15 results about "Full tensor" patented technology

The invention provides an edge cloud cache configuration method and device based on tensor complementation, and relates to the technical field of containerization deployment in an edge cloud network, the method comprises the steps of decomposing mirror image layer prefetching into prediction of mirror image layer cache and mirror image layer pre-scheduling, combining tensor complementation, an iTransform model and a CP decomposition algorithm, and after the tensor is complemented, obtaining an edge cloud cache configuration result. The iTransform model captures non-stationary dependence among dimensions of tensors through an inverted time sequence attention mechanism of the iTransform model while keeping high efficiency of parameters, steady inference on current time information is realized, so that an accurate mirror image layer prefetching task is supported, a CP decomposition algorithm performs tensor reconstruction on each selectable tensor to calculate a score of each selectable tensor, and the score of each selectable tensor is calculated to obtain a pre-fetching task of the mirror image layer. And finally, taking the selectable tensor with the highest score as a target tensor. Based on the method, efficient prefetching and cache optimization of the AI micro-service mirror image layer can be realized, so that challenges caused by resource limitation in an edge cloud environment are effectively relieved.

This invention relates to the field of industrial time-series data completion technology, and particularly to a method for industrial time-series data completion based on tensor weighted gamma norm. The method includes: collecting industrial time-series data through sensors and converting it into an observation tensor; processing the observation tensor for missing values ​​to obtain a tensor to be completed, and constructing a low-rank tensor completion model; defining a tensor weighted gamma norm and substituting it into the low-rank tensor completion model to obtain a low-rank tensor completion model using the tensor weighted gamma norm; solving the low-rank tensor completion model using the tensor weighted gamma norm using the alternating direction multiplier method to obtain the target solution; converting the target solution into the format of industrial time-series data to obtain the completed industrial time-series data. This invention utilizes tensor weighted gamma norm to complete industrial time-series data, and further leverages the interdependence and trends between data to mitigate the impact of the nuclear norm approximating the rank function on all singular values ​​to the same degree of contraction.

A method for 3D inversion of Full Tensor Gradiometry (FTG) data comprising receiving observed FTG data, performing a kernel matrix calculation on a subset of the observed FTG data and the gravity anomaly data, performing one-time forward modeling in a wavenumber domain to produce predicted FTG data and predicted gravity anomaly data for the reference density model, performing a residual between the observed data and predicted data, performing a depth-weighting function, a model covariance matrix, and data error covariance matrix on the observed FTG data and observed gravity anomaly data, obtaining a model update based on the depth-weighting function, kernel matrix, the model covariance matrix and the data error covariance matrix, and the residual between the observed FTG data and the predicted FTG data in the wavenumber domain, and performing inversion by directly obtaining an inverted model based on the model update and reference model.

The invention belongs to the technical field of image processing, and provides an intelligent carrier image completion method based on image cutting and tensor interconnection completion, and the method comprises the following steps: storing an RGB format image shot by a camera in a tensor form, and taking the image as a target tensor; preprocessing the prior tensor according to the size and the gray value of the current frame tensor, cutting the preprocessed prior tensor by using an AIP algorithm to generate a reference tensor, and stacking the reference tensor and a target tensor into a synthetic tensor; processing the synthetic tensor by using an ITSC algorithm to obtain a processed tensor after interconnection completion; and extracting the tensor of the corresponding region of the current image from the processed tensor to obtain a complemented tensor, and completing image complementation. According to the method, the stability and the effectiveness of image completion are superior to those of a current main intelligent flight vehicle completion method, and the stability and the effectiveness of image completion of the intelligent flight vehicle under severe weather and poor communication scenes can be greatly improved by applying the method.

A method for 3D inversion of Full Tensor Gradiometry (FTG) data comprising receiving observed FTG data, performing a kernel matrix calculation on a subset of the observed FTG data and the gravity anomaly data, performing one-time forward modeling in a wavenumber domain to produce predicted FTG data and predicted gravity anomaly data for the reference density model, performing a residual between the observed data and predicted data, performing a depth-weighting function, a model covariance matrix, and data error covariance matrix on the observed FTG data and observed gravity anomaly data, obtaining a model update based on the depth-weighting function, kernel matrix, the model covariance matrix and the data error covariance matrix, and the residual between the observed FTG data and the predicted FTG data in the wavenumber domain, and performing inversion by directly obtaining an inverted model based on the model update and reference model.

