23results about How to "Accurate quantitative evaluation" patented technology

The invention relates to a satellite operation risk quantitative evaluation method. The method comprises the following steps: S1, dividing satellite operation consequence states, and formulating satellite operation risk evaluation criteria; s2, constructing a satellite operation risk quantitative evaluation model by using a Bayesian network modeling tool; the satellite operation risk quantitative evaluation model is decomposed according to construction logic of a satellite layer, a function layer, a subsystem layer and a single machine layer, and the state of a top layer node is defined as a satellite operation consequence state; s3, collecting satellite operation data, and calculating a fault probability of a single machine corresponding to a bottom layer node in the satellite operation risk quantitative evaluation model according to the satellite operation data; s4, calculating to obtain a probability value of a satellite operation consequence state by adopting a satellite operation risk quantitative evaluation model; s5, according to a satellite operation risk assessment criterion, calculating a satellite operation risk comprehensive score through the probability value of the satellite operation consequence state; and S6, traversing all satellites of the satellite system, and repeating the steps S1 to S5 to obtain operation risk comprehensive scores of all satellites and performing sorting.

The invention relates to the technical field of signal analysis, in particular to an acute pain assessment method and system based on an EDA signal, and the method comprises the following steps: collecting a skin electrical activity EDA signal of a subject; calculating an individual time-varying sympathetic nerve activity TVSymp curve; the method comprises the following steps: constructing a priori knowledge base containing a standardized pain response sympathetic nerve SpainSymp template; inputting the EDA signal and the individual TVSymp curve into a PCVAE model, fusing features and decoupling the features into pain common features and individual specific features; carrying out pain intensity classification, and reconstructing and generating a standardized SpainSymp curve of which individual specific characteristics are removed; and outputting the pain intensity classification result and the dynamic change trend of the standardized SpainSymp curve in real time. By adopting the method, the pain-induced physiological reaction and individual baseline variation can be effectively decoupled and separated from the mixed EDA signal, the interference of individual difference is avoided, and the method has the characteristics of high accuracy and strong real-time performance.

This invention provides a multimodal fusion-based method for correlation analysis of deep-sea environmental data outside the Yangtze River Estuary, belonging to the field of deep-sea environmental analysis technology. This invention achieves accurate data registration by establishing a spatiotemporal standardization model for multi-source data and employing an adaptive spatiotemporal kriging interpolation algorithm. It utilizes a sparse coding marine signal separation algorithm to construct an overcomplete dictionary to separate mixed signals and extract pure features. Based on an attention mechanism, a feature extraction network is constructed to automatically learn deep feature representations of physical, chemical, and biological parameters. A matrix rank deficiency detection algorithm is used to automatically supplement feature compensation vectors to ensure feature integrity. A cross-scale attention mechanism based on wavelet transform is constructed to fuse multi-scale features. A Shapley value interpretability evaluation system is established to quantify the importance of correlated features. This invention solves the technical problem of inaccurate correlated feature extraction during the fusion of multi-source heterogeneous marine environmental data.

The purpose of the present invention is to provide a column chromatography sample online concentration device, method and application, which are used to overcome the problem of difficulty in analyzing volatile and semi-volatile components in chromatography products. The device comprises a hollow bracket (7), the open end of the hollow bracket (7) is connected to a gas pipeline (3) and a gas source (1), and a plurality of flow regulating valves (6) installed on the hollow bracket (7) are connected to a bronchial line (10); the hollow bracket (7) is connected to a chromatography column (4); and a gas path is formed by the gas source (1), the gas pipeline (3), the hollow bracket (7), the flow regulating valve (6), and the bronchial line (10). In a column chromatography separation experiment, the device continuously and controllably blows the gas flow into a product receiving container through the gas pipeline, so that the mobile phase in the product evaporates rapidly, thereby shortening the product concentration time and reducing the temperature of the collected sample, thereby providing a column chromatography experimental tool for chromatography-mass spectrometry analysis including samples from high-overmature areas.

