30 results about "Linear correlation analysis" patented technology

The invention provides a fault self-diagnostics method for multi-sensor system, which includes the following steps: firstly, carrying out linear analysis to the information obtained from each sensor of the multi-sensor system having relativity output, and then comparing corresponding relativity and setting threshold value to realize sensor array fault self-diagnostics of the multi-sensor, wherein, as the number of the sensor having relativity output is two, fault-diagnostics of the sensor system can be realized thereby providing alarm information; as the number of the sensor having relativity output is three, fault-diagnostics of the sensor system can be realized thereby providing alarm information and isolating the fault to guarantee normal operation of the system. The effects of the invention are that self-diagnostics, alarm and fault-isolation for the sensor are realized and single system for monitoring sensor operation status is saved thereby simplifying the system configuration and increasing stability of the self-diagnostics system through using the relativity between the information measured by each sensor in the multi-sensor system and using multi-channel measuring signal.

The invention relates to a method for judging abnormal electricity consumption behaviors of users based on an EEMD method. The method comprises the following steps of S1, carrying out cluster on electrical loads of the users by adopting a self-organizing map neural network method; S2, selecting one cluster from the clustering results of the step S1 at random and selecting any user in the cluster at random to obtain load data on any two identical time periods; S3, decomposing data in the step S2 into an IMF component and residual trend terms by adopting an empirical mode decomposition method; S4, carrying out linear correlation analysis on load residual terms of the two time periods respectively to obtain rho1 and rho2; S5, analyzing the rho1 and the rho2. The method for judging the abnormal electricity consumption behaviors of the users based on the EEMD method enables power supply enterprises to detect the abnormal behaviors in the electricity consumption process of the users, corresponding measures can be taken, and better services can be supplied to the users.

The present invention discloses a method for evaluating the coupling relationship between the collision waveform and the restraint system property, and overcomes the problem that the CAE simulation technology has huge calculation amount and is time-consuming when the coupling relation between the vehicle body structure and the occupant restraint system is studied. The method comprises: 1. establishment of the occupant response surface based on the single-degree-of-freedom model: 1) defining shape parameters of a dual trapezoidal wave and a trilinear constraint stiffness curve, 2) solving the occupant response surface with the single-degree-of-freedom model, and 3) respectively averaging the response surface in the X and Y directions; 2. correlation analysis of occupant response and collision waveform parameters: 1) carrying out supplementary definition on the collision waveform parameters, and 2) extracting the correspondence between basic parameters of the collision waveform and the Av from the occupant response surface, and carrying out linear correlation analysis; and 3. evaluation of the coupling relation between the collision waveform and the restraint system property: 1) establishing the comprehensive evaluation index alpha of the collision waveform, 2) establishing the comprehensive evaluation index beta of the restraint system, and 3) establishing ao of the comprehensive evaluation index of the collision waveform and the restraint system.

The invention discloses a line transformation relation abnormity judgment method based on correlation between electric quantity and line loss. The line transformation relation abnormity judgment method includes a data acquisition module which is used for acquiring electric quantity information, a data processing module which is used for analyzing correlation between electric quantity and line loss, and a data display module which is used for displaying abnormal line transformation relations, wherein the data acquisition module, the data processing module and the data display module are sequentially connected. The line transformation relation abnormity judgment method utilizes power consumption, voltage, current and other data of a line and a transformer provided by a power consumption information acquisition system, and utilizes a big data analysis technology and a transformer area line loss non-linear correlation analysis method to construct the line transformation relation error correction model independent of the local communication relation and find out the line transformation relation with statistical errors, so as to improve the accuracy of topological information of the power transmission line and provide technical guidance for conducting line transformation relation on-site troubleshooting, so that the calculation precision of line loss is improved, and technical support is provided for lean marketing management.