The application belongs to the technical field of image processing, and provides an intelligent carrier image completion method based on image cutting and tensor interconnection completion, which comprises the following steps: storing an RGB format picture shot by a camera in the form of a tensor as a target tensor; according to the size and gray value of a current frame tensor, pre-processing a prior tensor, and simultaneously cutting the pre-processed prior tensor to generate a reference tensor by using an AIP algorithm, and stacking the reference tensor and the target tensor into a synthetic tensor; processing the synthetic tensor by using an ITSC algorithm to obtain a processed tensor after interconnection completion; extracting a tensor of a current image corresponding region from the processed tensor to obtain a completion tensor, and completing image completion. The application is superior to the current main intelligent flight carrier completion method in stability and effectiveness of image completion, and application of the method can greatly improve the stability and effectiveness of image completion of the intelligent flight carrier in a bad weather and poor communication scene.

The application discloses a kind of conversion methods from aeromagnetic three-component to gradient full tensor, it is related to the technical field of aerogeophysical exploration data processing.Data includes: obtaining aeromagnetic three-component data;The three-component data of aeromagnetic is preprocessed, and corrected three-component data is obtained;In spatial domain, according to corrected three-component data, adaptive multilayer equivalent source initial model is constructed;Frequency domain-space domain mixed iteration conversion is executed to corrected three-component data, and through adaptive multilayer equivalent source initial model, gradient tensor is modified, and spatial domain gradient tensor that meets convergence condition is obtained;Converged spatial domain gradient tensor is output as final full tensor magnetic gradient data.The application realizes high-precision, high-efficiency conversion from vector three-component to gradient full tensor by mixed domain processing strategy and adaptive constraint mechanism, provides reliable technical means for data processing and geological interpretation under the condition that full tensor gradient cannot be directly measured.

The embodiment of the application discloses a structural color design method and device based on a tensor completion algorithm, which comprises the following steps: obtaining spectral data and geometric data of a dielectric array constituting a structural color, and combining the spectral data and the geometric data into multi-dimensional tensor data, wherein the tensor data comprises a to-be-completed tensor and a complete tensor containing all known entries; applying an alternating least squares method to Tucker decomposition of the to-be-completed tensor according to the tensor data, so as to obtain a minimum rank tensor after tensor completion, which is the same as known entries in the to-be-completed tensor; and converting the minimum rank tensor into spectral data and geometric data to obtain corresponding structural color. Through the above method, the embodiment of the application can quickly and accurately design structural color, avoids complex electromagnetic theory, and improves the device design efficiency of a small number of features.

This invention discloses a method for predicting the production capacity of deep coal and rock gas considering complex fracture networks. First, the method establishes a fracture network topological tensor matrix based on fractal geometry and non-Euclidean topological manifolds. Second, it introduces a nanoscale confined multi-state desorption operator to construct a cross-scale gas release source term and integrates continuum damage mechanics and phase field theory to generate a full-tensor permeability evolution functional. Subsequently, a kinetic model is established to quantify the conductivity attenuation boundary caused by coal powder bridging. Combining the above parameters, a spatiotemporal fractional derivative is introduced to construct a comprehensive flow field control equation characterizing nonlocal anomalous diffusion of fluids. Finally, this equation is mapped to a hypergraph network system for global order reduction solution. This invention effectively eliminates the computational singularity of multiphysics rigid equation sets, achieving efficient and high-precision prediction of deep gas well production capacity under time series, providing reliable support for formulating scientific drainage and production systems.

The present application belongs to the field of silicon-based optoelectronics, and particularly relates to a method for full tensor characterization of dielectric constant of magneto-optical film. The present application is based on transfer matrix method and modification of ellipsometer, and differential Mueller matrix of magneto-optical film under positive magnetic field and negative magnetic field is obtained by measurement of ellipsometer according to the characterization principle of transfer matrix method. Diagonal elements of dielectric constant tensor are obtained by fitting ellipsometric parameters according to structure model and dispersion model, and non-diagonal elements of dielectric tensor are obtained by parameter inversion of transfer matrix method. The present application firstly combines transfer matrix method and 4*4 Mueller matrix, and non-contact ellipsometric spectrum measurement is carried out under the condition of applied magnetic field by ellipsometer, so that full tensor characterization of dielectric constant of wafer-level magneto-optical film is realized without destroying wafer or carrying out sample processing, the vacancy of full tensor non-destructive characterization of dielectric constant of wafer-level magneto-optical film is filled, and the present application has great significance for further industrial application of magneto-optical film.

