102 results about "Rank correlation" patented technology

An image processing method is described for determining depth information from at least two input images recorded by a stereo camera system, the depth information being determined from a disparity map taking into account geometric properties of the stereo camera system, characterized by the following method steps for ascertaining the disparity map: transforming the input images into signature images with the aid of a predefined operator, calculating costs based on the signature images with the aid of a parameter-free statistical rank correlation measure for ascertaining a cost range for predefined disparity levels in relation to at least one of the at least two input images, performing a correspondence analysis for each point of the cost range for the predefined disparity levels, the disparity to be determined corresponding to the lowest costs, and ascertaining the disparity map from the previously determined disparities.

The invention discloses a wind and photovoltaic complementary power generation system reliability evaluation method based on a Copula theory. The method comprises the following steps of: (1) determining the power probability distribution of a wind power station and a photovoltaic plant; (2) respectively performing integral operation on the power probability distribution fWT(P1) and fPV(P2) of thewind power station and the photovoltaic plant, and calculating the accumulative power probability distribution of the wind power station and the photovoltaic plant; (3) calculating Kendall rank correlation coefficients of the power of the wind power station and the photovoltaic plant; (4) calculating a correlation parameter theta of a Frank Copula function; (5) forming a simultaneous equation through a formula (2) and a formula (4) to obtain the joint probability density of the random variables P1 and P2; and (6) acquiring the accumulative probability distribution of the wind and photovoltaiccomplementary power station through integral operation according to a joint probability density function of the power of the wind power station and the photovoltaic plant, forming an off-the-line table of the power of the wind and photovoltaic complementary power station through the accumulative power, and establishing a reliability model of the wind and photovoltaic complementary power station. According to the method, the reliability of the wind and photovoltaic complementary power generation system can be accurately evaluated.

The invention discloses a wind speed modeling method for a large-sized wind power plant in a mountainous area. The method comprises: 1, sampling historically recorded wind speed of the wind power plant, and calculating parameters c and k of wind speed Weibull distribution of each fan group of the wind power plant; 2, calculating a rank correlation coefficient Rho Rr of each fan group in the wind power plant, and constructing a historical wind speed rank correlation coefficient Rr of the wind power plant; 3, calculating related wind speed normal Copula functions of the wind power plant to obtain a joint probability distribution function, defined in the specification, of modeled and predicted wind speed with correlation, and edge probability distribution functions u1 to un of wind speed of fan groups; and 4, performing equiprobable reverse transformation of the Weibull distribution parameters c and k on the edge probability distribution functions of the wind speed of the fan groups to realize wind speed prediction. According to the method, the technical problem that a characteristic that wind speed in a wind power plant has correlation cannot be truly and effectively reflected, electric power distribution and safety operation of a power system are influenced due to direct influence of the correlation of the wind speed in the wind power plant on output of the wind power plant, and the like in the prior art are solved.

The invention discloses an improved type principal component analysis model-based fault detection method which is aimed at improving effects exerted by a conventional PCA algorithm on fault detection via further discovery of characteristics of distance correlation between training data. The method comprises the following steps: an angle correlation matrix and a distance correlation matrix of the training data are calculated, a new correlation matrix is obtained after the angle correlation matrix and the distance correlation matrix are added up, and corresponding characteristic values and vectors are calculated. An improved PCA model is built via use of the characteristic vectors, and the PCA model is applied to on-line fault detection. Compared with a conventional method, the fault detection method disclosed in the invention is advantageous in that angle correlation and distance correlation of the training data are taken into account at an off line modeling phase, data correlation characteristics are fully discovered, the improved type PCA model built via the fault detection method can be used for comprehensively describing potential characteristics of normal data, and good fault detection effects should be exerted.

The invention discloses a no-reference image quality evaluation method based on a multi-task convolutional neural network, and belongs to the field of image perception. The method specifically comprises the following steps: step 1, extracting a plurality of image blocks with fixed sizes from each image of a manually labeled image quality data set, and each image block corresponding to two labels,which are respectively a degradation category of the image and a degradation degree of the image, so as to form a training set; step 2, constructing a convolutional neural network model based on dictionary learning; step 3, training the constructed convolutional neural network model by using the training set, and determining parameters of the convolutional neural network model after the training is finished; and step 4, during application, inputting the to-be-scored pollution image into the trained convolutional neural network model to obtain a corresponding image quality score. Compared witha traditional method, the method is higher in consistency with subjective evaluation in the field of non-reference image quality evaluation, and key indexes such as the Spearman rank correlation coefficient and the Pearson linear correlation coefficient are obviously improved.