The embodiment of the invention provides a covert fault troubleshooting method and apparatus of a 4G base station. The method comprises the following steps: obtaining relevant dimensionality data, andintegrating the relevant dimensionality data to obtain a data index set; obtaining a correlation coefficient between index items of the data index set based on a linear correlation analysis method, and performing dimensionality reduction on the data index set according to the correlation coefficient to obtain a dimensionality reduction data set; and inputting the dimensionality reduction data setinto a trained fault positioning model to obtain a fault identification result. According to the covert fault troubleshooting method and apparatus of the 4G base station provided by the embodiment ofthe invention, the AI machine learning technology is imported, the incidence relation between deep factors of various covert faults of the 4G base station are mined to form an intelligent covert fault troubleshooting model to achieve automatic identification and diagnosis of problems.

The invention discloses an estuary dam geometrical morphology measuring method. The method includes the following steps that firstly, a prototype geologic model is determined according to measuring region geological data, a physical model is established according to the similarity theory of sedimentary physical simulation, an experimental scheme is designed accordingly, an experiment is carried out on the basis of the experimental scheme and the sedimentation process is controlled; secondly, the sedimentation result is researched through a section cutting method, the position of an estuary dam is determined, length and width data of the estuary dam and the extended distance of the lake shoreline are measured, a planar distribution diagram of the estuary dam is drawn, and thickness data of the estuary dam are measured in combination with the section; thirdly, linear correlation analysis is conducted on the obtained length-thickness and length-width data of the estuary dam; fourthly, modern sedimentation estuary dam length and width data measured on the basis of satellite photos are obtained, statistical analysis is conducted on the modern sedimentation estuary dam length and width data, and a research area estuary dam length-width empirical formula is established by synthesizing water tank simulation and modern sedimentation measuring results. The method has the advantage of being capable of guiding exquisite configuration anatomy of a work area estuary dam and can be widely applied to the technical field of reservoir description.

The invention discloses a method and a device for quantitatively distinguishing massive sandstones of the main body of a phase control sand body structure. The method comprises: dividing small layersand taking the comprehensive logging interpretation result as the object of the sand body structure research; performing linear correlation analysis on specified parameters and shale content, selecting top N items with better correlation as the basis of the comprehensive index method, and obtaining the threshold value of the specified parameters according to different log series values and core measured data corresponding to massive sandstones and bedding sandstones; determining a weight coefficient corresponding to each specified parameter; performing data standardization processing on top Nspecified parameters, and calculating the comprehensive index for the parameters after the data standardization processing, in which a weight based on the shale content is used as a coefficient and the directly / inversely proportional relationship of electrical characteristic of the massive sandstones is used as a basis; calculating the smoothness of the comprehensive index through a variance formula and a variation formula. According to the method and the device for quantitatively distinguishing the massive sandstones of the main body of the phase control sand body structure, the massive sandstones can be accurately identified to guide the fine exploration and development of lithological oil-gas reservoir.

The invention provides a method for measuring factors affecting rhizosphere soil amino acid availability. The method comprises the steps that typical zonal soil is collected for sample pretreatment comprising screening and grinding, the soil is placed into an artificial greenhouse for culturing plants, labeled amino acid is added, the soil plant sample treatment is performed to measure the physicochemical property of the soil, linear correlation analysis is carried out on the physicochemical property of the soil and the amino acid absorptive amount, and the main soil factors affecting the soil amino acid biological validity are researched. The method is easy to implement, the factors affecting the amino acid biological availability significantly can be found from complex factors through correlation detection, and a method foundation is provided for researching and controlling amino acid biological availability.

The invention provides a method for rapidly identifying shallow lake sediment pollution layering information through shallow cutting. The method comprises the following steps of: scanning by a shallow cutting device, collecting a columnar sample, analyzing the columnar sample and linear correlation, and finally drawing a contour map to obtain a sediment pollution layering result. According to the method for rapidly identifying the shallow lake sediment pollution layering information through shallow cutting, on the basis of shallow cutting scanning and columnar sample pollutant determination, linear correlation analysis of the water content and the pollutant content of the sediment in each layer is added, so that the pollution layering information of the sediment in the lake is rapidly identified through shallow cutting.

