142results about How to "Effective evaluation" patented technology

The invention discloses a crop disease remote sensing monitoring and early warning system based on time sequence spectral information analysis, and relates to the technical field of agricultural disease and insect pest monitoring. Computer drawing software is utilized to divide a corn planting field in equal proportion, and sensors are deployed to monitor the growth environment change in each grid in real time and generate microenvironment data information; the method comprises the following steps: calculating a microenvironment difference index Xbd according to microenvironment data, identifying a microenvironment difference aggregation area and sending a risk analysis instruction, after receiving the risk analysis instruction, capturing related spectral data information of the microenvironment difference aggregation area by using an unmanned aerial vehicle and a multispectral sensor, and constructing a multispectral fluctuation coefficient Xgp by analyzing related spectral data, and comparing the calculated rust disease risk assessment index Zpg with a preset threshold W in combination with the microenvironment difference index Xbd and the trained risk assessment model, and obtaining corresponding grade early warning according to the rust disease risk degree.

The invention relates to a dangerous rock body risk assessment method based on fracture density analysis. The method comprises the following steps: firstly, acquiring an aerial image of a dangerous rock mass, and preprocessing the aerial image; then, carrying out target detection on the preprocessed dangerous rock mass aerial image by adopting a YOLOv8 neural network to obtain a dangerous rock mass detection frame; on the basis of the dangerous rock mass detection frame, a Fast-SCNN convolutional neural network is adopted to carry out dangerous rock mass crack segmentation and density calculation, and dangerous rock mass crack density is obtained; and finally, determining the risk grade of the dangerous rock mass based on the crack density of the dangerous rock mass in combination with the crack direction and the cross point. That is to say, a dangerous rock mass risk assessment method based on deep learning is provided, the dangerous rock mass crack density, namely the proportion of the effective area of cracks in a dangerous rock mass target frame in the whole frame, is used as a main assessment index, and an intersection point generated due to different crack directions is used as an auxiliary judgment basis. The risk of the dangerous rock mass can be efficiently evaluated, so that the disaster risk of the rock mass is judged.

The invention relates to the field of metal part detection, in particular to a metal part surface quality detection method based on image processing. The method comprises the following steps: acquiring a preprocessed metal part surface grey-scale map; calculating the gradient value of each pixel point, taking the pixel points of which the gradient values are not zero as mark points, clustering and screening all the mark points to obtain a plurality of to-be-analyzed clusters, and taking the minimum bounding rectangles of the to-be-analyzed clusters as to-be-analyzed areas; obtaining the maximum inscribed ellipse of the target area, calculating the optimization degree of the ellipse, and determining a defect area; and iteratively adjusting the edge points of the target area in the preset direction, calculating the between-class variance of the defect area, obtaining the to-be-segmented areas when the between-class variance is maximum, and completing the surface quality detection of the metal part according to the area and the number of the to-be-segmented areas. According to the technical scheme, the precision and efficiency of the quality detection result of the metal part can be improved.

The invention discloses a lithium ore exploration system and method based on data analysis, and relates to the technical field of lithium ore exploration. In the operation process of the system, data from different sources are collected, geological abnormal parameters, lithologic density fluctuation parameters and gravity gradient parameters are obtained, the preprocessed data are analyzed, and a lithium ore exploration result is obtained; the method comprises the following steps: extracting geological features related to mineral resources, carrying out pattern recognition by using a deep learning technology, extracting key features from geological data, obtaining lithologic density Sgeo, rock magnetic parameters Wrock and rock resistivity Rgrad, and generating a three-dimensional geological model of a mining area through an AI algorithm based on the extracted features. The AI algorithm comprises regression analysis and a convolutional neural network (CNN) to process spatial data and generate three-dimensional visualization of a geologic structure, historical mining area distribution data is combined, the system uses a prediction algorithm random forest or a support vector machine (SVM) to predict lithium ore distribution, survey feedback is generated according to a prediction result, and a survey scheme is dynamically adjusted.

