbalance amount into a quantum initial state, and enabling a quantum circuit to act on the quantum initial state and performing measurement; and determining the correction of the node voltage based on the measurement result, judging whether to iterate based on the convergence condition, and outputting a load flow calculation result. According to the method, exponential acceleration of the quantum linear system is realized, and the solving efficiency is improved.

The application discloses a design method of a low peak-to-average ratio and pre-distortion compensation communication signal, which comprises the following steps: step 1, constructing an optimization problem model with the target function of minimizing the error vector magnitude between an actual sending signal after a power amplifier and an ideal sending signal, and the constraint conditions of a sending signal peak-to-average power ratio and out-of-band radiation at a sending side of a wireless communication system; step 2, introducing auxiliary variables and increasing constraint conditions related to the introduced auxiliary variables, transforming the signal design problem obtained in step 1 to obtain a new optimization problem; step 3, linearizing the nonlinear function representing the power amplifier characteristics in the target function of the optimization problem obtained in step 2 by using a linearization method to obtain an approximate problem after linearization; and step 4, designing an alternating direction multiplier method based on Newton method updating to solve the approximate problem in step 3 to obtain an optimized sending signal. The application can effectively solve the problem that the high peak-to-average power ratio of a sending signal in an OFDM system leads to distortion through a power amplifier, improve the power amplifier efficiency and improve the power amplifier nonlinearity.

The invention discloses a polishing path determining method and a polishing method.The determining method comprises the following steps that an initial polishing path based on an Archimedes spiral is determined, and any two adjacent initial path points are selected from the initial polishing path; and an error function is determined according to the respective removal functions of the two adjacent initial path points, and the optimal polishing distance of each adjacent initial path point in the initial polishing path is adjusted by using a Newton downhill method, so that the polishing path of the curved surface workpiece is determined. According to the method, the optimal path is generated by dynamically adjusting the distance between the initial path points, the periodic arrangement mode of a traditional spiral / grating path is broken, the intermediate-frequency ripple error caused by periodic motion is restrained, meanwhile, a deterministic optimization mechanism based on error convergence replaces the random layout of a pseudo-random path, and the optimal path is obtained. The problem of local non-uniform material removal caused by high randomness is avoided, and excessive dependence on the dynamic performance of an ultra-high-performance machine tool is reduced.