The invention discloses an efficient control method for realizing optical network construction on the basis of linear correlation analysis, and belongs to the technical field of communications. According to the method, multi-dimensional optimized decomposition is carried out on optical access network hotspots by adopting linear correlation of feature vectors, and the most suitable construction models are matched to satisfy the construction demands of the hotspots. According to the method, linear matching of the optical access network hotspots and the construction optimized models is newly provided, an approximation set is found, a Bayesian network is constructed to carry out decision judgement, and the optimum construction models are selected to realize the efficient construction of the hotspots.

The invention discloses a calculation method for quickly determining phreatic water level fluctuation characteristics. The calculation method comprises the following steps: determining a target analysis area of phreatic water level fluctuation characteristics; collecting rainfall data and phreatic water level monitoring well actual measurement data in an administrative region where the target analysis region is located; constructing a coordinate system; drawing a point diagram on a coordinate system according to the collected sum; carrying out linear correlation analysis on the drawn point graph to obtain a linear correlation linear equation; calculating a correlation coefficient R of the linear correlation linear equation to verify whether the linear correlation linear equation is established or not; and determining the submersible water level burial depth or elevation of the target analysis area by utilizing the linear correlation linear equation and the rainfall data of the target analysis area so as to analyze the submersible water level fluctuation characteristics of the target analysis area. The method has the advantages that the fluctuation characteristics of the phreatic water level can be quickly determined, and a basis is provided for evaluating migration of pollutants in underground water and investigating the environment of a polluted site.

The invention discloses a dimension reduction and correlation analysis method suitable for large-scale data, and the method comprises the steps: projecting high-dimensional data to a Fourier domain, and converting a solving feature vector problem of linear correlation analysis into a meaningful Fourier domain basis; because the Fourier domain basis is predefined and the characteristic value distribution of the data is ordered, accelerating training by inputting the training samples in batches until the required Fourier basis is stable and ordered; determining the number of Fourier bases and aprojection matrix, and multiplying the projection matrix by the high-dimensional data set to obtain a low-dimensional data set so as to facilitate rapid processing of data. According to the data dimension reduction method, on the basis of fast Fourier transform and correlation analysis, noise and redundant information in a high-dimension data set can be removed, unnecessary operation processes indata processing are reduced, and the running speed and the memory use efficiency in data dimension reduction calculation are improved.

The invention provides a method and device for clustering the states of a blast furnace. The method comprises the steps that process parameters of the states of the blast furnace are collected and preprocessed; state feature data of the process parameters is extracted; the state feature data of the process parameters is subjected to linear correlation analysis, and the linear correlation result between the state feature data is determined; when it is determined that the linear correlation result shows linear independence, a K-means algorithm is utilized for clustering the state feature data, and the clustering result of the states of the blast furnace is acquired; and thus, the states of the blast furnace are precisely divided according to the clustering result, and correlation analysis of operation and indexes can be carried out conveniently so that a blast furnace superintendent can grasp the current state of the blast furnace to precisely guide blast furnace operation.

The invention discloses a noninvasive method for determining iron content in brain tissue. The method comprises the steps of performing whole brain magnetic susceptibility imaging on participator with magnetic resonance instrument, and storing amplitude image in obtained image data; measuring average signal intensities of caudate nucleus, putamen, globus pallidus, thalamus, red nucleus, substantia nigra, frontal lobe white matter and medulla oblongata in brain region of each participator, and dividing with the average signal intensity of medulla oblongata as internal reference respectively, to obtain relative amplitude signal intensity data; performing normal distribution conversion on the obtained relative amplitude signal intensity data, performing Pearson linear correlation analysis with brain region iron content distribution data of population of same age group published by autopsy research, and fitting to obtain a simple relation equation according to correlation analysis result. The method can non-invasively accurately estimate iron content in brain, only needs measurement and calculation on a simple third-party image processing software during measurement, and needs no special workstation.

