103 results about "Linear correlation" patented technology

This invention discloses a downconversion fluorescence thermometry method based on bilinear mode, implemented using a hardware system. The hardware system includes a 280nm light-emitting diode, two convex lenses, and a Tb... 3+ :Cs2Na 0.9 Ag 0.1 The system comprises InCl6 temperature-sensing material, a grating spectrometer, an oscilloscope, a signal generator, a computer, and a thermostat. The specific implementation steps are: signal excitation and acquisition; temperature calibration; actual temperature measurement; and high measurement accuracy: VPR mode linear correlation coefficient R² ≥ 0.998, FL mode linear correlation coefficient R² ≥ 0.992, avoiding measurement errors introduced by the exponential bias or correction term of traditional FIR technology, thus fundamentally improving temperature measurement accuracy.

The invention relates to the technical field of atmospheric boundary layer height prediction, and discloses a multi-meteorological parameter coupling-oriented atmospheric boundary layer height prediction method, which comprises the following steps of: acquiring meteorological data, and preprocessing the meteorological data; analyzing linear correlation between meteorological parameters and pollution parameters in the meteorological data and the height of an atmospheric boundary layer, and screening thermal characteristics, dynamic characteristics and pollution characteristics from the linear correlation as a multivariate characteristic set; constructing a prediction model based on a bidirectional long-short-term memory network and an attention mechanism, and performing automatic optimization on model hyper-parameters by adopting a Bayesian optimization method to obtain an optimized prediction model; and predicting the height of the atmospheric boundary layer by using the optimized prediction model. According to the invention, high-precision and high-reliability atmospheric boundary layer height prediction data support is provided for short-term pollution early warning and environment management.

The invention relates to the technical field of model construction, in particular to a displacement fluid and shale rock imbibition law numerical simulation method and system. According to the method, by quantitatively analyzing the linear correlation degree of granularity and experimental capillary constant distribution and the disturbance degree of local feature points, regularization parameters of a regression algorithm are dynamically adjusted, and on the basis of accurately-calibrated capillary constants, a contact angle is determined by combining permeability characteristic data of probe liquid, so that the permeability of the probe liquid is determined. According to the method, shale surface free energy is obtained through surface energy component theoretical model decoupling, the interface action state of displacement fluid, shale and crude oil is reflected through a three-phase contact angle determined through a three-phase equilibrium relation, and the adhesion work needed by shale oil stripping is obtained. According to the method, the high-precision fitting model of the granularity and the capillary constant is established, and the surface energy component theory is combined, so that more accurate calculation of the shale oil stripping adhesion work is realized, and a reliable numerical simulation basis is provided for improving the shale oil recovery ratio.

The invention discloses a health state monitoring method and system based on big data multi-dimensional evaluation, and relates to the cross technical field of health monitoring, big data processing and quantum machine learning. Through multi-source health data collection and in combination with quantization coding and high-dimensional data dimension reduction technologies, core low-dimensional feature vectors are effectively extracted, further, nonlinear correlation features in the feature vectors are deeply mined through a quantum neural network model, comprehensive and accurate evaluation of the health state of the user is achieved, and the user health state evaluation accuracy is improved. The multi-dimensional and deep evaluation mode can reflect the health state of the user more accurately, and provides a more reliable basis for subsequent early warning and intervention.

The invention relates to a heavy-load locomotive wheel remaining service life prediction method based on an abrasion rule, and relates to the technical field of heavy-load locomotive operation and maintenance, and the method comprises the steps: collecting wheel basic data, turning repair data, operation data and line data; analyzing the linear correlation between the continuous variable and the abrasion loss by adopting a Pearson's correlation coefficient, carrying out hypothesis testing, and outputting a significance degree factor influencing the wheel abrasion; the wheel diameter average ten thousand kilometer abrasion loss and the wheel flange average ten thousand kilometer abrasion loss corresponding to all the working conditions are obtained; in each iteration, according to the current wheel state and the working condition, calling the average ten thousand kilometer abrasion loss of the wheel diameter and the average ten thousand kilometer abrasion loss of the wheel flange corresponding to each working condition; and training the random forest model by taking the running mileage, the abrasion loss and the line condition as input characteristics, and outputting a corrected accumulated running mileage prediction result. Scientific basis is provided for operation and maintenance management of heavy-duty locomotive wheels, and safety and economical efficiency of heavy-duty railway transportation are improved.

