18 results about "Concentration curve" patented technology

The invention relates to a method for constructing an HBV (Hepatitis B Virus) related HCC (Hepatitis C Chromatography) risk model by using an ESPL1 serum marker. The method comprises the following steps: firstly, identifying and extracting key oscillation characteristic indexes in an ESPL1 concentration curve through an improved time domain-frequency domain hybrid analysis system (TF-HySys) according to the fluctuation characteristic of the serum marker concentration on a time sequence; then, a dynamic probability coupling matrix (PCM) is constructed by utilizing the obtained oscillation characteristic indexes, preset auxiliary marker concentration / characteristics and clinical characteristic data; thirdly, constructing a differential equation inversion integration model (InDiMod) based on the PCM to carry out HCC risk modeling, and outputting a comprehensive dynamic risk integral (iDRS); secondly, establishing a'risk layering-threshold dynamic linkage system '(RT-DynLink) to carry out risk layering; and finally, integrating the above steps to develop an individual HCC risk trajectory generation and visual engine (TrajGen-Vis), and providing support for clinical intervention decision.

The invention discloses a smell time sequence release control method and system, and the method comprises the steps: constructing an action network and an evaluation network of reinforcement learning, constructing a target smell concentration curve on a time sequence, obtaining a current state parameter, and inputting the state parameter into the action network; the action network outputs the action value to execute the smell release of the corresponding smell driving device, and detects the real smell concentration value and the change rate of the corresponding position on the corresponding time sequence; acquiring the odor concentration value and the change rate of the target odor concentration curve on the same time sequence, constructing a joint reward and punishment function by combining the actually detected odor concentration and the change rate of the same time sequence, updating the evaluation network by using the reward and punishment function, updating the action network to output a new action value, and driving an odor driving device according to the new action value; and calculating comparison loss under all time sequences of the target odor concentration curve, constructing a multi-time-sequence joint loss function of the target odor concentration curve, and training a reinforcement learning model based on the multi-time-sequence joint loss function.

The invention provides a mixed data regression model-based pm2.5 influence factor analysis method and system, and the method comprises the steps: building a mixed data regression model of which covariables are component data and numerical data and dependent variables are functional data: the mixed data regression model is a pm2.5 concentration curve of a city, is the functional data, is the proportion of first yield, second yield and third yield of the city, and is called the proportion of third yield for short; the data is component data, logarithm of per capita GDP, average temperature and numerical data, is a to-be-estimated component type coefficient changing along with time, is distributed to a component type covariable at any moment, is a to-be-estimated function type coefficient and is a function type residual error; obtaining robust M-estimation based on equidistant logarithmic ratio transformation, functional basis expansion and an iterative reweighted least square method; and according to the estimated values, analyzing the influence of the three-yield ratio, the per capita GDP and the average temperature of each city on the pm 2.5. The method can be used for analyzing the pm 2.5 influence factors.

The present invention relates to a method for dynamic prediction of leakage concentration field of hazardous chemical equipment based on infrared thermal imaging correction, which comprises the following steps: (1) obtaining real-time parameters from the scene; (2) adding a time variable to the Gaussian calculation model, integrating the instantaneous leakage in the infinite time range, and obtaining the critical condition of the concentration field prediction algorithm; (3) integrating the original model in a finite time, and resolving the integral result by the obtained critical condition, thereby obtaining a new dynamic prediction model in which the leakage influence range changes with time; (4) calculating the isoconcentration curve of the new dynamic prediction model; (5) combining infrared images and real-time monitoring data, and drawing the actual isoconcentration curve by edge detection technology; (6) locating the same coordinate position point on the theoretical prediction model, correcting the theoretical concentration curve with the actual concentration curve, performing overall coordinate transformation on the concentration field, and correcting the entire concentration field; (7) retaking the infrared thermal image after a certain period of time, and correcting the concentration field again. The method improves the accuracy and effectiveness of emergency response.

