6 results about "Nonparametric regression" patented technology

The invention provides an attitude trajectory optimization method and system based on a self-adaptive sliding window. The method comprises the following steps: acquiring visual media data and decoding the visual media data into a time sequence image frame sequence; performing attitude estimation on each frame of image to obtain a coordinate set of each attitude feature point; caching a coordinate set of the historical attitude feature points to form a variable-length dynamic trajectory cache queue; constructing a sliding window according to the coordinate sets of the attitude feature points of the current frame and the previous frame; performing abnormal data elimination on each coordinate track; performing B spline fitting on each coordinate track; sequentially executing multi-stage optimization on the coordinate track; and updating the sliding window frame by frame to obtain a sequential sequence of the optimized attitude feature points. The method has the beneficial effects that the window radius is dynamically adjusted based on the motion intensity, the window is expanded at low speed to enhance noise suppression, and the window is reduced at high speed to reduce delay; and nonparametric regression fitting is carried out by adopting a cubic B spline, so that the modeling capability of a nonlinear motion track is enhanced, and the track smoothness is improved.

The present invention relates to the technical field of power grid assessment and optimization. Disclosed are a progressive planning-based power grid evaluation method and system based on a combined assessment theory. The method comprises: using a combined weighting method to perform weight correction on an obtained index by; obtaining an assessed value on the basis of a similarity theory-based assessment method; performing standardization processing on the index by means of non‑dimensionalization processing; and performing evaluation on the basis of non-parametric regression. By means of a combined subjective-objective weighting method, the present invention ensures the objectiveness and fairness of assessment results. By means of a deep learning model, in particular an LSTM network and an attention mechanism, the efficiency and accuracy of assessment are improved. The systematic method of the present invention has wide prospects for application. In the present invention, by means of the design of automated optimization of assessment parameters, adaptive adjustment can be performed on the basis of historical data and real-time data, so that assessment results are closer to actual values, thereby improving the practicality of assessment.

The present invention discloses a progressive power grid planning evaluation method and system based on a combination assessment theory, and relates to the technical field of power grid assessment and optimization. The method includes: correcting a weight of an obtained index by using a combination weighting method; obtaining an assessed value based on a similarity theory assessment method; standardizing an index by dimensionless processing; and performing evaluation based on nonparametric regression. The present invention ensures objectivity and fairness of an assessment result and the efficiency and the accuracy of assessment are improved. The present invention may be adaptively adjusted, making the assessment result closer to reality.

The application discloses a building deformation prediction method based on a nonparametric regression model, and comprises the following steps: 1, obtaining the measured time series data of a building monitoring point, and performing noise reduction pretreatment on the data by using a sliding average method; 2, establishing a nonparametric regression model for the pretreated data, and performing autocorrelation test on irregular terms in the nonparametric regression model; 3, performing parameter optimization on SVR by using a fish-eagle optimization algorithm, and then establishing an SVR irregular term regression prediction model by using optimal parameters to fit irregular terms; 4, obtaining a final nonparametric regression model; and 5, performing deformation prediction on the building. The fish-eagle optimization algorithm can obtain a global optimal solution of an optimization problem, the optimization result is independent of initial conditions and the algorithm is independent of a solution domain, has strong robustness, can be well used for solving model parameters, and the method can realize accurate deformation prediction.

The application discloses a remote sensing data normalization method and system based on geographical weighted nonparametric regression, and the method comprises the following steps: building a geographical weighted nonparametric regression estimation model; obtaining a target image and a reference remote sensing image set, and forming a remote sensing image pair based on the target image and the corresponding reference remote sensing image; preprocessing the target image in the remote sensing image pair to obtain a resampled target image with a spatial resolution consistent with that of the reference remote sensing image; judging the coefficient of variation in each local window of the resampled target image and the reference remote sensing image, and screening out qualified homogeneous pixels based on the coefficient of variation and a preset threshold to form a homogeneous pixel set; and performing pixel-by-pixel calculation on the image to be normalized based on the geographical weighted nonparametric regression estimation model and the homogeneous pixel set, so as to obtain a normalization result. The remote sensing data with high width, high time resolution, consistent spectrum and consistent radiation can be used as a radiation reference benchmark to realize the normalization of any target image.

The application discloses a kind of narrowband internet of things system terminal working state timer dynamic configuration method, belong to satellite communication technical field, comprising: constructing the time delay power consumption multi-objective optimization problem of narrowband internet of things system terminal under low-orbit satellite internet of things scene;Based on the time delay power consumption multi-objective optimization problem, obtain the support vector machine nonparametric regression model of narrowband internet of things system terminal working state timer parameter to time delay and power consumption;The support vector machine nonparametric regression model of time delay and power consumption is substituted into the time delay power consumption multi-objective optimization problem, and the second generation non-dominated sorting genetic algorithm is used to solve, and the pareto front optimal solution set of time delay power consumption multi-objective optimization problem is obtained;From the pareto front optimal solution set, determine the working state timer parameter value that satisfies the time delay power consumption demand of current scene, according to the working state timer parameter value that satisfies the time delay power consumption demand of current scene determined to dynamic configuration timer parameter.