The invention relates to the technical field of cold-chain logistics, and provides a cold storage site selection method, device and equipment and a storage medium. The method comprises the following steps: constructing a cold storage site selection evaluation model based on a geographic information system, a multi-dimensional evaluation index of cold storage site selection and a spatial constraint condition; performing spatial clustering on target site selection areas obtained based on the cold storage site selection evaluation model to obtain a plurality of target cold storage alternative areas; and determining a target address of the refrigeration house from the target refrigeration house alternative area based on the refrigeration house demand information, a preset refrigeration house decision strategy and a constructed total cost function. According to the cold storage site selection method, device and equipment and the storage medium, modeling can be carried out through a geographic information system, multi-dimensional indexes and spatial constraints, the alternative areas are screened through spatial clustering, the target address of the cold storage is determined from the target cold storage alternative areas in combination with cold storage requirements and the total cost function, and the rationality of cold storage layout is effectively improved.

The application discloses a power equipment state intelligent early warning system and method based on multi-source data fusion, and the early warning system comprises a data acquisition module, which is used for collecting multi-dimensional operation data of power equipment, including equipment operation parameter data, environment sensing data, image detection data and historical operation and maintenance data; a data fusion module, which receives the multi-dimensional operation data for preprocessing, generates a standardized processing data set, and performs fusion processing on the data set. The application belongs to the technical field of power equipment state monitoring and early warning, can cover full-dimensional data of equipment operation, environment, image and operation and maintenance, eliminates the limitation of a single data source, provides complete and reliable data support for subsequent analysis, is efficient and intelligent in fusion processing, extracts core features of multiple types of data through CNN and LSTM, combines genetic and reinforcement learning to optimize fusion weights, greatly improves the relevance and effectiveness of fused data, and avoids heterogeneous data fusion deviation.

The invention relates to a water transmission and distribution dynamic scheduling optimization method, which comprises the following steps that a water transmission and distribution test area is established, the water transmission and distribution test area comprises a test branch pipe, a gas pumping unit and a test user side, and two ends of the test branch pipe are respectively connected with a target water plant and the test user side; performing water hammer disturbance effect analysis on the test branch pipe to obtain a water hammer focus of the test branch pipe; air is pumped into the test branch pipe based on the air pumping unit, and vibration parameters and cutoff parameters of the water hammer focus are obtained through strain vibration monitoring and underwater sound cutoff monitoring; establishing an interference factor modulation unit, and performing interference parameter correction on the vibration parameter and the cutoff parameter based on the interference factor modulation unit to obtain a training parameter; circularly executing the previous step to obtain multiple groups of training data, and constructing and training based on the obtained training data to obtain a filtering matching unit; establishing a water transmission and distribution optimization network in the target pipe network area; and managing and optimizing water supply scheduling in the target pipe network domain based on the water transmission and distribution optimization network.

This invention relates to a method, storage medium, and application for calculating passive earth pressure on finite soil considering the spatial effect of narrow foundation pits. The method includes: acquiring calculation parameters for the narrow foundation pit, determining the spatial effect amplification factor, and obtaining the passive earth pressure of the soil taking into account the spatial effect. The spatial effect amplification factor is calculated based on a fitting formula. The fitting formula is obtained by: establishing a passive earth wedge mechanical model of the finite soil, calculating the passive earth pressure of the finite soil at different depths, and then calculating the passive earth pressure intensity of the finite soil; defining the ratio of the passive earth pressure intensity of the finite soil to the improved Rankine passive earth pressure intensity as the spatial effect amplification factor; plotting the spatial effect amplification factor curves for different foundation pit widths, and establishing the fitting formula for the spatial effect amplification factor. Compared with existing technologies, this invention can more accurately and quantitatively assess the spatial effect, thereby obtaining more precise passive earth pressure. It can be used to optimize the penetration depth of retaining piles in narrow foundation pits and has significant engineering application value.