The present application relates to the technical field of water environment data monitoring, and particularly relates to an environmental online data abnormal clue analysis method and system, the present application receives uploaded environmental online data in a collection period, filters out first abnormal data in the environmental online data, selects a filtering standard of abnormal data, statistically processes and collates the filtered environmental online data, generates a time node-pollutant concentration curve, draws a tangent line at each time node in the curve, determines a node slope, records a node with a node slope greater than a preset node slope as an abnormal node, judges the environmental online data based on the abnormal node, generates a corresponding processing instruction or completes the abnormal clue analysis of the environmental online data based on the judgment result, and re-determines the operation parameters of the corresponding components based on the received processing instruction. The present application effectively realizes fast and accurate analysis of the obtained environmental online data, and effectively improves the use efficiency of the environmental online data.

The invention discloses a breast cancer heterogeneous component automatic segmentation and quantitative analysis method and system. The method comprises the following steps: S1, collecting multi-temporal breast DCE-MRI original image data; step S2, carrying out comprehensive preprocessing on the DCE-MRI original image data; s3, based on a deep learning technology, automatically segmenting the breast tumor and internal heterogeneous components to obtain a segmentation result; s4, based on the segmentation result, automatically generating a time-signal intensity curve and a contrast agent concentration curve; s5, fitting the generated standardized time-signal intensity curve and the contrast agent concentration curve, extracting features, and classifying the features into different dynamic enhancement modes; s6, key quantitative parameters are extracted from the standardized time-signal intensity curve, and pharmacokinetic characteristics are extracted from the contrast agent concentration curve; and S7, establishing a comprehensive analysis model. Through deep learning and image processing technologies, an objective basis is provided for accurate diagnosis, molecular typing prediction and individualized treatment of breast cancer.

The invention belongs to the technical field of groundwater pollution treatment, and discloses a dynamic evaluation method and system for the service performance of a PRB material in groundwater pollution remediation, and the method comprises the steps: obtaining a pollution remediation concentration curve, and calculating the actual removal amount of a filling material to hexavalent chromium pollutants according to the concentration curve; calculating the active surface area of the filling material, and establishing a correlation model of the active surface area and the removal performance of the filling material based on the active surface and the actual removal amount; measuring complex resistivity spectrum data of different areas at different time points of the polluted site and extracting characteristic parameters of the complex resistivity spectrum data to obtain complex resistivity characteristic parameters; and constructing a mapping model of the actual removal amount of the hexavalent chromium pollutants and the complex resistivity characteristic parameters, and performing zoned quantitative evaluation on the service performance of the filling material based on a calculation result of the mapping model. According to the invention, a whole-process dynamic evaluation system of the repair concentration, the adsorption performance and the electro-physical characteristics is integrated, and real-time dynamic monitoring and quantitative evaluation of the material performance in the in-situ repair project are realized.

This application provides a real-time air pollution monitoring system and method for industrial plants. The system clusters the emission inflection points of pollutant concentration curves at various monitoring points within the industrial plant into multiple abnormal emission events, thereby identifying pollution source monitoring points within the industrial plant. It calculates the angle between the pointing vector from the pollution source monitoring point to other monitoring points within the industrial plant and the wind direction vector, obtaining the vector angle of the pollution source monitoring point. Then, it determines the environmental impact confidence level of the pollution source monitoring point using the vector angle and the maximum pollutant concentration in each abnormal emission event. When the environmental impact confidence level is greater than the impact threshold within the industrial plant, the sampling frequency of the downwind monitoring point is optimized based on the distance between the pollution source monitoring point and the downwind monitoring point. Based on the above scheme, risk confidence assessment of pollution sources in industrial plant air pollution monitoring can be achieved, thereby improving the accuracy of capturing abnormal emission events.

