13results about How to "Improve interpolation accuracy" patented technology

The invention discloses a Transform-based seriously missing multivariate time sequence interpolation algorithm, and relates to the technical field of data interpolation, the algorithm comprises the following steps: S1, analyzing a database taking time as a sequence to obtain a multivariate time sequence data set, and preprocessing the multivariate time sequence data set to obtain a sample data set; s2, constructing a TransSMITS model, wherein the TransSMITS model comprises a sequence interpolation module and a weighting module; and S3, inputting the sample data set into the TransSMITS model, and training the TransSMITS model to obtain a standard TransSMITS model. According to the transform-based seriously missing multivariate time sequence interpolation algorithm provided by the invention, the problem that the filling precision of an existing model on a seriously missing multivariate time sequence is relatively poor is effectively solved.

The invention discloses a rainstorm interpolation method considering mountain torrent drainage basin topographic factors, and particularly relates to the technical field of hydrological space-time interpolation influenced by elevation. Data preparation comprises drainage basin basic data, thematic data and drainage basin rainfall data; the drainage basin rainfall data is detected and then divided to obtain three typical flood fields of the drainage basin, and the obtained three typical flood fields of the drainage basin are subjected to interpolation research by adopting an inverse distance weighting method, a Kriging method and a geographically weighted regression method which are added with topographic factors respectively; wherein the distance weight and the elevation weight are determined by the inverse distance weight method considering the terrain, firstly, the weight of the inverse distance weight method considering the terrain is determined, and the weight distribution in the horizontal distance and the weight distribution in the vertical distance are included; the method is subjected to cross validation to obtain an average relative error, an average absolute error and a root-mean-square error, and the characteristics and the watershed applicability of the rainstorm interpolation method are obtained.

The invention relates to a processing method for improving position instruction interpolation precision in a numerical control system. The processing method comprises the following steps that a servo driver caches a position instruction; calculating a position instruction increment; and performing fine interpolation processing on the position instruction. The invention further relates to a processing device for improving the interpolation precision of the position instruction in the numerical control system, a processor and a computer readable storage medium of the processor. According to the processing method and device for improving the position instruction interpolation precision in the numerical control system, the processor and the computer readable storage medium, the interpolated position instruction can be obtained in real time through cyclic calculation, the interpolation precision of the position instruction is improved, and finally the machining precision and the machining effect of a machine tool can be improved.

The utility model relates to a kind of anti-falling connectors, female seat has first insulating body and first terminal, the butt joint end of first insulating body is equipped with the socket of axial inner recess, the inner side wall of socket is equipped with first guide part;First terminal is installed on first insulating body and has first contact part towards socket;Male head has second insulating body and second terminal, the outer side of second insulating body is equipped with second guide part, second guide part and the cooperation of first guide part guide second insulating body insertion socket;Second terminal is installed on second insulating body and has second contact part, and second contact part is used to contact with first contact part and is conducted through;Stopper is set on first insulating body and can be opened and closed movement, by closing state support second insulating body.The utility model can effectively control the normal and axial movement after male head is inserted, to further promote connection accuracy and stability, simple structure, it is convenient to manufacture and combination, investment cost is low.

The invention discloses a monitoring data quality control method and device based on a multi-outlier detection algorithm, and belongs to the field of environmental monitoring data processing, and the method comprises the following steps: step 1, data screening and preprocessing, step 2, data quality control, and step 3, grid data and regional data generation. According to the invention, by combining three machine learning algorithms and utilizing STL decomposition, misjudgment is effectively avoided, and the accuracy of anomaly detection is improved. According to the improved IDW + algorithm, by introducing a variation function and a parameter estimation point screening mechanism, the precision of an interpolation result is ensured, and interference of invalid parameter estimation points is reduced. IDW interpolation is firstly carried out on the missing points, it can be ensured that an interpolated basic data set is more complete, and instability caused by the missing data points does not need to be considered too much during Kriging interpolation. The overall interpolation result obtains double guarantee on the accuracy of local data and the smoothness of global space grid data.

The application discloses a groundwater level space-time dynamic monitoring and visual analysis method and system, relates to the technical field of groundwater resource monitoring and visualization, and comprises the following six steps: multi-source data fusion preprocessing, mixed space interpolation of the Kriging and machine learning, isopachous surface generation and optimization, time sequence animation synthesis, abnormality identification and classification, and early warning heat map visualization. The system comprises a data acquisition module, a space interpolation module, an isopachous surface generation module, a time sequence animation module, an abnormality identification module and an early warning visualization module. The application improves the space interpolation precision through multi-source data fusion and mixed interpolation of the Kriging and machine learning, directly presents the space-time evolution of the water level through the isopachous surface and the time sequence animation, identifies abnormal areas such as over-exploitation funnel through space-time gradient analysis, and assists in management decision through the early warning heat map, so as to solve the technical problems of sparse monitoring sites and the difficulty of directly presenting the space-time evolution law in traditional reports.

An image processing method and device thereof, and a readable storage medium, the image processing method comprising: obtaining an original image, the original image comprising pixels to be interpolated; extracting high-frequency texture components of each pixel to be interpolated on the original image in the vertical direction and the horizontal direction respectively; setting a vertical direction interpolation weight and a horizontal direction interpolation weight of each pixel to be interpolated according to the high-frequency texture components of each pixel to be interpolated on the original image in the vertical direction and the horizontal direction; obtaining an interpolation pixel value of each pixel to be interpolated according to the vertical direction interpolation weight and the horizontal direction interpolation weight of each pixel to be interpolated.