The invention provides a method and a system for testing noise of a hybrid electric drive assembly of a hybrid vehicle with a small-capacity battery. The method comprises the following steps: arranging a microphone at a noise testing point; arranging a vibration acceleration sensor at the vibration measuring point; under the pure electric working condition, the vehicle speed starts from 0 km / h, the motor torque is controlled through an accelerator pedal, slow acceleration is conducted at the motor torque of 30 Nm, 50 Nm and 70 Nm respectively till the electric quantity of a battery is consumed to the lower limit, and the hybrid working condition is started; synchronously recording vibration noise of each measuring point and motor rotating speed and torque data; working condition testing is carried out, and acceleration signals of all the vibration measuring points and sound pressure signals of all the noise measuring points under different working conditions are obtained; and analyzing and processing the test data, and confirming the noise source distribution and the noise source resonance frequency. According to the method, the electric drive howling can be effectively tested, analyzed and evaluated through specially set vibration noise test working conditions and data processing parameters of the electric drive assembly in the whole vehicle state of the hybrid power vehicle with the small-capacity battery.

The invention relates to the technical field of operation training evaluation, in particular to a training quality evaluation method and system based on pilot attention distribution. The method comprises the following steps: collecting data required by pilot attention distribution training quality evaluation according to a specific flight mission scene; based on the collected data, calculating a standard attention distribution model of the pilot in a specific flight mission scene, and generating attention distribution and actual attention distribution of the standard attention distribution model; and comparing the attention distribution of the standard attention distribution model with the actual attention distribution, evaluating the training quality of the attention distribution of the pilot in the specific flight mission scene, and forming and displaying an evaluation result. According to the method, the attention distribution mode of the pilot is quantified, the eye movement tracking technology and task-related subjective and objective data are combined, the performance of the pilot in simulator training can be objectively and accurately evaluated, and the scientificity, fairness and safety of flight training are improved.

The invention belongs to the technical field of ocean engineering, and discloses a seabed vibration elbow solid-liquid two-phase flow erosion corrosion coupling analysis method and system. The method comprises the following steps: establishing a three-dimensional fine model of a local bent pipe section; constructing a flow accelerated corrosion model by using a mass transfer equation and a solubility equation to calculate a flow accelerated corrosion rate; an E / CRC particle erosive wear model is introduced to calculate the erosive wear rate of particles to the wall surface of the pipeline; an erosion-corrosion coupling model is constructed based on the electrochemical corrosion secondary current model to simulate the erosion corrosion process of solid-liquid two-phase flow in the vibration pipeline, and an erosion corrosion coupling response rule in the vibration elbow is obtained. Compared with an original analysis method which only considers erosion wear, the erosion corrosion rate calculation precision is improved by 36%, the simulation result and experiment comparison error is reduced to be within 20%, and technical support is provided for accurate analysis of pipeline damage under the erosion corrosion coupling effect.

The invention discloses an ultrasonic nondestructive testing method for residual stress of a titanium alloy pipe, and relates to the technical field of metal detection. Comprising the following steps: carrying out surface residual stress benchmark measurement, selecting an ultrasonic emission frequency, carrying out pretreatment on the surface of the titanium alloy pipe, carrying out multi-mode ultrasonic beam focusing scanning, establishing an ultrasonic speed and stress correlation model, carrying out acoustic anomaly identification on an asymmetric stress area, carrying out residual stress three-dimensional imaging, and correcting stress distribution. According to the ultrasonic nondestructive testing method for the residual stress of the titanium alloy pipe, by combining ultrasonic signal processing, complex stress correlation modeling and acoustic anomaly recognition technologies, the defects of a traditional testing method in the aspects of precision, adaptability and non-destructiveness are overcome. The distribution and concentration condition of the residual stress of the titanium alloy pipe can be efficiently and accurately evaluated, and the reliability and environmental adaptability of a detection result are effectively improved.

