16 results about "Sum squared error" patented technology

The invention discloses a power distribution network traveling wave fault positioning method and a related device, and relates to the technical field of power distribution networks, and the method comprises the steps: collecting a transient signal after a fault at a preset key monitoring point of a power distribution network, extracting an initial traveling wave head from the transient signal, and measuring the moment when the initial traveling wave head reaches other preset monitoring points in the power distribution network, obtaining traveling wave arrival time between the key monitoring point and each monitoring point; the time difference between the traveling wave arrival time is used as the actually measured traveling wave arrival time difference to construct a fault positioning optimization model with the purpose of minimizing the error sum of squares of the theoretical traveling wave arrival time difference and the actually measured traveling wave arrival time difference; and solving the fault positioning optimization model through a pre-constructed chaos particle swarm optimization algorithm to obtain a traveling wave fault positioning result of the power distribution network. The method solves the problems that the positioning effect is not ideal due to the fact that the prior art is prone to falling into local optimum and is poor in adaptability to a complex topological structure, and the convergence speed cannot meet the requirement for rapid power supply recovery.

The invention belongs to the technical field of unmanned aerial vehicle aircraft design, and particularly relates to a longitudinal aerodynamic parameter identification calculation method in a closed-loop state and a large angle-of-attack range, and the method comprises the steps: building a flight simulation model; performing aerodynamic characteristic simulation based on a flight simulation model to obtain an aerodynamic load value, comparing the aerodynamic load value with data tested in an actual flight experiment, and calculating and minimizing an error sum of squares; dividing the whole angle-of-attack range into a plurality of sub-intervals, respectively obtaining the optimal aerodynamic parameters of each sub-interval based on the minimum sum of squares of errors, inputting each optimal aerodynamic parameter into the flight simulation model, and carrying out model accuracy verification; and drawing an aerodynamic characteristic curve according to each optimal aerodynamic parameter, and verifying the applicability of the flight simulation model. The method has universality and is suitable for longitudinal aerodynamic coefficient parameter identification of different types of unmanned aerial vehicles, the parameter identification efficiency is improved, and meanwhile the applicability of the model under the complex flight working condition is enhanced.

The application discloses a lightweight indoor 3D laser ground extraction algorithm method, system and medium. The method comprises the following steps: acquiring indoor 3D laser radar data; obtaining coordinate values based on a laser radar coordinate system according to the indoor 3D laser radar data; sending the coordinate values to a preset plane equation to obtain a ground plane normal vector; sending the ground plane normal vector to a first preset coordinate system to establish a constraint to obtain a comprehensive error value; and accumulating squares of values in the comprehensive error value to obtain a comprehensive error sum of squares; extracting a minimum value in the comprehensive error sum of squares, and setting a coordinate point corresponding to the minimum value as an optimal current pose. The application is suitable for various lasers, and by giving a preset threshold, whether it is 16 lines, 32 lines or 128 lines, the algorithm accuracy and robustness are ensured, and the accuracy of recognized ground points is improved.

The application provides a ship type classification prediction method and system based on K-means and XG-Boost, acquires ship data and carries out pretreatment, then adopts a K-means clustering algorithm to respectively cluster each kind of data in the pretreated ship data to obtain multiple clusters, calculates error sum of squares of all data in each cluster, calculates the classification number of each kind of data according to the error sum of squares, selects a certain classification number by using an elbow method, marks the ship type of all clustered ships according to the classification number, then takes the ships with marked ship types as training set samples, adopts an XG-Boost classification algorithm to train the training set samples to obtain multiple classification prediction models, verifies the multiple classification prediction models to obtain an optimal classification prediction model, and predicts the ship types of all ships in the world according to the optimal classification prediction model and marks the ship types. The application can accurately classify all ships in the world, and can avoid overfitting and underfitting of the model while ensuring the accuracy.

This invention discloses a data visualization monitoring method and system for heating networks in heating station supply areas, specifically relating to the management field. The method includes synchronously collecting multi-dimensional data, establishing a heating network spatial coordinate system to locate the data collection nodes, and storing the coordinate data in a data storage center. It employs a K-means clustering algorithm to extract three typical heating patterns and simultaneously evaluates the matching degree of user heating patterns. An optimization cycle is set to extract optimized samples, and the gradient descent method is used to minimize the sum of squared errors between model predictions and actual values, updating relevant model parameters. Based on data analysis results, this invention generates three targeted decision-making suggestions: resource allocation, inspection priority, and heating guidance. Combined with historical data tracing and operational pattern mining, it provides comprehensive support for short-term operational optimization and long-term planning of the heating network, effectively improving the efficiency of heating resource utilization, reducing operational risks, and minimizing resource waste, thus exhibiting significant economic and management benefits.