This invention discloses a lightweight modeling method, apparatus, system, and storage medium for high-dimensional data meteorological forecasting tasks, belonging to the technical field of computation, extrapolation, or counting. The method constructs prediction vectors and target variables from the original high-dimensional data required for the target meteorological forecasting task. Through an improved variational autoencoder strategy, it reconstructs latent predictor variables that influence or potentially influence the target variables from the prediction vectors. It then selects latent variables highly correlated with the original predictor variables to construct a candidate predictor variable dataset. After removing candidate variables that are significantly uncorrelated with the target variables and those with strong linear correlations from the candidate predictor variable dataset, it performs key predictor variable selection and constructs a lightweight prediction model based on the key predictor variables. This invention significantly reduces the dimensionality of the model input data while maintaining prediction accuracy, and enhances the model's prediction accuracy by constructing predictor variables that influence the target variables and have clear physical meaning.

The invention relates to the technical field of rural carbon source abnormity diagnosis, and discloses a machine learning diagnosis method for rural carbon source abnormity. The method comprises the following steps: step 1, setting inspection points, acquiring management data of all carbon sources of a country, actual measurement data of all the inspection points and management data of fluctuation factors, and classifying to form a data set; 2, the distribution rationality of rural carbon source inspection points is evaluated, a coverage index is generated, different rural carbon source structures are adapted, and the comprehensive adaptation precision is high; 3, evaluating the linear correlation degree of the greenhouse gas total CO2 equivalent of all inspection points and the linear distance between the inspection points, generating a correlation coefficient, and accurately judging the risk of carbon source leakage; 4, a fixed threshold value is set, corresponding management measures are triggered, the problems of insufficient routing inspection coverage, carbon source leakage and the like are rapidly solved, and the prevention and control timeliness is improved; and 5, monitoring and evaluating the abnormal degree of the rural carbon source, generating an abnormal score, and triggering management measures, so that the abnormal response is more timely.

This invention discloses a method and system for joint inversion of structural constraints based on Cauchy's inequality. It proposes a Cauchy inequality constraint applicable to structural constraints, achieving a linear correlation between the model's gradient vector set. Simultaneously, it calculates structural constraints separately according to different directions, constructing a structural constraint inversion. The directions can be freely combined as needed, including four directions: horizontal, vertical, 45° inclined, and 135°. The corresponding gradients and partial derivatives are obtained by discretizing the directions, with different weighting coefficients configured. Different directional combinations can better simulate the distribution characteristics of actual geological subsurface space. This method overcomes the limitation of previous structural constraint inversion techniques that lack consideration of the spatial differences of actual geological bodies. Furthermore, by explicitly expressing the gradients in different directions, it reduces the computational complexity of joint inversion using Cauchy's inequality constraints.

The invention relates to a qualitative and quantitative method for liensinine perchlorate. The qualitative method comprises the following steps: weighing 1mg of liensinine perchlorate and 1mg of liensinine, uniformly grinding and tabletting the liensinine perchlorate and the liensinine with 100mg of potassium bromide respectively, acquiring an infrared spectrum of 4000-400cm <-1 > by adopting an infrared spectrometer, and comparing spectrograms to find that the peak shapes of the liensinine perchlorate and the liensinine are similar, the peak shapes of the liensinine perchlorate and the liensinine perchlorate are common characteristic peaks and the peak shapes of the liensinine perchlorate are unique characteristic peaks of the liensinine perchlorate and the liensinine are common characteristic peaks and the peak shapes of the The quantitative method comprises the following steps: weighing a series of liensinine perchlorate reference substances with different masses, uniformly grinding and tabletting the liensinine perchlorate reference substances and 100mg of potassium bromide respectively, collecting an infrared spectrum, carrying out integration on a 625cm <-1 > characteristic peak to obtain a peak area, and drawing a standard curve by taking the peak area as a vertical coordinate and taking the sampling mass of the reference substances as a horizontal coordinate; the method comprises the following steps: weighing a sample to be detected, collecting an infrared spectrum, integrating a 625cm <-1 > characteristic peak to obtain a peak area, substituting the peak area into the standard curve equation, calculating the mass of the liensinine perchlorate in the sample, and substituting the mass into the content calculation formula to obtain the content of the liensinine perchlorate in the sample. The method is good in precision, repeatability and stability, wide in linear range, high in linear correlation coefficient and high in recovery rate, the problem that liensinine interference cannot be avoided in an existing content determination method is effectively solved, whether liensinine perchlorate is generated or not can be qualitatively judged, and the quantity of liensinine perchlorate generated can be quantitatively detected; and a feasible new method is provided for production process optimization and quality evaluation of liensinine perchlorate.