The present invention relates to a carbon emission data monitoring and analysis system and method. This system addresses the problem of mixed flue gas from a multi-unit thermal power plant being unable to be traced to the source of a single unit. The system includes: a data acquisition module that obtains flue gas data from the total chimney outlet through a CEMS, calculates precise carbon emissions using humidity and dust concentration correction models, and simultaneously collects power generation, coal consumption, and concentration curves; an anomaly judgment module that comprehensively determines whether an anomaly exists based on the corresponding carbon emissions per unit power generation and coal consumption, and the distortion rate of the concentration curve; an anomaly location module that injects tracer gas into each unit and detects the tracer gas concentration at the total outlet, uses a deconvolution algorithm to infer the emission contribution rate of each unit, and identifies abnormal units; and a cause investigation module that determines an investigation sequence based on historical data and matches suspected causes. The present invention achieves decoupling and precise traceability of carbon emission data from a single unit in mixed flue gas, enabling rapid anomaly location and improving the low-carbon intelligence level of power plants.

The invention discloses a trace substance tracer monitoring method based on an intelligent algorithm, and the method comprises the following steps: screening a plurality of trace substance tracers according to the characteristics of a multilayer loose sandstone geological reservoir; calculating the dosage of the trace substance tracer according to the monitoring time and the release rate of the tracer; according to the difference of different engineering parameters, different types of tracer patches are placed in all layers and sections of the directional producing well; meanwhile, multiple rounds of collection and detection analysis are conducted on the oil-water mixed sample, and a segmented water-soluble trace substance tracer agent output concentration curve and an oil-soluble trace substance tracer agent output concentration curve are obtained; according to the corrected tracer agent concentration data, a machine learning algorithm is utilized to consider the influence of multiple factors to calculate the output contribution rates of different layer sections, and therefore the output condition of each layer section of the directional oil production well is obtained. According to the method, the output layer sections of the directional producing well are monitored by adopting various trace tracers in combination with an intelligent algorithm, so that the interlayer output change can be accurately mastered, and a reliable basis is provided for next development and adjustment.

The application relates to an air tightness detection method, device, equipment, storage medium and program product. The method comprises the following steps: obtaining actual concentration curves of each detection position on a battery pack in the process of charging the battery pack with tracer gas; the actual concentration curve comprises data of concentration change of the tracer gas with time in the gas replacement process; determining air tightness detection results of each detection position according to reference concentration curves of each detection position and the actual concentration curves; the reference concentration curve comprises data of concentration change of the tracer gas with time calculated by a flow field model in advance, and the air tightness detection result is used for characterizing whether the tracer gas leaks at the detection position. The air tightness detection efficiency can be improved by adopting the application.

The invention discloses a method for judging complex characteristics of a crack by using a tracer concentration curve, which specifically comprises the following steps: step 1, in the multi-section fracturing process of a horizontal well, injecting different oil-water two-phase tracers into a reservoir along with fracturing fluid in the multi-section fracturing process, and then sampling to obtain the output concentration of the tracers; step 2, respectively drawing a dimensionless concentration output curve of the water phase tracer agent of each section; 3, setting a judgment standard according to the curve graph drawn in the step 2; 4, analyzing the characteristics of the fracturing section according to the standard specified in the step 3; according to the method, the application function of tracer testing is further expanded, the hydraulic fracturing crack complex feature identification method which is low in cost, easy to operate and high in reliability is provided, and a new technical means is added for fracturing effect evaluation.

The present invention belongs to the technical field of petroleum extraction, and specifically relates to a staged fracturing tracer productivity analysis and testing method, comprising the following steps: S1: calculating a tracer dosage and an injection rate according to staged fracturing data; S2: preparing a tracer solution of a specified concentration and adding the solution to a dosing device; S3: adding the tracer to different layers during the fracturing process through the dosing device; S4: continuously sampling from a sampling port of a flowback fluid pipeline during fracturing fluid flowback; S5: processing the collected samples and then testing the samples to obtain a tracer concentration curve; and S6: comprehensively analyzing and processing the obtained data and curves, comprehensively interpreting and evaluating them, and providing relevant analysis results. The present invention has a simple structure and can simultaneously stir the tracer liquid in a box in both circumferential and vertical directions, thereby promoting mutual contact of the tracer liquid in the box and ensuring uniform mixing, without stratification or precipitation.