The invention belongs to the technical field of unmanned aerial vehicle design, and particularly relates to an open-loop state large-angle-of-attack range longitudinal aerodynamic coefficient identification calculation method, which comprises the following steps of: comparing simulation data with test data in an actual flight test, calculating an error sum of squares of the simulation data and the test data, and minimizing the error sum of squares; dividing the whole attack angle range into a plurality of sub-intervals, respectively obtaining the optimal aerodynamic parameters of each sub-interval based on the minimum sum of squares of errors, inputting each optimal aerodynamic parameter into the flight simulation model, comparing the optimal aerodynamic parameters with test data for verification, and executing the next step when the difference value between the optimal aerodynamic parameters and the test data is within a set range; and drawing an aerodynamic characteristic curve according to each optimal aerodynamic parameter, verifying the applicability of the flight simulation model, and optimizing the robustness of the flight simulation model. The method is suitable for longitudinal aerodynamic coefficient parameter identification of different types of unmanned aerial vehicles, the parameter identification efficiency is improved, and meanwhile the applicability of the model under the complex flight working condition is enhanced.

The application relates to a privacy protection recommendation method and system based on matrix decomposition and belongs to the technical field of privacy protection recommendation. The method comprises the following steps: obtaining a historical rating matrix of a user; performing matrix decomposition on the historical rating matrix to obtain a shared rating matrix; sending the shared rating matrix and a scored item set to a recommendation server to generate public parameters, a decomposition matrix and a shared value of the decomposition matrix; generating inner product triplets and multiplication triplets by using a triplet server; calculating errors between real ratings and predicted ratings by using the recommendation server to generate an error shared matrix; optimizing the error shared matrix until the error squares of all the error shared matrices are less than a threshold value; calculating partial derivatives of a loss function on the decomposition matrix to obtain a gradient shared matrix; updating the decomposition matrix to obtain a user decomposition shared matrix; and generating a privacy protection recommendation result of the user by using the user decomposition shared matrix. The application provides strong protection in the aspect of protecting user privacy.

The invention relates to the technical field of power systems and renewable energy scheduling, and discloses a small hydropower station cluster planning and grouping method and device and a medium, and the method comprises the steps: obtaining multi-source data of each small hydropower station, and constructing a small hydropower station cluster feature space model; constructing a mathematical effectiveness index and a field rationality index, and establishing a k-means clustering algorithm multi-dimensional evaluation index system; executing an improved k-means + + clustering algorithm, and generating clustering schemes and evaluation results under different K values; constructing a derivative evaluation index based on an error sum of squares, distributing an index weight, calculating a comprehensive score corresponding to each K value, and determining an optimal clustering k value; and outputting a small hydropower station cluster grouping scheme corresponding to the optimal clustering number. According to the method, adaptive grouping of small hydropower station clusters is realized through a clustering algorithm driven by a small amount of data, and a small hydropower station cluster division scheme with reasonable spatial distribution, unified basin attributes and coordinated operation characteristics is provided for regional power grid dispatching.

A deformable block registration improvement method based on historical information correction comprises the steps that an image is layered according to scenery information, and key areas are marked according to application requirements and a layering result; random block selection and deformation calculation in the key area: randomly selecting blocks in the key area, adjusting the size of the selected blocks, and calculating an initial deformation matrix of the selected blocks by adopting a normalized error sum of squares and an affine model; correcting a deformation result based on a historical deformation field: constructing historical deformation field data, extracting historical deformation data of the current block, and correcting an initial deformation matrix through a dynamic weight model; and performing new deformation field fitting: applying consistency constraint to the correction block, fitting a global deformable field by adopting thin-plate spline interpolation, outputting after filtering optimization, and updating a historical deformation field database. According to the method, the problems of low registration precision and error accumulation of deformable blocks in a multi-moving-target scene are solved through marking key areas by image layering, performing targeted random block selection, performing historical deformation field correction and performing consistent deformation field fitting.

This invention relates to an automatic focusing method for laser galvanometers based on a polynomial regression algorithm, including variable definition, data collection of sample data within different power ranges from 10% to 80%, and data preprocessing; employing a piecewise polynomial regression model, and adding an L2 regularization term to the model to prevent overfitting; and minimizing the observed value D. i The model parameters are estimated using the sum of squared errors between the predicted and actual values. The model is used to predict values ​​in real time. When the absolute value of the deviation ∈ between the predicted and actual roundness values ​​D exceeds the threshold Th, the galvanometer height H or laser power P is dynamically adjusted to make D approach the target value D. target =0; the system is based on the optimal height H * The Z-axis position of the galvanometer is adjusted in real time to focus the laser beam at the optimal position; the deviation between the actual value D and the predicted value ∈ is periodically collected to update the regression model coefficients. This invention enables precise focusing of the laser beam, improving product consistency and yield.