The invention belongs to the technical field of gas separation membranes, and particularly relates to a molecular simulation-based screening method of a coordination regulation mixed matrix membrane. The method is combined with a molecular simulation technology and is used for quantitatively evaluating the interface compatibility of the mixed matrix membrane and reasonably screening and designing a coordination active additive so as to synergistically optimize the interface structure and the gas separation performance. According to the method disclosed by the invention, a new method for accurate prediction and rational design from a microscopic molecular structure to macroscopic membrane performance is realized, and the method can be used for guiding efficient development of high-performance MMMs.

The application provides a classroom teaching behavior analysis method and system based on multi-modal data fusion, relates to the technical field of data analysis, and comprises the following steps: collecting a multi-modal classroom behavior data set, identifying interactive behavior events for discretization coding, establishing a behavior chain dependency graph model based on an interactive behavior event coding set, identifying a chain dependency path based on each target interactive behavior event, determining classroom behavior data to be fused, generating a fusion window weight according to the chain propagation time of the chain dependency path, weighting and fusing the classroom behavior data to be fused, obtaining classroom behavior fusion data, and obtaining an interactive behavior score index of each target interactive behavior event. The technical problem that the prior art lacks causal time sequence analysis of classroom multi-modal behavior fusion, resulting in low accuracy of quantitative evaluation of classroom teaching quality, is solved. The technical effect of accurate and reliable evaluation of classroom teaching quality is achieved.

The present invention relates to the technical field of material waterproof performance testing, and specifically to a device and method for testing waterproof building materials. The present invention first obtains a connected domain in an image to be tested, and extracts the skeleton pixel points of each connected domain; obtains the humidity value of the unsprayed surface; further obtains the corrected texture possibility of each connected domain based on the distribution characteristics of the skeleton pixel points of each connected domain, combined with the similar characteristics of the overall extension characteristics of the skeleton pixel points between the connected domains; further obtains the corrected gradient value of each pixel point based on the corrected texture possibility, and obtains the water droplet contour, and finally obtains the waterproof performance parameters of the material to be tested in combination with the change in humidity value before and after spraying. The present invention analyzes the distribution of skeleton pixel points in the image and the similar characteristics of the overall extension, corrects the gradient value of the pixel point, accurately identifies the water droplet contour, and accurately and quantitatively evaluates the waterproof performance of the material in combination with the humidity dimension.

The present application belongs to the field of power system demand response and carbon emission monitoring, and discloses an industrial load management method, system, device and medium, which constructs a power-carbon coupling topological model of transformer substation-feeder-pilot area-user level, generates a user dynamic carbon potential image in real time, then establishes an industrial load flexible adjustment potential evaluation model based on carbon efficiency ratio to divide user priority, executes the control instruction in cooperation relying on the local layer-station layer-main station layer three-layer control architecture, and finally collects actual carbon reduction data for iterative optimization by reinforcement learning. The present application improves the carbon perception accuracy and control pertinence of load management, stimulates the internal motivation of users to actively participate in green power consumption and demand response, and realizes the precise quantitative evaluation of carbon reduction effect, thereby effectively supporting the green, efficient and safe operation of the new power system.

The invention relates to the technical field of nondestructive testing of fatigue cracks of large-span steel bridges, in particular to an intelligent scanning robot for fatigue cracks of weld joints of large-span steel bridge decks. The TMR phased array detection module comprises a ferrite magnetic core, an excitation coil and a sensor array probe composed of a plurality of TMR sensors, and the data processing module is used for processing transmitted magnetic flux leakage abnormal signals and identifying the position and size of a weld fatigue crack; the external power supply module provides a working power supply for each module; during detection, the exciting coil excites a uniform magnetic field in a welding seam area, the motion control module controls the walking trolley to continuously scan the whole welding seam area, the sensor array probe senses a magnetic flux leakage abnormal signal of the welding seam area and transmits the signal to the data processing module, and the data processing module completes identification and output of crack parameters. The automatic scanning detection of the fatigue crack of the welding seam is realized, and the length, depth and position information of the crack is accurately recorded.