Disclosed are a monitoring method and a monitoring device for irrigation water use (IWU), a computer device and a non-transitory computer readable medium. The method includes: determining a linear correlation between a first evapotranspiration (ET), a first soil water storage, and a monthly reference ET of a target region according to a first data set in response to a monitoring instruction from a user; determining multiple second soil water storages of the target region based on a second data set, and the linear correlation of the first ET, the first soil water storage, and the monthly reference ET of the target region; determining the IWU of the target region according to the first ET, the second ET, the first soil water storage, the second soil water storage of the target region, and the first preset correlation.

The application is a modified asphalt mixing equipment monitoring method and system based on MEMS, and relates to the technical field of equipment state monitoring, comprising: a redundant sensor deployment and pairing module; a consistency index real-time calculation module; a judgment and alarm triggering module.In the application, the standardized deployment and pairing of the redundant sensors eliminates the system error of traditional sensors due to parameter and installation differences from selection, installation to software binding; the two-dimensional analysis of the time domain linear correlation coefficient and the frequency domain energy correlation coefficient is adopted, and then the weight factor is fused into a consistency index, which not only avoids the limitations of single-dimensional judgment, but also comprehensively and accurately identifies the potential faults of the sensor itself and the key components of the equipment, effectively reduces false positives and false negatives, and provides a reliable basis for the preventive maintenance of the modified asphalt mixing equipment.

Disclosed are a method for screening a riboswitch capable of specifically recognizing doxycycline as well as rational engineering and application of the riboswitch, and belongs to the field of gene expression regulation. The present disclosure provides a doxycycline specific riboswitch, and establishes a high-throughput screening method based on flow cytometry, and obtains the doxycycline riboswitch with further improved activation fold by way of computer-aided prediction of binding sites of the riboswitch and calculation of mutation sites. According to a dose-response curve, the riboswitch shows linear correlation at 40-100 μg / L, and meanwhile, a whole-cell sensor constructed is low in price, high in stability and simple to operate, and can be used for on-site rapid detection.

The application discloses a detection method for cathode fluid distribution of a proton exchange membrane fuel cell stack, which is characterized by utilizing the relationship between the characteristic frequency of the flow channel impedance and the stoichiometric ratio of the cathode fluid (f ch The linear correlation between 1 / ln(1-1 / λ) and 1 / ln(1-1 / λ) is used to determine the cathode fluid distribution of each cell in the stack. The detection method is simple, practical and effective. All parameters are extracted from the real-time measured electrochemical impedance spectrum, without the need for prior correction, which is of great significance for high consistency stack design and health state monitoring of each cell in the stack.

The application relates to the technical field of network catering services, in particular to a catering takeout platform scoring method based on XGBoost-PCA, which comprises the following steps: constructing a modular scoring system; performing normalization processing on the data of each module; calculating the original module scores of each module based on an XGBoost algorithm; performing dimension reduction on the original module scores by adopting a PCA principal component analysis algorithm; and performing weighted summation on the module dimension reduction scores to obtain a final platform score; the application constructs multiple decision trees by XGBoost, calculates the gain of different features at a split node, identifies the index with the largest contribution to the prediction result and eliminates the redundant weak features, and further combines PCA to analyze the linear correlation between the features, eliminates the linear redundancy by maximizing the variance, and obtains the dimension reduction comprehensive score, which removes the repeated potential factors in the original data, avoids repeated calculation of these factors in subsequent evaluation, and thus ensures the objectivity of the evaluation.

The invention discloses a method for researching correlation between sweet substances in rose essential oil and a sensor based on an electronic nose, and belongs to the technical field of tobacco flavor detection.The method comprises the following steps that firstly, main sweet substances in the rose essential oil are added into cigarettes, and the content of the sweet substances in the rose essential oil is determined by combining sensory rating and grey correlation degree analysis; screening out aroma substances and other sensory qualities which are remarkably related to the sweetness; preparing solutions with different concentration gradients from the screened aroma substances remarkably related to the sweet feeling, scoring the odor intensity and testing the electronic nose to respectively obtain original response data values of the sensor to the aroma substances, and establishing linear correlation analysis through SPSS software to obtain the original response data values of the sensor to the aroma substances. Finally, finding out the electronic nose sensor with the strongest correlation with the sweet substances as WLSGF / A, wherein the correlation between the rose oxide and the WLSGF / A is the best; according to the method, mathematical statistics is combined with sense organs and the electronic nose, so that objective and efficient evaluation of the sweet aroma is realized.