The invention belongs to the technical field of unmanned aerial vehicle design, and particularly relates to a longitudinal aerodynamic parameter identification calculation method under a closed-loop state and a small attack angle range, and the method comprises the steps: simulating the flight state change process of an unmanned aerial vehicle under the condition of the closed-loop state and the small attack angle range based on a flight simulation model; dynamic characteristics of the aircraft under different longitudinal pneumatic conditions are obtained; performing parameter identification calculation on the dynamic characteristics of the aircraft under different longitudinal pneumatic conditions to obtain flight simulation data; iterative optimization is performed on the longitudinal aerodynamic model parameter combination set through a genetic algorithm, and an optimal longitudinal aerodynamic model parameter combination is obtained by combining the sum of squares of errors between flight simulation data and actual flight test data; and simulation verification and error analysis are carried out on the optimal longitudinal aerodynamic model parameters, and verification is completed when a preset precision requirement is met. The influence of the control law on the flight test in the flight process is considered, and the identification of the longitudinal aerodynamic coefficient parameters in the corresponding closed-loop state is more accurate.

The invention discloses a multi-peak Gaussian fitting concave cavity blade tip gap measurement method and system, and belongs to the technical field of concave cavity blade tip gap measurement, and the multi-peak Gaussian fitting concave cavity blade tip gap measurement method comprises the steps: S1, obtaining an analog voltage signal reflecting the size of a blade gap; s2, establishing a double-Gaussian model of the concave cavity blade; s3, establishing an error sum of squares model; and S4, parameters in the error sum of squares model are adjusted by using an iterative algorithm, and an iteration termination condition is that the error sum of squares is smaller than a preset threshold, and the obtained parameter value is the parameter of the double-Gaussian model. By the adoption of the technical scheme, the double-Gaussian model and the error quadratic sum model are utilized, and the blade tip clearance of the concave cavity blade can be measured rapidly and accurately.

The invention relates to the technical field of digital assembly of parts, and discloses a large-scale assembly fixture measurement reference thermal deformation compensation method and device, and the method comprises the steps: obtaining a real-time temperature when a laser tracker measures a coordinate value of a common observation point through a temperature sensor, constructing a temperature field, and carrying out the measurement of the coordinate value through a temperature sensor; then calculating the thermal deformation displacement of each common observation point through a finite element method, compensating the theoretical coordinate point set, registering the compensated and corrected theoretical coordinate point set with the measurement coordinate point set, solving a least square function about the sum of squares of distance errors by adopting a singular value decomposition method, and calculating the thermal deformation displacement of each common observation point; the rotation matrix and the translation vector when the point set in the measurement coordinate system is transferred to the unified coordinate system are obtained, and the station transfer coordinate value is obtained, so that the station transfer precision of the laser tracker is improved, and the method has the outstanding advantage of carrying out rapid compensation aiming at the temperature influence.

The invention discloses a sound source localization method based on reference particle swarm optimization in the technical field of sound source localization, and aims to solve the problems that the traditional particle swarm optimization is easy to fall into local optimum, global exploration and local development are difficult to balance, the convergence speed is low and the like. Acquiring an actual value of time difference of arrival data of the signal received by each sensor; taking an error sum of squares between an actual value and a theoretical value of the time difference of arrival data as a main fitness function; and executing a reference particle swarm optimization algorithm, and performing global optimization on the sound source position. Wherein the reference particle swarm optimization algorithm constructs a dynamic reference particle set, designs a nonlinear adaptive weight mechanism, automatically adjusts the balance of global and local search based on the number of iterations and population dispersion, and introduces a sub-fitness function evaluation module at the same time. According to the method provided by the invention, millimeter-level positioning precision can be realized, and the convergence speed is improved by 80% compared with that of a traditional particle swarm optimization algorithm.

This invention discloses a method for analyzing the machining accuracy of CNC machine tools based on discrete sampling and transient response. It establishes a time decay model for the CNC machine tool, collects input and output data, and uses a hybrid particle swarm optimization (PSO) and gradient descent algorithm to identify model parameters. Machining errors are discretely sampled using a sampling period T. The error sample values ​​at each sampling time are used as input and convolved with the impulse response model. The convolution output is divided into steady-state and transient outputs, and a recursive equation incorporating historical transient summations is established. With the minimum sum of squared machining errors as the optimization objective, a PSO algorithm is used to search for the sampling period and tool feed gain that minimize the objective, and the CNC machine tool control parameters are set accordingly. This invention establishes the response model, the transient relationship between control input and output without changing the hardware. By optimizing control parameters, surface ripple is suppressed, and machining errors are reduced. The model is identified solely based on input and output data.

The application discloses a kind of dynamic characteristic characterization performance acquisition methods of pulse pressure sensor, belongs to pressure sensor metrological calibration field.The application provides a kind of dynamic characteristic characterization performance acquisition methods of pulse pressure sensor, utilizes high-order constant coefficient differential equation with zero output to characterize the dynamic response characteristics of pulse pressure sensor, with the minimum residual error square sum as the basis to carry out system identification, the quantitative differential equation obtained can reflect the influence of measurement system drift;Compared with high-order constant coefficient differential equation of the same order without zero output, smaller system error and random error can be obtained.