4 results about "Sum squared error" patented technology

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.

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.

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.

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.