The invention provides a prospecting exploration method for ion adsorption type rare earth ore, and belongs to the technical field of geological mineral exploration, and the prospecting exploration method comprises the following steps: delineating an ore-forming mother rock area in a working area according to the existing ore points of the ion adsorption type rare earth ore in the working area and in combination with a geochemical exploration abnormal area; delineating a favorable metallogenic landform area in the working area through a GIS space analysis technology; carrying out superposition analysis on the ore-forming mother rock area and the favorable ore-forming landform area, and determining a favorable ore-forming prospective area in the working area through comparison; collecting a sample in the metallogenic distant view area, and verifying whether mineralization abnormity exists in the metallogenic distant view area or not by using a rare earth ion leaching-titration precipitation method; and in an area with mineralization abnormity in the metallogenic distant view area, exploration and evaluation are carried out by arranging Gannan drills in the metallogenic distant view area, the resource quantity of the metallogenic distant view area is calculated, and the prospecting exploration range of the ion adsorption type rare earth ore is determined. According to the method, the metallogenic prospective area can be rapidly delineated in a large range, the working range is reduced, and the efficiency of exploration work is improved.

The invention discloses a model library-based spaceflight radio frequency signal quality multi-domain evaluation and compensation method, and belongs to the technical field of wireless communication. The implementation method comprises the steps of determining signal system parameters based on various CCSDS standards and a spaceflight protocol system, extracting related parameters of spaceflight standards in a time-frequency domain, generating standard time-frequency domain radio frequency signals, converting the standard time-frequency domain radio frequency signals into a related domain, a modulation domain, an energy domain and a polarization domain, and establishing spaceflight radio frequency signal sub-model libraries of the domains; obtaining a time-frequency domain measured signal through a receiver, integrating time domain information and frequency domain information, and constructing a time-frequency domain sub-evaluation model; constructing a multi-domain comprehensive evaluation model by adopting a parallel data transmission mode and a weight data processing method; calculating the weight of the evaluation result of each domain through an entropy weight method, and obtaining a comprehensive quality evaluation result of the spacecraft radio frequency signal; and based on the distortion coefficient, a robust signal equalization algorithm is adopted to process the signal, the influence of the distortion effect on the signal quality is compensated, and the robustness and the anti-interference capability of signal transmission are improved.

The invention relates to the technical field of medical data processing, and discloses a construction method and application of a systemic lupus erythematosus activity evaluation model. Expression level data of CD177 on the surface of neutrophil, anti-dsDNA antibody titer data, anti-dsDNA antibody concentration data, complement C3 concentration data and complement C4 concentration data are combined, a machine learning algorithm is utilized, and the systemic lupus erythematosus activity evaluation model is constructed. A high-precision systemic lupus erythematosus activity evaluation model is obtained through training, systemic lupus erythematosus activity can be evaluated efficiently, comprehensively and accurately, and an SLE patient is effectively assisted in seeing a doctor in time and making a correct treatment decision.

The invention discloses a simulation experiment device for migration and transformation of pollutants in water and soil media and an evaluation method, and relates to the field of pollutant migration and pollution remediation in environmental media such as natural resources and ecological environments, and the simulation experiment device can independently simulate one scene for simulation and can also perform combined simulation on multiple scenes. The simulation scene is closer to the real condition, the water and soil environment medium condition is simulated more truly, especially, design is carried out for a large number of dominant channels and lenticules existing in the stratum, the simulation effect is more scientific and accurate, trace indexes are introduced according to the pollutant property, a pollutant migration evaluation model is established, and the method has the advantages of being high in practicability and easy to popularize. Therefore, the aim of scientifically and comprehensively evaluating the influence of the pollutants on the environmental medium is achieved, the pollutant migration evaluation method can effectively evaluate the pollutant migration path and the potential pollution area, the pollution range can be more scientifically described, and the evaluation method can provide effective theoretical support for pollution investigation and restoration.