This application discloses a model processing method, apparatus, device, storage medium, and program product, relating to the field of artificial intelligence technology. In the method of this application, singular value decomposition is performed on the network weight matrix of a hybrid expert model, and columns with singular values ​​less than a threshold are selected from the resulting right singular vector matrix as the null basis matrix. Thus, the null basis matrix can characterize the activation mode directions that contribute less to the activation of the expert network. Furthermore, a sub-network weight matrix is ​​constructed based on the columns of the null basis matrix and the network weight matrix. In this way, the proximity of the linear correlation between each column of the network weight matrix and the null basis matrix can be determined based on the maximum and minimum singular values ​​of the sub-network weight matrix, thereby determining the ineffective feature sensitivity of each expert network, and pruning the network parameters of the hybrid expert model based on the ineffective feature sensitivity. This reduces the number of model parameters.

This invention discloses a method, device, and medium for determining bandgap width based on linear region identification. The method includes: acquiring spectral data of the material to be tested and converting the spectral data into a Tauc plot; segmenting the Tauc plot into data segments and calculating the linear correlation coefficient of each data segment; identifying multiple candidate linear regions within the data segments based on the linear correlation coefficient; filtering target linear regions based on the candidate linear regions and performing linear fitting on the target linear regions to obtain the bandgap width of the material to be tested. By segmenting the Tauc plot into data segments and calculating the linear correlation coefficient for linear region filtering, the objectivity, accuracy, robustness, and efficiency of bandgap width determination can be improved, avoiding the errors and inefficiencies of manual bandgap width determination.

The application discloses a data security communication method of a 6G terahertz communication system, and relates to the technical field of data processing, wherein a key generation strategy combining continuous randomization and multi-dimensional target optimization is used to generate all round keys of a symmetric encryption algorithm, so that each round key generated is kept to have maximum difference with previous keys in mathematical characteristics, linear correlation between the keys is reduced, the ability to resist differential analysis and linear analysis is enhanced, all round keys of the symmetric encryption algorithm are combined to form a total key, and fragmentation processing is performed on the total key; the fragmented key obtained through the fragmentation processing is encrypted and transmitted by using the public key of a receiver in the 6G terahertz communication system; even if part of the fragments are intercepted in the transmission process, an attacker cannot restore the complete key; and the total key can be obtained only after a sufficient number of fragments are collected and decrypted by combining the private key, so that the security of key distribution is improved, and the method is suitable for the complex environment of 6G terahertz communication.

The invention discloses a coding and decoding method and device, a solving method and device, an encryption method, a learning method and a chip, and relates to the technical field of data processing. The encoding and decoding method comprises the following steps: constructing a linear equation set based on a preset key value table, and obtaining a coefficient matrix of the linear equation set; solving a maximum linear independence group of the coefficient matrix, and adding preset key value pairs corresponding to rows except linear independence rows in the maximum linear independence group into a linear correlation set; updating the system of linear equations based on the linear correlation set, and obtaining a coding vector based on the updated system of linear equations; for the query key, the query key is decoded based on the encoding vector and the linear correlation set. According to the method, the coding success can be ensured by setting the linear correlation set, and the coefficient of the storage overhead can be reduced, so that the storage overhead can be saved, and the query efficiency is improved.

The invention discloses an evaluation method for predicting the fatigue life of a deep-sea flexible pipeline, and the method comprises the steps: calculating a product of a preset corrosion coefficient, a preset flow velocity sensitive index power of a seawater flow velocity and a correction index factor of a seawater temperature, so as to obtain an instantaneous corrosion damage rate and accumulated corrosion damage, calculating the product of the reference elastic modulus and the temperature sensitive correction term to obtain the elastic modulus, and calculating the ratio of the product of a preset stress coefficient and the square of the seawater flow velocity to the elastic modulus to obtain the bending stress, and calculating the product of the preset fatigue damage coefficient, the seawater flow velocity and the preset material fatigue sensitivity index power of the bending stress to obtain a fatigue damage rate and accumulated fatigue damage, obtaining total accumulated damage through a nonlinear interactive coupling model, and obtaining the total service life through a linear correlation model. Therefore, the coupling effect of the seawater flow velocity and temperature and the interaction effect of corrosion and fatigue damage can be comprehensively considered, and the precision of predicting the fatigue life of the deep-sea flexible pipeline is improved.