The invention discloses a variable selection and forecast method of the silicon content in molten iron of a blast furnace. According to the method, blast furnace process parameters of a prediction model of the silicon content in molten iron of a blast furnace are used as input variables; after normalization preprocessing is performed on sample data of the input variables, variable selection is performed on the sample data of the input variables by using a multivariate correlation analysis method and a Spearman rank correlation analysis method, to remove the correlation between production process parameters; and a support vector machine algorithm is used to establish the forecast model of the silicon content in molten iron of the blast furnace, and particle swarm optimization algorithm is introduced to optimize model parameters. The variable selection and forecast method of the silicon content in molten iron of a blast furnace has universal applicability in forecasting the silicon content in molten iron during smelting of a blast furnace, and can achieve desirable forecast accuracy and improve the forecast hit rate of the silicon content in molten iron.

The invention provides a sintering process working condition identification method and system considering a time sequence. The method takes the time sequence data of the process parameters of a sintering process as the input and takes a sintering process working condition as the output, and comprises the steps of firstly, utilizing a Spearman rank correlation analysis method and an information entropy analysis method for parameter selection and combination, and obtaining the combined decision parameters; then, using a fuzzy C-means clustering algorithm based on the dynamic time warping distance for clustering the time sequence data, and obtaining a clustering result of the combined decision parameters; and finally, using a naive Bayes classifier for the working condition recognition, and obtaining the recognized sintering process working condition. According to the working condition recognition method, the effective recognition of the working condition during the sintering process is achieved, and the important economic value and the application value are achieved.

The present invention provides a correlation-matrix feedback method and system for an antenna array. The method comprises steps of: selecting, at a receiving end, a codeword from a predetermined correlation-matrix codebook comprising a plurality of codewords according to a predetermined criterion to represent a correlation matrix to be fed back (300); and feeding back an index of the selected codeword in the predetermined correlation-matrix codebook to a transmitting end (302); wherein each codeword is a codeword matrix for approximating a correlation matrix of an antenna array at the transmitting end. According to the present invention, it is possible to take good advantage of the characteristics of closely-spaced ULA antennas and spatial correlation thereof, design a corresponding codebook for quantization and feedback, and reduce feedback overhead and computational complexity so as to improve the system performance of a spatial correlation aided system, such as a MIMO system.

The invention provides a multi-component converted wave fracture prediction method based on rank correlation analysis. The predication method includes steps of selecting a calculation time window, intercepting the radial component and the transverse component of a to-be-handled sampling point according to the calculation time window; performing rank correlation analysis on the to-be-handled sampling point and acquiring a maximal rank correlation coefficient; judging whether the to-be handled sampling point has fracture development and determining the location of the fracture development; separating the radial component and the transverse component to the to-be-handled sampling point judged to have fracture development and acquiring a quick transverse wave and a slow transverse wave; calculating the anisotropy coefficients according to the time difference between the quick transverse wave and the slow transverse wave; repeating the steps from calculation time window selection to anisotropy coefficient calculation for the next to-be-handled sampling point until calculation on seismic data is completed. According to the invention, judgment is made on calculation results by adopting adiscrimination method, so that areas with distinctive non-development of fractures are removed and accuracy in fracture development statistics is improved.

The invention discloses a pilot protection method based on Spearman rank correlation coefficient. The method comprises the following steps: firstly acquiring fault features of different types of supply transient current according to transient short-circuit current expressions of different types of power supply; measuring waveform difference of transient current at two sides when an internal of thenew energy terminal outgoing line occurs by utilizing the Spearman rank correlation coefficient; and distinguishing the internal and external faults according to the waveform difference of transientcurrent at two sides when the internal fault occurs, thereby realizing the pilot protection on the new energy terminal outgoing line. By utilizing the method disclosed by the invention, the internal and external faults can be reliably distinguished, and the reliable pilot protection on the new energy terminal outgoing line is realized.

The invention relates to a cross-correlation and autocorrelation cascade based frame synchronizing method, which includes: 1) repeatedly modulating a synchronizing sequence in length of N twice at a transmitting end to serve as a frame header of a physical layer frame, transmitting radio signals to a receiving end through a signal generator, sampling the radio signals to be a discrete sequence after the receiving end receives the radio signals; 2) subjecting the received discrete sequence to sliding cross-correlation operation through the local-storage synchronization sequence at the receiving end and obtaining a first secondary correlation output sequence; 3) subjecting the first secondary correlation sequence in the step 2) at the receiving end to obtain a second secondary correlation output sequence; and 4) finishing frame synchronization since any moment is the starting moment of the physical layer frame if sampling point value of the first secondary correlation output sequence at any moment is larger than a set threshold value output by first secondary correlation and a sampling point value in the second secondary correlation output sequence is larger than a set threshold value output by second secondary correlation.