The invention discloses a scenario simulation experiment design method and device, and the method comprises the steps: processing experiment demand information, and obtaining a simulation scenario; processing the simulation scenario by using an experiment design model to obtain a simulation experiment sample and experiment sample space description information; processing the simulation experiment sample and the experiment sample space description information by using an integrated operation model to obtain an experiment simulation result; performing situation monitoring on the simulation scenario by using a situation monitoring model to obtain simulation process data; and comprehensively evaluating the simulation process data and the experiment simulation result to obtain a comprehensive evaluation result. According to the method, the simulation scenario is subjected to experimental design, and the scenario simulation experiment efficiency is improved. The simulation process data and the experiment simulation result are comprehensively evaluated to obtain a comprehensive evaluation result, and rapid and efficient evaluation of the scenario simulation result is realized.

The invention discloses a low-efficiency sea use comprehensive evaluation method based on multi-dimensional analysis, and relates to the technical field of marine resource management and evaluation, and the method comprises the steps: collecting sea use benefit data, and processing the collected data through a superposition analysis method; performing percentage assignment on the processed sea utilization benefit data; constructing a multi-level index system through an analytic hierarchy process, and calculating a target data weight value through a Delphi method; calculating a dimension score according to the assignment and the weight value of the sea utilization benefit data; and calculating a comprehensive score according to the dimension score, and performing grading evaluation on the sea use project. According to the technical scheme, efficient and accurate low-efficiency sea use evaluation can be made for sea use projects, and the method has high application value in the aspects of enhancing sea area space management and control and promoting ocean resource conservation and utilization.

The invention provides a customer service evaluation method and device based on an improved NLP model, a medium and equipment, and relates to the technical field of natural language processing. Through an improved NLP model EUEM based on a Transform architecture, deep learning and natural language processing are performed on historical interaction data, intelligent analysis of interaction quality and emotional tendency is realized, compared with traditional manual evaluation, an evaluation result can be given more quickly and more accurately, and labor cost is reduced; a score calculation formula is synthesized, weight parameters are adjusted, and the weights of the interaction quality and the emotional tendency in evaluation can be balanced according to actual requirements, so that the evaluation result better meets the actual requirements; the dynamic emotion influence scoring mechanism can consider real feelings of clients in different interaction stages and emotion states, so that the evaluation of emotion scores is more flexible and accurate; automatic, efficient and accurate evaluation of customer services is achieved, and therefore the customer satisfaction degree is improved.

The invention discloses a visual data construction and display method and system, electronic equipment and a medium, and relates to the technical field of data processing. The method comprises the steps of obtaining asset data of a target enterprise, and generating an asset hierarchical structure based on the asset data; combining the asset distribution layer, the asset association layer and the asset attribute layer to construct an annular visual interface of the target enterprise; in response to a display request of a user, a plurality of asset evaluation paths with different path widths are generated in the annular visual interface, and the path widths represent asset value proportions corresponding to the asset evaluation paths; obtaining the data distribution density of each asset evaluation path in the annular visual interface, and determining a display scale corresponding to each asset evaluation path according to each data distribution density; and displaying each asset evaluation path on an annular visual interface according to the corresponding display scale and path width. By implementing the technical scheme provided by the invention, the effect of improving the efficiency of constructing and displaying the visual data is achieved.

The invention belongs to the field of geological engineering construction, discloses a TBM (Tunnel Boring Machine) real-time slag monitoring system and a TBM real-time slag monitoring method for advanced geological forecast, solves the problems of lack of real-time performance, continuity and accuracy and low processing efficiency of surrounding rock state analysis in the traditional technology, and provides powerful support for advanced geological forecast in a TBM tunneling process. The method comprises the following steps: continuously acquiring rock slag images to obtain a rock slag acquisition video; cutting the rock slag acquisition video into an image sequence with a fixed time interval, and aligning the timestamp of each rock slag image with the recording time of the TBM tunneling parameters; then the cut rock slag image is preprocessed; then identifying the preprocessed rock slag image to obtain a classification result of the rock slag; and finally, the classification result of the rock slag and TBM tunneling parameters are fused to serve as input, and the surrounding rock grade is calculated through a surrounding rock grade grading model so that the tunneling strategy can be adjusted in real time. The method is suitable for underground engineering construction scenes.