Embodiments of the present invention provide a method and device for diagnosing hidden faults of a 4G base station. The method includes: acquiring relevant dimension data, integrating the relevant dimension data to obtain a data index set; and obtaining the data index based on a linear correlation analysis method According to the correlation coefficient between the index items of the set, reduce the dimension of the data index set according to the correlation coefficient to obtain a dimension-reduced data set; input the dimension-reduced data set into the trained fault location model to obtain the fault identification result. The embodiment of the present invention provides a method and device for diagnosing hidden faults of 4G base stations, which introduces AI machine learning technology, and forms an intelligent hidden fault troubleshooting model by mining the correlation between various deep-level factors of hidden faults of 4G base stations. , to realize the automatic identification and diagnosis of problems.

The invention discloses a processing method for accurately interpolating and extending the hydrological characteristics of a design station, and aims to provide a processing method for the hydrological characteristics of a design station closer to the real value. It includes the following steps: (1) simple linear correlation analysis; (2) complete linear correlation analysis; (3) partial value calculation; and (4) physical numerical calculation of complete linear correlation. The invention is applicable to the processing of hydrological characteristics of design stations in the technical field of hydrology and water resources.

The invention provides a regional wind power modeling method, which comprises the following steps: acquiring historical power generation powers of a plurality of wind power plants in a set region, performing linear correlation analysis and clustering processing on the wind power plants in the region based on the historical power generation powers, and determining a plurality of equivalent wind power plants in the set region; according to each equivalent wind power plant, establishing an edge density function of each equivalent wind power plant by using an orthogonal series method; and according to the edge density function of each equivalent wind power plant, establishing a wind power joint probability model of a set area by using a Pair-Copula function method. Through the method, the calculation number of the wind power plants in the region is reduced, the modeling dimension is reduced, the influence of the random variable boundary effect is avoided, and the probability modeling accuracy of the generated power correlation of the wind power plants is improved.

The invention discloses an MD / QM / CSM method for extracting representative conformation of a beta-CD subject-object system. The method comprises the following steps: (1) calculating a topological structure and RESP charges of a host molecule; (2) calculating topological structures and RESP charges of guest molecules; (3) constructing an initial conformation of a subject-object compound; (4) screening dominant conformations of the host-guest compound, the host molecules and the guest molecules; (5) carrying out ECD calculation on the dominant conformation of the subject-object compound, and comparing with an ICD experiment to determine the accuracy of the screening structure; (6) calculating inclusion free energy of dominant conformations of the subject-guest compound, the subject molecules and the guest molecules by adopting a QM / CSM method, and performing linear correlation analysis on a calculated value and an experimental value. According to the method, the representative conformation of the subject-guest compound system can be accurately extracted, an accurate structural model is provided for calculation of the inclusion free energy, meanwhile, the inclusion free energy and the solvent effect in vacuum are calculated, calculation of the inclusion free energy of the subject-guest system is more perfect, and guidance is provided for experiments.

According to an application of MT-ND6 as a new target in metabolic syndrome diagnosis and treatment drugs, expression of the MT-ND6 gene in peripheral blood leucocytes of type 2 diabetes patients and livers of obese mice is remarkably reduced, meanwhile, methylation level of the MT-ND6 gene is remarkably increased, linear correlation analysis shows that the methylation level of the MT-ND6 gene is in negative correlation with expression of mRNA of the MT-ND6 gene, and in positive correlation with insulin resistance index HOMA-IR, glycosylated hemoglobin content and serum triglyceride level, and knock-down of the MT-ND6 can cause mitochondrial dysfunction, increase liver lipid droplet accumulation and reduce insulin sensitivity, indicating that the MT-ND6 gene is closely related to metabolic syndrome. The invention provides a new target for clinical diagnosis and treatment of metabolic syndrome and complications thereof, and has important application value.

The invention discloses a machine learning-based early accelerated aging diagnosis method for a ternary lithium ion battery. The method comprises the steps that 17 aging feature parameters representing the health state of the ternary lithium ion battery are extracted from a discharge capacity-voltage curve, a discharge IC curve and a discharge DV curve of the ternary lithium ion battery; then, a new combinatorial algorithm is utilized to accurately diagnose accelerated aging of the ternary lithium ion battery in an early stage, firstly, important features are selected through a random forest, then, linear correlation of the important features is reduced through linear correlation analysis, and finally, accelerated aging is judged through a logistic regression model. Accurate early diagnosis of accelerated aging of the ternary lithium ion battery is realized, so that whether accelerated aging of the ternary lithium ion battery occurs or not is judged in the early stage, and important information is provided for health state management and health state evaluation of the lithium ion battery.