The invention discloses an AC-DC hybrid power grid probability power flow analysis method taking regard of rank correlation among multiple types of nondeterminacy sources and aims to solve a problem of compliance to rank correlation among different distribution type random variables caused by access of multiple types of new energy to a power grid, such as wind energy and solar energy. According to the method, probabilistic power flow analysis on an AC-DC hybrid power grid is carried out, and thereby safe and reliable operation is guaranteed.

The invention discloses a machine tool cross beam optimal design assessment method adopting combination weighing-grey correlation. The machine tool cross beam optimal design assessment method comprises the following steps that three-dimensional modeling is conducted on original cross beams, and static and dynamic characteristics of the original cross beams are analyzed to determine optimized factors and assessment indexes of the cross beams; cross beams of multiple structural schemes are designed, and several optimal schemes are preliminarily screened by analyzing and comparing static parameters of the cross beams; for the preliminarily screened schemes, cross beam rib plate structures, rib plate thickness and guide rail supporting rib plate inclination angles on the cross beams serve as test factors, the levels of the factors are determined, and an orthogonal test table is selected to conduct a simulation test on parameter combinations; simulation data is analyzed and processed by adopting a grey correlation method and a combination weighing method to obtain an optimal scheme; properties of the cross beams before and after optimization are compared to determine the reasonability of the optimal design parameter combinations. The machine tool cross beam optimal design assessment method makes a final analysis result real and reliable and accord with objective reality.

The invention discloses a method for evaluating NOR and NAND flash memory performance. The method is used for solving the technical problem of poor comprehensive operational capability of a present flash memory performance evaluation method. According to the technical scheme, the method comprises the following steps: firstly, testing a read-write speed U1 of the flash memory, and then testing the mounting time U2 of the flash memory, the average loss U3 of the flash memory, the memory consumption U4 of the flash memory, the hardware read/write speed U5 of the flash memory, the erasing speed U6 of the flash memory, the erasing energy consumption U7 of the flash memory, the hardware read/write energy consumption U8 of the flash memory and the file system energy consumption U9 of the flash memory in turn, and finally adopting a rank correlation analysis method for comprehensively evaluating the indexes from U1 to U9. The comprehensive evaluation for 9 indexes related to read-write, loading, erasing and energy consumption of the flash memory is adopted; the read-write speed, the file system operation capacity and the energy consumption related to the performance test for the flash memory are estimated; a corresponding index system is supplied for the three aspects of file system, hardware driving and energy consumption; and a rank correlation method is adopted for carrying out comprehensive evaluation and calculation, so that a test result can reflect the comprehensive capacity of the flash memory in the aspects of read-write, loading, erasing and energy consumption.

The invention discloses a method for optimizing parameters of a contact line and a pantograph based on sensitivity analysis. According to bow-net contact pressure during running of a high speed train, the existing problem is analyzed, level value design of the parameters is carried out through central composite design, and multi-factor and five-level parameters are obtained; an Spearman rank correlation coefficient method is adopted to compute correlation coefficients between the parameters of the contact line and the pantograph and the contact pressure to judge the correlation; and an Sobol method is adopted to compute sensitivity coefficients of the parameters of the contact line and the pantograph about the contact pressure, judge the impact of the parameters on the contact pressure and determine an optimization order of the parameters when the bow-net parameter optimization is carried out, after each index meets relevant standard requirements, optimization is ended and all bow-net parameter values are output. The method has reasonable optimization, and the parameters of the contact line and the pantograph can be adjusted quickly and reasonably, so that the contact pressure of the parameters of the contact line and the pantograph can be controlled reasonably.

A method and apparatus of identification by extracting and matching biometric detail from a subcutaneous vein infrared image. The image's Region of Interest is identified and artifacts are removed. A bank of filters, such as Symmetric Gabor Filters, Complex Gabor Filters, Log Gabor Filters, Oriented Gaussian Functions, or Wavelets, filters the image into a set of key value images that are subdivided into regions. An enrollment key, defined by ordered statistical measures of pixel intensities within the regions, is compared using a distance metric to a stored verification key. Various statistical measures may be used, such as variance, standard deviation, mean, absolute average deviation, max value, min value, max absolute value, median value, or a combination of these statistical measures. Various distance metrics may be used, such as Euclidean, Hamming, Euclidean Squared, Manhattan, Pearson Correlation, Pearson Squared Correlation, Chebychev, or Spearman Rank Correlation.