The present application relates to the technical field of production control, in particular to a kind of online coating data remote acquisition and analysis method and device of heat-sensitive paper production line.The method analyzes heat-sensitive paper image and each information in coating time on time sequence.Analyze the thickness change and shape change between adjacent time, which can effectively quantify the thickness change significance of each thickness area. Quantify the first coating unevenness at each time. Analyzing the linear correlation between the first coating unevenness and the ambient humidity can evaluate the influence of humidity in the current environment, obtain the second coating unevenness, obtain the influence weight of each parameter data on the doctor blade, and adjust the real-time parameter data based on the adjustment amount. The present application quantifies the real unevenness caused by the wear of the doctor blade by analyzing the thickness change and other characteristics in the coating process of heat-sensitive paper on time sequence in real time, combined with the influence of ambient humidity on coating thickness, and then adjusts the doctor blade parameters to avoid further wear of the doctor blade in time.

The invention discloses a pulsed eddy current thickness evaluation method based on symmetric entropy. Comprising the following steps: establishing a three-layer pulsed eddy current analysis simulation model of air in a pipeline, a pipeline wall and a coating layer; performing differential normalization on the detection signal to obtain a preprocessed signal; equally dividing the pre-processed signal into N discrete event intervals according to a time sequence, calculating local energy of the pre-processed signal and a mirror image signal in each interval, and normalizing the local energy into two groups of probability density functions; constructing a symmetric entropy characteristic quantity based on the Shannon information entropy so as to represent signal energy distribution symmetry change; symmetrical entropies of different known thicknesses are collected, and a quantitative mapping model between the symmetrical entropies and the pipeline thicknesses is established; and substituting the symmetric entropy value of the detection signal into the fitting curve to realize inversion and quantitative evaluation of the pipeline thickness. The pulsed eddy current thickness evaluation method provided by the invention shows good linear correlation in thickness quantification and shows strong robustness under lift-off interference.

The application discloses an ultrasonic rolling and dynamic stress real-time regulation integrated device and belongs to the technical field of ultrasonic rolling, which comprises a machine tool, a horizontal sliding table slidingly arranged along the length direction of the machine tool, and a sliding seat slidingly assembled on the top of the horizontal sliding table. The horizontal sliding cooperation of the mounting block and the sleeve pipe, in combination with a special counterweight mechanism composed of a limiting ring, a counterweight ring, a plug rod and a supporting plate, can provide constant and accurately adjustable static pressure for the rolling process. In addition, the adaptability of the limiting ring from top to bottom with the gradual change of the inner diameter and the outer diameter of the counterweight ring enables the automatic increase and decrease of the counterweight by controlling the lifting height of the guide block two, without the need for complex manual operation. The application solves the problems of over-processing of the convex area and insufficient processing of the concave area caused by the linear correlation between the traditional spring elastic force and the deformation amount, ensures the uniform distribution of the residual compressive stress on the workpiece surface, significantly improves the strengthening consistency of ultrasonic rolling, and adapts to complex working conditions with different topography errors and material hardness.

The application discloses a tunnel lining image distortion correction method and relates to the technical field of image correction. The method comprises the following steps: establishing a camera coordinate system, an object coordinate system and an image coordinate system; analyzing the tunnel lining image distortion causes; fitting the known coordinate points of the tunnel lining profile by using the least square method, determining the center and radius of the tunnel lining arc; establishing a mapping model of the image element and the parameter angle, and solving the parameter angle by using the Newton iteration method; based on the solved parameter angle, establishing a linear correlation model of the arc length and the parameter angle, and then obtaining a nonlinear curve of the image element and the arc length; constructing a uniform correction coordinate model to correct the nonlinear curve of the image element and the arc length, so that the image element and the arc length are linearly correlated, and then combining the bilinear interpolation to perform tunnel lining image resampling. The application can realize the elimination of the stretching distortion through the correction process of the arc fitting-perspective mapping-uniformization, and achieves the imaging effect of the equivalent parallel straight line segments.

This application discloses a method for handling data anomalies in photovoltaic power prediction acquisition devices, belonging to the field of power technology. The method includes: synchronously acquiring and storing multidimensional meteorological data and actual power generation data of the photovoltaic system to obtain raw data; performing linear correlation and nonlinear correlation analysis of the raw data using the maximum information coefficient to obtain core input features; identifying and marking anomalies in the core input features and removing the anomalies to obtain de-anomaly-removed data; and performing iterative interpolation on the de-anomaly-removed data to obtain imputed data and outputting it. This method solves the problems of insufficient accuracy in photovoltaic power data processing and inaccurate identification of key information in existing technologies, thereby improving the accuracy of photovoltaic power data analysis and processing.