The invention discloses an efficient control method for realizing optical network construction on the basis of linear correlation analysis, and belongs to the technical field of communications. According to the method, multi-dimensional optimized decomposition is carried out on optical access network hotspots by adopting linear correlation of feature vectors, and the most suitable construction models are matched to satisfy the construction demands of the hotspots. According to the method, linear matching of the optical access network hotspots and the construction optimized models is newly provided, an approximation set is found, a Bayesian network is constructed to carry out decision judgement, and the optimum construction models are selected to realize the efficient construction of the hotspots.

The invention provides a method for quickly identifying the layered information of sediment pollution in shallow lakes by shallow profile. First, the shallow profile device scans and collects columnar samples, then performs columnar sample analysis and linear correlation analysis, and finally draws a contour map to obtain Sediment contamination stratification results. The present invention provides a method for quickly identifying the layered information of sediment pollution in shallow lakes by shallow profile. On the basis of shallow profile scanning and columnar sample pollutant measurement, the linear correlation between the water content of each layered sediment and the pollutant content is added. analysis to quickly identify pollution stratification information in lake sediments through shallow profiling.

The invention provides a method for determining the factors affecting the availability of amino acids in rhizosphere soil. By collecting representative zonal soil, sample pretreatment: sieving, grinding, placing in an artificial greenhouse to cultivate plants, adding labeled amino acids, soil Plant samples were processed to measure the physical and chemical properties of the soil, and linear correlation analysis was performed with the amino acid absorption to study the main soil factors affecting the bioavailability of soil amino acids. The method of the invention is simple to operate, and the factors that significantly affect the bioavailability of amino acids can be found among complex factors through correlation detection, which provides a method basis for researching and regulating the bioavailability of amino acids.

The invention provides a fault self-diagnostics method for multi-sensor system, which includes the following steps: firstly, carrying out linear analysis to the information obtained from each sensor of the multi-sensor system having relativity output, and then comparing corresponding relativity and setting threshold value to realize sensor array fault self-diagnostics of the multi-sensor, wherein, as the number of the sensor having relativity output is two, fault-diagnostics of the sensor system can be realized thereby providing alarm information; as the number of the sensor having relativityoutput is three, fault-diagnostics of the sensor system can be realized thereby providing alarm information and isolating the fault to guarantee normal operation of the system. The effects of the invention are that self-diagnostics, alarm and fault-isolation for the sensor are realized and single system for monitoring sensor operation status is saved thereby simplifying the system configuration and increasing stability of the self-diagnostics system through using the relativity between the information measured by each sensor in the multi-sensor system and using multi-channel measuring signal.

The application of MT‑ND6 as a new target in the diagnosis and treatment of metabolic syndrome, the expression of MT‑ND6 gene in the peripheral blood leukocytes of type 2 diabetic patients and the liver of obese mice was significantly reduced, and the methylation of MT‑ND6 gene Linear correlation analysis showed that the methylation level of MT‑ND6 gene was negatively correlated with its mRNA expression, and positively correlated with insulin resistance index HOMA‑IR, glycated hemoglobin content and serum triglyceride level. ‑ND6 can cause mitochondrial dysfunction, increase liver lipid droplet accumulation, and reduce insulin sensitivity at the same time, indicating that MT‑ND6 gene is closely related to the occurrence of metabolic syndrome; the present invention provides a method for clinical diagnosis and treatment of metabolic syndrome and its complications A new target with important application value.