This invention discloses a method, apparatus, device, and storage medium for credit assessment of campus card deduction transactions, relating to the technical field of campus card systems. The method includes: acquiring deduction transaction information data of the user to be assessed; constructing a feature matrix of independent variables with multiple dimensions, whereby the deduction transaction information data includes transaction behavior data and user information data; mapping the original feature values ​​in the feature matrix of independent variables to corresponding WOE values ​​according to a pre-constructed feature mapping rule, wherein the pre-constructed feature mapping rule is obtained after optimal binning of historical sample data based on the DFS binning algorithm; inputting the mapped WOE values ​​into a pre-trained logistic regression model to calculate the user's risk quantification score; and generating risk control instructions based on the comparison result between the risk quantification score and a preset threshold. This application can solve the risk of overdue payments and bad debts under the campus card deduction model, realizing accurate assessment and automated hierarchical management of user credit risk.

The invention relates to the field of agricultural information technology and plant protection, in particular to a corn disease control method and system fusing CNN and a large model, and the method comprises the steps: carrying out the precise positioning, type recognition and severity quantitative calculation of a disease region of a corn leaf image through the cooperative processing of image segmentation and a classification model; taking the obtained structured evaluation result and context information as prompts, and obtaining real-time and related prevention and treatment knowledge from a professional knowledge base by means of a retrieval enhancement generation technology; and finally, multi-source information is fused by the large language model, and a customized natural language prevention and treatment report is generated. According to the invention, end-to-end intelligentization from disease identification to prevention and control decision making is realized, the limitation of dependence on manual experience in the prior art is effectively overcome, and the precision and efficiency of agricultural plant protection are significantly improved.

The invention provides a microwave reaction cavity heating uniformity analysis method and system, and relates to the technical field of microwave heating. Real-time microwave excitation and cavity wall temperature array signals are synchronously collected, and excitation weights are analyzed by using a pre-built model and a regularization inversion algorithm; on-line and dynamic analysis of the heating state of the microwave reaction cavity in operation is achieved, the hysteresis problem of traditional detection depending on shutdown is solved, random noise can be effectively stripped from an actually measured temperature field through screening of dominant modes, construction of energy space distribution and weighted fusion, and the detection accuracy is improved. The method comprises the following steps: firstly, extracting a characteristic temperature field dominated by the inherent electromagnetic characteristics of a cavity, enhancing the physical mechanism property and anti-interference capability of analysis, then introducing compensation calculation based on the dielectric temperature change characteristics of the material, correcting heat distribution distortion caused by the change of the attributes of the material, and calculating the heat distribution distortion; and the obtained reference temperature field can more truly reflect the heating uniformity capability of the cavity.

The invention provides a thermal barrier coating heat insulation effect test method based on an ITO-AZO thin film thermocouple. The thermal barrier coating heat insulation effect test method comprises the following steps of preparing an insulating layer, preparing a lower-layer thin film thermocouple, preparing a thermal barrier coating, preparing an upper-layer thin film thermocouple and testing the heat insulation effect of the thermal barrier coating. The evaluation of the thermal barrier coating in the flow field environment of 1200 DEG C or below is realized by preparing the double-layer ITO-AZO film thermocouple on the surface of the turbine blade.

This disclosure provides a method and related products for assessing psychological resilience. The method includes: acquiring speech and audio data generated by a target user in response to a multi-topic emotion paradigm task, wherein the multi-topic emotion paradigm task includes multiple pre-set dialogue speech tasks used to assess the target user's psychological resilience. Based on the speech and audio data, a multi-dimensional psychological state representation set for the target user is determined, wherein the multi-dimensional psychological state representation set includes at least one of acoustic features, syntactic features, semantic features, a semantic resilience index, and an affective dimension index based on valence-arousal-dominance. The multi-dimensional psychological state representation set is input into a pre-set psychological resilience regression prediction model, outputting a psychological resilience assessment result for the target user. This disclosure provides a non-invasive, highly ecologically valid, and large-scale screening-applicable digital psychological resilience assessment solution.