A spectral analysis method for thermodynamically analyzing performs multivariate analysis to a plurality of measurement spectra measured under a plurality of measurement parameters, using MCR method that separates a pure spectrum from the plurality of measurement spectra, and calculates a concentration value of each pure spectrum. In this method, an equilibrium model corresponding to an equilibrium state of a sample in which three or more types of chemical species coexist is set, and at least one chemical-equilibrium equation corresponding to the equilibrium model is set. In the MCR method, a concentration curve based on the chemical-equilibrium equation is fitted to the calculated concentration values, an optimal value of a thermodynamic parameter is acquired, a new concentration value is acquired from the chemical-equilibrium equation based on the optimal value, and thus the concentration value is constrained.

The application provides an industrial park ventilation dead zone CO2 quantitative detection method and system, and relates to the technical field of data processing. The industrial park ventilation dead zone CO2 quantitative detection method comprises the following steps: constructing a physical environment and initializing parameters; closing a ventilation opening, injecting a quantitative CO2 gas into an experimental box, and then waiting for the concentration in the experimental box to stabilize; opening a fan to perform constant flow replacement, and simultaneously recording the concentration drop sequence C i (t) of N different measuring point positions by using a plurality of gas concentration sensors of a space monitoring array; performing arithmetic average or weighted average processing on the multi-channel data collected by the plurality of gas concentration sensors to obtain an instantaneous spatial average concentration curve of the experimental box; fitting the instantaneous spatial average concentration curve into a double exponential decay function C(t); inversely calculating a main flow region volume V1, a ventilation dead zone volume V2, and an exchange flow rate Q e between the dead zone and the main flow region; and outputting a dead zone volume proportion v and an exchange efficiency index q to evaluate ventilation efficiency and pollutant retention risk.

The invention provides a tracer agent-based water invasion path identification method, which comprises the following steps of S1, selecting a tracer injection well, injecting a tracer agent into the tracer injection well, and obtaining the tracer agent injection time; s2, multiple wells around the tracer injection well are selected as monitoring wells, and the concentration and time of the tracer appearing in the multiple monitoring wells for the first time are obtained through monitoring; and S3, drawing tracer agent concentration curve graphs of the plurality of monitoring wells according to the concentration and time of the tracer agent appearing in the monitoring wells for the first time, and realizing water invasion path identification between the monitoring wells and the tracer injection wells according to the tracer agent concentration curve graphs. The method is high in precision and accuracy, is not limited by the arrangement of monitoring points, and can obtain comprehensive water invasion path information in a short time.

This invention relates to the field of hydraulic fracturing testing technology, and particularly to a fracture monitoring method, a brine hydraulic fracturing experimental apparatus, system, electronic equipment, and medium. The method includes: adjusting the concentration of the injected brine using a brine concentration control module based on a preset concentration curve, the concentration curve dynamically changing with experimental time or real-time multiphysics feedback data; during the hydraulic fracturing process of the injected brine, acquiring multiphysics data of the target fracture using a multiphysics monitoring module; and calculating the blockage state and salting-out degree of the target fracture using a multiphysics coupling analysis algorithm based on the multiphysics data. This approach solves the technical problem of existing technologies being unable to monitor the multiphysics coupling process under high temperature and high salinity conditions, improving the depth of research and the fidelity of experimental simulations regarding the fracture salting-out blockage mechanism during brine discharge from salt cavern-type compressed air energy storage.

The application discloses a kind of based on concentration curve's resident printing method, device, equipment and storage medium, it is related to ink-jet printing technical field.The method is by determining single nozzle average effective height according to the number of overlapping nozzle;According to single nozzle average effective height, obtain first step height;According to first step height, determine preset concentration curve;After controlling nozzle group according to single scanning image data and preset concentration curve and scanning out ink along main scanning direction, along sub scanning direction moves the distance of first step height, then again according to single scanning image data and preset concentration curve and scans out ink along main scanning direction.The application is by every PASS in resident printing image data is according to preset concentration curve and split into twice printing, equivalent to the printing area corresponding to each PASS, especially nozzle splicing area is carried out feathering processing, reduce the splicing lane superposition problem in resident printing, improve image printing quality.