2 results about "Local regression" patented technology

This invention provides a geographically weighted infectious disease risk analysis method and system, comprising: rasterizing multi-source data and constructing a unified grid dataset and analysis indicator library; calculating the Pearson correlation coefficient between grid cases and various indicators in the unified grid dataset, and outputting the final set of influencing indicators; determining the neighborhood range using an adaptive bandwidth method and determining the spatial weights corresponding to neighborhood samples based on a specified kernel function; constructing exposure sequences corresponding to the current analysis period and multiple historical lag periods for each key indicator; forming a cross-basis local sample set based on the cross-basis features constructed based on the target grid cell and neighboring grid cells, constructing a geographically weighted distributed lag nonlinear model based on the cross-basis local sample set, and performing local regression fitting; comparing the effect differences of different exposure levels over all lag periods to obtain the cumulative effect value, and determining the lag period that contributes the most to the infectious disease risk of the target grid cell as the optimal lag period.

This invention provides a method for reconstructing complex surfaces based on white light interferometry data: The method acquires surface topography measurement data of the complex surface to be reconstructed using white light interferometry; constructs a sliding local region centered on each point to be estimated within the measurement area; processes the measurement data within each local region to obtain the height value of the corresponding point to be estimated; and outputs the global reconstruction result of the complex surface after traversing all points to be estimated across the entire region. The process of processing the measurement data within each local region includes the following steps: S1, using MM estimation to perform robust pre-estimation of the measurement data within the current local region; S2, using the absolute value of the residual as input, and through mixing... t Distribution clustering adaptively classifies the measurement data to obtain the retained valid measurement data; S3, repeat S1 to S2 until the outlier removal iteration is completed to obtain the final valid measurement dataset; S4, use weighted Jacobi basis functions to perform local regression to obtain the height value of the point to be estimated.