The invention provides a method and device for clustering the states of a blast furnace. The method comprises the steps that process parameters of the states of the blast furnace are collected and preprocessed; state feature data of the process parameters is extracted; the state feature data of the process parameters is subjected to linear correlation analysis, and the linear correlation result between the state feature data is determined; when it is determined that the linear correlation result shows linear independence, a K-means algorithm is utilized for clustering the state feature data, and the clustering result of the states of the blast furnace is acquired; and thus, the states of the blast furnace are precisely divided according to the clustering result, and correlation analysis of operation and indexes can be carried out conveniently so that a blast furnace superintendent can grasp the current state of the blast furnace to precisely guide blast furnace operation.

The invention discloses a method and a device for quantitatively distinguishing massive sandstones of the main body of a phase control sand body structure. The method comprises: dividing small layersand taking the comprehensive logging interpretation result as the object of the sand body structure research; performing linear correlation analysis on specified parameters and shale content, selecting top N items with better correlation as the basis of the comprehensive index method, and obtaining the threshold value of the specified parameters according to different log series values and core measured data corresponding to massive sandstones and bedding sandstones; determining a weight coefficient corresponding to each specified parameter; performing data standardization processing on top Nspecified parameters, and calculating the comprehensive index for the parameters after the data standardization processing, in which a weight based on the shale content is used as a coefficient and the directly / inversely proportional relationship of electrical characteristic of the massive sandstones is used as a basis; calculating the smoothness of the comprehensive index through a variance formula and a variation formula. According to the method and the device for quantitatively distinguishing the massive sandstones of the main body of the phase control sand body structure, the massive sandstones can be accurately identified to guide the fine exploration and development of lithological oil-gas reservoir.

A non-linear correlation analysis method based on joint structure constraint and incomplete multi-modal data obtains multiple modal phenotype data and weights corresponding to SNP through four steps, non-linear correlation between SNP and phenotypes is constructed through non-linear transformation, and therefore complex correlation between SNP and phenotypes is considered; and through contribution of a plurality of SNPs to phenotypes, modal sharing and modal specific biomarkers corresponding to different modalities are obtained. The minimum root-mean-square error is obviously superior to the minimum root-mean-square error value obtained by the prior art, so that the performance of detecting the biomarker can be improved.

The invention discloses a screening method for processing suitability of sweet potato chips. The screening method specifically comprises the following steps of: treating a sample and determining the quality, wherein the quality determination comprises yield, sensory evaluation indexes, chromatic aberration, rupture force, adhesion and oil content, and a comprehensive index of the processing suitability of the sweet potato chips is obtained by weighting six quality indexes according to a certain weight by using Y; then carrying out single-factor variance analysis and principal component analysis on the six indexes influencing the processing suitability of the sweet potato chips, and establishing an expression between a principal component factor and the quality indexes of the sweet potato chips; calculating correlation coefficients of the comprehensive index Y of the sweet potato chips, the quality indexes of the sweet potato chips and the principal component factor one by using a regression linear correlation analysis method; and then establishing a quality evaluation model and suitability evaluation, thus determining the processing suitability of different varieties of sweet potatoes. The screening method disclosed by the invention can provide powerful reference for actual processing of the sweet potato chips, help sweet potato chip processing manufacturers to provide scientific basis for selecting product raw materials, and can effectively reduce early trial production and investment cost of the sweet potato chip processing manufacturers.

The invention discloses an MD / QM / CSM verification method of a self-assembled supramolecular material. Cyclodextrin is used as a host molecule, and three naphthol molecules are used as guest molecules for verification. The method specifically comprises the following steps: performing MD simulation on host-guest molecules and a host-guest molecule compound, extracting a dominant conformation, and obtaining inclusion free energy from the extracted dominant conformation by using a QM / CSM method. According to the method, the clathration free energy of the subject and the object can be well obtained, linear correlation analysis is carried out on the obtained clathration free energy and the experimental value, and if good linear correlation R2 = 0.97 exists between the clathration free energy and the experimental value, the change trend is consistent with the experimental value. According to the MD / QM / CSM verification method of the self-assembled supramolecular material, an established calculation model not only can calculate composite free energy in vacuum, but also inspects a solvent effect, so that calculation of inclusion free energy of a subject-object system is more perfect. According to the model calculation method, the change trend of inclusion free energy is accurately obtained, and guidance is provided for experiments.