The invention provides a session quality evaluation method, system and device and a medium, and relates to the technical field of data analysis, the method comprises the following steps: determining candidate keywords based on session information of a current session; determining the keyword weight of each candidate keyword based on the undirected graph, selecting a preset number of candidate keywords as keywords based on the values of the keyword weights, and determining the sentiment weight of each keyword according to the sentiment tendency and sentiment intensity corresponding to each keyword under each evaluation dimension; according to the dynamic change condition of the emotional tendency and / or emotional intensity corresponding to each keyword in the session information, dynamically adjusting the emotional weight of each keyword; and in combination with the occurrence frequency, the emotion weight and the keyword weight of each keyword, performing weighted summation on the score of each score dimension to obtain a session quality score of the current session. According to the method, the session quality can be accurately and quickly evaluated.

The invention provides a geothermal resource surface geochemical exploration method and system, and the method comprises the steps: determining a matched net degree according to an exploration area range, collecting gas in soil and soil samples, and determining the gas components and element compositions of the samples through different devices; the influence of the formation reaction is considered, and gas and elements with the migration capacity and anti-interference performance meeting the requirements are selected as geothermal chemical exploration indexes of different formation types; the content of soluble inorganic salt in the stratum and the content of gas in the stratum are measured, and the position where heat storage exists is recognized in combination with the set high-salt and low-gas area; and calculating a cover layer score and a reservoir layer score based on geothermal chemical exploration indexes, further calculating a comprehensive score, and realizing quantitative rating of the thermal reservoir stratum according to the comprehensive score. By adopting the scheme, the problems of insufficient comprehensiveness and insufficient exploration precision in the prior art are solved, the optimization of reliable indexes is realized, a heat storage and cover layer comprehensive evaluation method system is formed based on a heat storage mode of high salt and low gas, and underlying stratum geothermal resources can be effectively tracked.

The invention discloses a method for testing and evaluating the thermal comfort of an automobile using an air-conditioning dummy in an extreme environment. In the testing method, the air-conditioning dummy and a thermocouple installed on a seat are used for testing; thermocouples are respectively arranged on the left and right sides of the hip position of the seat, and thermocouples are respectively arranged on the left and right sides of the backrest 15cm and 30cm away from the seat; the testing method comprises the steps of refrigeration, heating and extreme sudden change environment testing. The evaluation method is applied to the test method and comprises test effectiveness judgment and scoring rules. If the difference between the subjective evaluation score of the driver and the final score of the air conditioner dummy is less than 30%, the test is considered to be successful, and if the overall scores of the driver and the air conditioner dummy exceed 30%, the test needs to be carried out again; according to the scoring rule, the ratio of the air conditioner dummy to the thermocouple to the subjective evaluation is 5: 2: 3. According to the method for testing and evaluating the intelligent air conditioner, the intelligent air conditioner can be tested and evaluated more efficiently, accurately and safely through the air conditioner dummy in the extreme environment.

The invention discloses an optical fiber parameter measurement method and system based on a holmium laser optical fiber, and belongs to the technical field of optical fiber measurement. The method specifically comprises the steps of simulation optimization of a preliminary optical fiber arrangement scheme, precise adjustment of the angle and brightness of the far end of an optical fiber, a detailed scheme of multi-parameter measurement, and an intelligent performance evaluation and overall optimization strategy based on deep learning. Optical fiber arrangement is adjusted through multi-dimensional simulation, and optical fiber far-end setting is optimized in combination with experimental verification, so that basic improvement of optical fiber performance is realized; comprehensively recording optical fiber performance data by using a multi-parameter measurement method, and intelligently evaluating by using a deep learning model to ensure that the optical fiber performance meets a preset standard; for indexes which do not reach the standard in evaluation, the invention further provides an overall optimization scheme, so that comprehensive optimization and performance improvement of the optical fiber system are realized, and the design and manufacturing accuracy and efficiency of the optical fiber system are improved.