The invention relates to an agent quality evaluation method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: determining a plurality of agents from an agent market; for each agent, according to the task execution record of the agent, evaluating the task completion quality of the agent, and determining a task completion quality factor; according to the user preference operation record of the intelligent agent, performing user preference evaluation on the intelligent agent, and determining a user preference factor; according to the task completion quality factor and the user preference factor, performing quantitative evaluation on the intelligent agent to obtain a quantitative evaluation result of the intelligent agent; sorting the plurality of agents based on the quantitative evaluation results of the plurality of agents to obtain an agent quality evaluation result; the intelligent agent quality evaluation result is used for updating the arrangement sequence of the multiple intelligent agents in the intelligent agent market. By adopting the method, the accuracy of intelligent agent quality evaluation can be improved.

The present invention provides a method for detecting local selective corrosion of stainless steel, and belongs to the technical field of material corrosion resistance evaluation. The present invention immerses stainless steel in an electrolyte, selects a suitable electrolyte formula, wherein sulfuric acid and hydrochloric acid are used to dissolve metal grain boundaries, which is beneficial to subsequent electrochemical testing, uses potassium thiocyanate as a depolarizing agent for electrochemical testing, and selects a suitable scanning rate to obtain a corrosion characterization parameter I G , and then combined with the microscopic morphology of stainless steel, multiple stainless steel samples can be distinguished, thereby accurately and quantitatively evaluating the degree of local selective corrosion. The experimental results show that the detection method provided by the present invention can detect the four samples I G The value distinction is large and the morphology is different, which can be used to describe the degree of local selective corrosion.

The invention discloses a method for qualitatively and quantitatively analyzing new psychoactive substances in tobacco tar through in-situ ionization-quadrupole rod time-of-flight mass spectrometry, an electronic tobacco tar sample does not need to be pretreated and can be directly diluted with an internal standard solution, then in-situ ionization-quadrupole rod time-of-flight high-resolution mass spectrometry analysis can be carried out, and only several minutes are needed. The method can obtain comprehensive information of a complex electronic cigarette liquid sample at m / z 50-1000Da to realize qualitative analysis, can make a standard curve through an internal standard method to carry out accurate quantification, and realizes qualitative and quantitative analysis at the same time in an ultra-fast manner. The rapid, accurate and high-sensitivity qualitative and quantitative analysis method is established by taking the new psychoactive substances in the electronic cigarette liquid as research objects, and technical support can be provided for rapid screening of the new psychoactive substances.

The invention discloses an environmental perception evaluation method and system based on a skin electric signal, a terminal and a storage medium, and the method comprises the steps: obtaining panoramic image data and geographic information data, carrying out the environmental feature extraction of the panoramic image data and the geographic information data, and obtaining a target feature, inputting the target features into a structured database for storage to obtain an environment feature database; classifying the environment feature database data to obtain a target street image and a skin electric signal, and inputting the target street image and the skin electric signal into a perception prediction model for training to obtain a trained perception prediction model; and obtaining to-be-detected image data, inputting the to-be-detected image data into the trained perception prediction model for prediction, and obtaining a pressure perception prediction result. According to the method, the perception prediction model is trained according to the target street image and the skin electric signal, the influence of the psychological stress is perceived and predicted, and accurate assessment of the spatial psychological stress is realized.

This invention belongs to the field of heat pipe technology, specifically relating to a method for controlling and online evaluating the content of non-condensable gases in high-temperature heat pipes. The invention includes the following steps: S1, deep cleaning of materials to eliminate non-condensable gases and other impurities dissolved or adsorbed from the end caps, shell, wick, and filling tube; S2, process cleaning to ensure that no new contaminants are introduced during assembly and welding; S3, heat pipe purification and venting to complete the injection of the working fluid and the final purification and venting within the heat pipe; S4, long-term surface barrier to prevent helium and hydrogen from permeating into the heat pipe. This invention addresses the entire process from materials, manufacturing, filling, and testing, achieving proactive and precise control and quantitative evaluation of non-condensable gas content from three dimensions: source control, process elimination, and online evaluation. This improves the long-term reliability and performance consistency of heat pipes under various complex environments.