The invention relates to the technical field of intelligent medical treatment, and discloses a lumbar endoscopic postoperative chronic neuropathic pain early warning deep learning large model system. According to the system, a postoperative multi-modal data initial pool of a patient is constructed, and original data streams are collected; performing space-time alignment and missing value interpolation on the original data stream by using the dynamic feature extraction network to form a standardized time sequence feature matrix; inputting the feature matrix into a hierarchical attention feature fusion network, calculating interaction weights of different modal features on a plurality of time scales, and generating enhanced feature representation fused with multi-scale context information; deducing an evolution path of a neural function state under different physiological parameter combinations through a risk trajectory simulation engine based on enhanced feature representation, and constructing an individualized risk evolution trajectory map; and according to the map, adopting a self-adaptive threshold decision model to identify an abnormal fluctuation interval deviating from a normal recovery mode, and outputting a chronic neuropathic pain risk early warning signal.

The invention discloses a multi-model-based straight line machining surface machining path interpolation method and a machine tool, machining path model information is generated based on workpiece straight line machining surface information, a cutter location point trajectory curve in the machining path information is associated with a straight line machining surface upper edge curve, and a cutter axis point trajectory curve is associated with a straight line machining surface lower edge curve; then geometric interpolation is carried out based on the machining path model information, machining speed setting is carried out based on the machining path model information, and the machining speed is set based on an interpolation cutter location point after geometric interpolation; calculating the position information of each physical axis from the position information of the interpolation cutter location point and the cutter axis vector information in an inverse solution manner, and storing the position information; interpolating information is arranged into a control command list, the control command list data is executed in sequence, and the interpolating information comprises the position information of each physical axis and the processing speed information. And accurate interpolation can be performed based on cutter axis point trajectory curves, cutter location points and cutter axis point correlation function information in multiple models, so that the bow height error is eliminated, and the interpolation precision is improved.

The invention discloses a wind resource data processing method and system, and the method comprises the following steps: carrying out the same-tower interpolation of the wind resource data of different height layers of a target anemometer tower through the target wind resource data of the target anemometer tower; after same-tower interpolation is carried out on the target anemometer tower, whether target data missing exists in the target wind resource data of different height layers or not is judged; selecting adjacent anemometer towers of the target anemometer tower according to the inter-tower distance and terrain similarity calculated according to the terrain data, and acquiring adjacent wind resource data of the adjacent anemometer towers; performing different-tower interpolation on target data in the target wind resource data of different height layers of the target anemometer tower by using the adjacent wind resource data; and obtaining corrected wind resource data of the target anemometer tower. According to the method, through'terrain similarity 'filtering, it is ensured that the microenvironments where the two towers are located are comparable, and the wind speed / wind direction correlation modeling precision is improved; when a plurality of suspected anemometer towers meet the terrain similarity, the suspected anemometer towers can be reserved at the same time, so that the interpolation precision is improved.

The embodiment of the application provides a non-stationary autoregressive regularization seismic data interpolation method and device, and belongs to the technical field of computers. The method comprises the following steps: acquiring seismic data; processing the seismic data based on a non-stationary autoregressive model to obtain prediction error filter coefficients; and reconstructing missing or aliasing data in the seismic data according to the prediction error filter coefficients and the seismic data to obtain interpolated data. The adaptive prediction error filter coefficients are estimated by minimizing the prediction error containing the regularization term, so that the interpolation is performed. The seismic data with non-stationary characteristics can be effectively processed, the interpolation precision is improved, the calculation time is reduced, and the complex underground structure is adapted. Through the shaping regularization technology, the application has wide application potential in the field of seismic exploration, and can significantly improve the efficiency and precision of oil and gas exploration.

The utility model provides an automatic plug-in device for battery joints, and relates to the technical field of lithium battery modules. Comprising a mounting frame; the plug fixing mechanism is arranged on the surface of one side of the plug fixing mechanism mounting plate, the plug fixing mechanism can fix a test plug and can adjust the up-down and left-right fixing positions of the plug, and the plug fixing mechanism mounting plate can drive the plug fixing mechanism to float; the plug fixing mechanism comprises a plug fixing mechanism mounting plate, universal balls are arranged at the four corner angles of the plug fixing mechanism mounting plate, the plug fixing mechanism mounting plate is arranged at the tail ends of two floating shafts, and the floating shafts are arranged on the two sides in the mounting frame. The whole plug fixing mechanism can be subjected to floating adjustment in the X-axis direction, the Y-axis direction and the Z-axis direction, and automatic plug-in of the test plug can be achieved in the mode that the plug automatically recovers to the original position after plug-in is completed.

This invention discloses a precise brain tumor resection path planning system integrating ultrasound and electromagnetic tracking, relating to the field of medical image processing. The invention includes: preoperative multimodal image segmentation and initial path planning; intraoperative real-time ultrasound image acquisition and feature point extraction; construction of a deformation interpolation model based on tissue type-weighted anisotropic kernel functions, introducing a divergence constraint regularization term; construction of a continuous three-dimensional deformation field within the region of interest using a hierarchical progressive strategy; application of the deformation field to the initial path for dynamic correction; control of the update frequency through an adaptive triggering mechanism, and real-time display of path risks using color coding. This invention achieves dynamic path correction in cases of intraoperative brain drift, contributing to improved accuracy in surgical path planning.