The invention relates to a method and device for evaluating the contribution degree of automobile interior trim parts to in-automobile odor, computer equipment, a computer readable storage medium and a computer program product. The method comprises the steps that according to the actual positions of the interior trim parts in a vehicle, all the interior trim parts are arranged in a smell screening simulation cabin, the size of the smell screening simulation cabin is adjusted, and the test temperature, the test humidity and the test duration of the smell screening simulation cabin are set; obtaining a first subjective evaluation average value of the odor intensity of each interior trim part in the odor screening simulation cabin; under the condition that the automobile assembly parts in the cabin are removed, obtaining a first objective evaluation value and a second subjective evaluation average value of the odor intensity of each interior trim part in the odor screening simulation cabin; according to the first subjective evaluation average value, the first objective evaluation numerical value and the second subjective evaluation average value of the odor intensity, the odor contribution degree of each interior trim part is evaluated. By adopting the method, the contribution degree of each interior trim part to the odor in the vehicle can be quickly and accurately determined.

The embodiment of the invention provides a risk control strategy evaluation method and device and computing equipment, and the method comprises the steps: obtaining a plurality of pieces of risk control flow data recorded in a risk control service platform under a target risk control business, and deploying at least one first risk control strategy in the risk control service platform, the risk control flow data comprises risk control basic data, an executed first risk control strategy and a corresponding first strategy execution result; a second risk control strategy is executed in the test environment based on the risk control basic data to obtain a corresponding second strategy execution result, and the second risk control strategy is a fresher risk control strategy corresponding to at least one first risk control strategy; and evaluating the second risk control strategy according to the first strategy execution result and the second strategy execution result of each risk control basic data to obtain a risk control strategy evaluation result. Risk control flow data are reproduced in the test environment, the comprehensiveness, coverage rate and authenticity of the test are ensured, and the risk control strategy is evaluated more efficiently and accurately.

The invention discloses a long text scene-oriented large language model security risk assessment method, system and equipment, belongs to the technical field of large language models, and solves the problem that the security guarantee of a large language model in a long text scene is seriously insufficient and a great gap of a security assessment method exists. The method comprises the steps that when a large model faces long text input, whether the safety performance of the same harmful task is consistent with an evaluation result in a short text scene or not is evaluated for the same harmful task; according to the method, the short text scene security field data is utilized to automatically generate the harmful content with consistent overall semantics and in a long text form, the long text scene security risk assessment data set is constructed, and the potential security risk of the model in the long text scene is identified. An adopted long text evaluation method comprises context learning, a harmful long text generation technology based on reverse length expansion and a thinking chain, and a safety evaluation index subjected to unbiased estimation processing. The method is suitable for evaluating the security risk of the large language model in the long text scene.

The invention belongs to the technical field of drug clinical evaluation, and particularly relates to a drug clinical evaluation method and system based on big data and artificial intelligence, and the method comprises the steps: S1, constructing a default evaluation template; constructing a user-defined index library; s2, constructing an evidence database; s3, establishing a mapping relationship between each drug evaluation index and the business field of each evidence database; s4, on the basis of the default evaluation template and the self-defined index library, establishing an evaluation index system of the medicine according to specific requirements of medicine evaluation; s5, based on the mapping relationship between each medicine evaluation index and the business field of each evidence database, obtaining the corresponding evaluation evidence of the medicine from the evidence database by using each medicine evaluation index of the evaluation index system; and S6, sending the evaluation index system of the to-be-evaluated medicine and the corresponding evaluation evidence to an evaluation end for evaluation, and obtaining a clinical evaluation result of the medicine. According to the method, the evaluation accuracy and efficiency can be improved, and the objectivity and consistency of evaluation results are ensured.