The invention provides an error correction method for a full-tensor magnetic gradient probe. The method comprises the following steps: acquiring chip error data of the full-tensor magnetic gradient probe; the chip error data comprises a full-tensor magnetic gradient of a full-tensor magnetic gradient probe and a gradient of a plane gradiometer; the full-tensor magnetic gradient probe is provided with at least one plane gradiometer; each plane gradiometer is provided with the chip; obtaining an error angle of each plane gradiometer according to the full-tensor magnetic gradient and the gradient of each plane gradiometer; and performing chip angle error correction on the full-tensor magnetic gradient according to the error angle of each plane gradiometer to obtain the corrected full-tensor magnetic gradient. According to the method, the error angle of each plane gradiometer is obtained by comparing the full-tensor magnetic gradient of the full-tensor magnetic gradient probe with the gradient of each plane gradiometer, so that the correction of the angle error of the chip of the full-tensor magnetic gradient probe is completed, and the accuracy of full-tensor magnetic gradient data is improved.

The invention discloses a full-tensor magnetotelluric data scoring method and device, a medium and a program product, and the method comprises the steps: firstly obtaining the actual measurement data of a magnetotelluric measurement point, carrying out the response synthesis of the actual measurement data through a one-dimensional anisotropic model and a phase drift function, and obtaining the corresponding synthesis response data, the method comprises the following steps: constructing a robust regression model on the basis of the residual error of actually measured data and synthesized response data, then performing data fitting on the actually measured data by using the robust regression model to obtain a corresponding fitting reference line, and finally, calculating the residual error of the fitting reference line according to the actually measured data of the magnetotelluric measuring point at each frequency under different rotation azimuth angles and the residual error of the fitting reference line. And scoring the magnetotelluric measuring points to obtain a measuring point scoring result. According to the method, objective and automatic magnetotelluric measuring point data scoring is realized, and the requirement of three-dimensional inversion for data evaluation can be effectively met.

The invention discloses a cubic miniature full-tensor magnetic gradient sensing chip, which comprises a cubic base and twelve micro electro mechanical system single-axis fluxgate sensing devices arranged on the surface of the cubic base, the cubic base is formed by splicing and fixing six substrates through concave-convex sockets; the upper surface and the lower surface of each substrate are respectively bonded and fixed with a single-axis fluxgate sensing device, so that a cross-shaped twelve-unit fluxgate sensing array which is completely symmetrical about the center of the cube and is distributed at equal intervals is formed on the cubic base. The micro-electro-mechanical system fluxgate geomagnetic tensor sensing chip is manufactured by adopting the MEMS technology, compared with a traditional fluxgate tensor instrument, the micro-electro-mechanical system fluxgate geomagnetic tensor sensing chip is good in stability, high in consistency, firmer and not prone to being influenced by environment temperature changes and external stress, the scale factor error of the micro-electro-mechanical system fluxgate geomagnetic tensor sensing chip can be effectively reduced, and the performance of the micro-electro-mechanical system fluxgate geomagnetic tensor sensing chip is enhanced.

The present application provides an error correction method for a full-tensor magnetic gradient probe, the method comprising: obtaining chip error data of the full-tensor magnetic gradient probe; the chip error data comprising the full-tensor magnetic gradient of the full-tensor magnetic gradient probe and the gradient of a planar gradiometer; the full-tensor magnetic gradient probe being provided with at least one planar gradiometer; each planar gradiometer being provided with the chip; obtaining the error angle of each planar gradiometer based on the full-tensor magnetic gradient and the gradient of each planar gradiometer; performing chip angle error correction on the full-tensor magnetic gradient based on the error angle of each planar gradiometer to obtain the corrected full-tensor magnetic gradient. The present application obtains the error angle of each planar gradiometer by comparing the full-tensor magnetic gradient of the full-tensor magnetic gradient probe with the gradient of each planar gradiometer, thereby completing the correction of the chip angle error of the full-tensor magnetic gradient probe and improving the accuracy of the full-tensor magnetic gradient data.

The application discloses a kind of equivalent permeability full tensor calculation method of fractured medium based on EDFM, comprising the following steps: S1: generating random cracks, construct fractured medium physical model;S2: based on EDFM, matrix grid and crack grid are divided, and grid basic parameters are given;S3: based on EDFM, construct fractured medium percolation model;S4: adopt three kinds of boundary condition loading mode, solve the pressure distribution in whole calculation domain;S5: calculate pressure gradient and flow velocity distribution, and calculate the average pressure gradient and average flow velocity in whole calculation domain;S6: calculate equivalent permeability full tensor matrix, and it is symmetrically handled, obtain the calculation result.The application can solve the problem that the crack grid form is complex or the number of cracks is too much in fractured medium, resulting in low calculation efficiency and high calculation cost, and the calculated equivalent permeability full tensor can well represent the heterogeneity and anisotropy of fractured medium, providing technical support for the development of fractured medium.