The invention discloses a laser radar photon accumulation effect compensation method dynamically adaptive to multiple scenes, and relates to the technical field of laser radars, and the method comprises the steps: calculating a signal detection rate and a noise detection rate according to simulation parameters and simulation data of a laser radar; calculating the steady-state detection probability density according to the signal detection rate, the noise detection rate and the photon arrival rate; establishing a linear incidence matrix of ideal photon arrival time distribution and an actual measurement histogram as a sensing matrix according to the steady-state detection probability density and the laser full width at half maximum; ideal photon arrival time distribution is recovered from the actually measured histogram according to the sensing matrix; and taking a peak value time bin corresponding to a peak value of the ideal photon arrival time distribution, and calculating coordinates of a laser radar detection target according to the peak value time bin. According to the invention, the problem of photon accumulation effect is solved by recovering ideal photon arrival time distribution, and the detection precision is improved.

The application belongs to the technical field of sewage detection, and provides a norovirus GI and GII double genotype synchronous quantitative detection method, which realizes synchronous detection and absolute quantification of norovirus GI and GII in the same reaction tube, does not need to rely on a standard curve, and avoids errors caused by batch differences of standard products; in terms of primer and probe design, the constructed detection system shows high specificity, and even under the coexistence condition of other viruses with close genetic relationship, no non-specific amplification occurs; through gradient dilution experiment verification, the digital PCR method shows good linear response in a wide dynamic range, excellent linear correlation, low repeat variation coefficient, and shows excellent detection consistency and stability; the droplet generation performance is stable, the effective droplet number is always maintained at more than 19500, and the reliability of the quantitative result is ensured.

The application provides a helicopter aerodynamic force analysis method and device considering rotor interference with aerodynamic components, and the method comprises the following steps: calculating a critical inflection point of a position relationship between downwash of a helicopter rotor and a plurality of aerodynamic components and a wake tilt angle of the helicopter according to a back chamfer of the helicopter rotor; establishing a linear correlation between an interference coefficient of the critical inflection point and the wake tilt angle, and obtaining a target three-axis speed of a target aerodynamic component under the interference of the helicopter rotor according to the linear correlation and three-axis speed of the helicopter, and analyzing aerodynamic force of the helicopter according to the target three-axis speed; wherein the target aerodynamic component belongs to the plurality of aerodynamic components. The method improves the simulation effect of the flight performance of the helicopter, and improves the efficiency and accuracy of the helicopter aerodynamic force analysis.

The invention provides a real-time closed-cup flash point prediction method based on a trace distillation range measuring device, and relates to the technical field of distillation ranges and flash point tests.The method comprises the following steps that a preorder distillation range temperature set is obtained in real time, and the preorder distillation range temperature set comprises initial steam temperatures corresponding to a plurality of preset recovery volume percentage nodes; the steam pressure and the liquid temperature are obtained in real time to obtain the steam pressure change rate and the liquid temperature change gradient, and then the heat capacity disturbance factor of the device is calculated; correcting each initial steam temperature in the preorder distillation range temperature group in real time by using a heat capacity disturbance factor to obtain a corresponding first corrected steam temperature; and calculating and predicting the closed-cup flash point through linear weighting calculation of each first corrected steam temperature based on a weight distribution relation pre-established by the test steam temperature of the preset recovery volume percentage node and the linear correlation characteristic of the closed-cup flash point. According to the method, the closed-cup flash point is predicted while the distillation range is measured, and time and samples are remarkably saved.

This invention discloses a method for stabilizing prostate-specific antigen (PSA) standards, a matrix calibration method, and an evaluation method for test kits, belonging to the field of in vitro diagnostics and biometabolic technology. This application establishes a linear correlation between buffer matrix and serum matrix PSA detection results, deriving a specific matrix calibration conversion function that can convert buffer matrix PSA detection values ​​into equivalent serum matrix detection values, effectively offsetting detection errors caused by matrix effects. Experimental data show that after correction using this method, the average absolute bias of PSA detection decreased from 125.82% to 21.01%, and the accuracy after correction meets clinical application requirements. This method enables the replacement of traditional serum matrix calibrators with highly stable, low-cost buffer matrix calibrators, significantly reducing the production and application costs of PSA test kits.