The present invention relates to the technical field of plastic product defect detection, and discloses a plastic product surface defect detection method and system based on machine vision, comprising the following steps: Step 1: Acquire a surface image of a plastic product; the present invention acquires an image of the surface of the plastic product, analyzes the image, calculates the proportion of abnormal areas, makes a preliminary judgment on bubbles on the surface of the plastic product, generates a pre-defective signal or a defective signal, and based on the generated pre-defective signal, specifically analyzes the bubbles on the surface of the plastic product, calculates a defect judgment value, and evaluates the degree of influence on the plastic product based on the defect judgment value, so that when the plastic product is detected, the defects of the bubbles on the surface of the plastic product are efficiently and accurately identified and evaluated based on the image analysis, thereby improving the detection accuracy, and providing real-time feedback on the detection results, thereby timely adjusting the production process or improving the product design, and reducing rework and resource waste caused by defective products.

The invention provides a power load management simulation system, method and device and a medium. The power load management simulation system comprises a digital simulator, hardware and simulation software under a unified specification standard. The hardware comprises a calculation unit, an actual physical device and a simulation interface under a unified specification standard; the simulation software is used for providing a digital model and a simulation environment required by simulation; the calculation unit is used for acquiring the operation data of the actual physical device according to the digital model and processing the data; the digital simulator is used for performing power load management simulation on the processed operation data in combination with a digital model; the simulation system provides hardware and simulation software which are unified in specification and standard, compatibility and stability of the system can be guaranteed, integration complexity is reduced, and real-time performance and accuracy of simulation results are improved. In the simulation method, a simulation link sequence and an implementation method of each link under a standard are provided, so that the correctness and credibility of a power load management simulation result are ensured.

The invention relates to a 5G industrial application quality comprehensive availability evaluation method and apparatus, and a medium. The method comprises the steps of obtaining index values of each 5G industrial application quality comprehensive evaluation index in a current period and a historical period; determining the influence degree of each network quality index in each period according to the service standard maximum value and the service standard minimum value of each network quality index, and determining the weight and the evaluation reference value of each network quality index according to the influence degree; evaluating the network quality value according to the index value, the weight and the evaluation reference value of each network quality index in the current period; evaluating the service quality value according to the index value of each service quality index in the current period; and carrying out comprehensive availability evaluation on the 5G industrial application quality according to the network quality value, the service quality value and the index value of each network wireless index in the current period. According to the method, 5G industrial application quality evaluation and industrial application are combined, and 5G industrial application quality evaluation is effectively carried out.

The invention relates to an electromagnetic performance evaluation method and device of a round wire, computer equipment, a storage medium and a program product. The method comprises the following steps: acquiring basic parameters and grid parameters of a to-be-detected area; the basic parameters comprise a dielectric constant, an initial electromagnetic field parameter, conductivity and magnetic conductivity, and the grid parameters comprise a grid size and an electromagnetic field parameter in each grid; constructing an electromagnetic performance evaluation model of the to-be-tested area according to the basic parameters of the to-be-tested area and the grid parameters of the to-be-tested area; the to-be-detected area comprises a round wire area and a round wire adjacent area; the electromagnetic performance evaluation model of the to-be-tested area is obtained based on the broadband internal impedance of the to-be-tested area and the structure of the round wire area; and analyzing the electromagnetic performance evaluation model, and determining electromagnetic field parameters of the to-be-detected area. By adopting the method, the efficiency of determining the electromagnetic field parameters of the to-be-detected area can be improved.

The invention provides a data processing method and device, a server, a medium and a program product. According to the method, in response to an evaluation request for the property service quality of a to-be-evaluated subject initiated by a target terminal, various index data for evaluating the property service quality of the to-be-evaluated subject is obtained based on multiple channels, and the index data are input into a pre-trained artificial intelligence model; and processing each item of index data based on an artificial intelligence model to obtain a property service quality score for each item of index data of the to-be-evaluated subject, the artificial intelligence model being a model obtained based on historical sample data set training and used for evaluating the property service quality score. And generating a property service evaluation report based on the property service quality score, and sending the property service evaluation report to the target terminal. According to the technical scheme, a property service quality evaluation mode for evaluating the subject matter more efficiently and accurately is provided for a bank, so that the bank business processing efficiency is improved.