180 results about "Screening analysis" patented technology

The invention discloses a line planning method and system, and relates to the technical field of electric power line inspection. According to the line planning method, a plurality of feasible inspection paths are generated by obtaining a list of tasks to be inspected and three-dimensional coordinates of an electric tower and an inspection part of the electric tower, combining regional environment data, constructing a semantic knowledge graph and a spatial topological structure chart, determining an optimal path through evaluation, screening and analysis, and transmitting the optimal path to an unmanned aerial vehicle to execute an inspection task. According to the method, the flight state is monitored in real time, the abnormal condition is found in time, and the residual path is dynamically replanned in the inspection process, so that the smooth execution of the inspection task is ensured. The flight state and the environment interference of the unmanned aerial vehicle are monitored in real time, and the dynamic path is replanned according to the actual condition; according to the method, the flexibility and emergency response capacity of the inspection task are remarkably improved, the efficiency and safety of the inspection task are effectively improved by dynamically adjusting the path, and the adaptive capacity of the unmanned aerial vehicle in a complex environment is enhanced.

The invention relates to the technical field of data processing, in particular to a traditional Chinese medicine stir-frying process monitoring method and system. According to the system, various information is collected and processed, so that all-directional collection of data is realized, all functional modules are coordinated through a corresponding algorithm, and the overall performance of the system is greatly improved. The image acquisition module can capture appearance and internal structure changes of the traditional Chinese medicinal materials in real time, the spectrum acquisition module deeply analyzes internal chemical component information of the traditional Chinese medicinal materials, and the sensing data acquisition module monitors various environmental parameters in the stir-frying process by using data acquired by various sensors. According to the method, the obtained multi-dimensional information is further subjected to screening, analysis, model training and other processing, complementation and collaboration of multiple modules are achieved, and comprehensive analysis and monitoring of data in the frying and roasting process of the traditional Chinese medicinal materials are achieved.

The invention discloses a multi-stage equipment energy efficiency optimization control system and method for an efficient machine room, and relates to the technical field of equipment optimizing.The method comprises the steps that environment parameter data and design parameter data of a refrigerating machine room are obtained, an environment correction factor is analyzed, and the cold load rate is dynamically corrected based on the environment correction factor; on the basis of preset delay time, phase-space reconstruction is carried out on the historical corrected cold load rate sequence, the final embedded dimension is analyzed, and a hybrid prediction model is constructed on the basis of the final embedded dimension; matching optimal operation parameters based on physical resonance characteristics of equipment in combination with comprehensive energy efficiency indexes of the machine room; and performing data structure compression on the optimal operation parameters and the comprehensive energy efficiency indexes of the corresponding machine room, performing screening analysis on data points, and updating a parameter library. And invalid data interference is reduced, so that the system can realize self-adaptive optimization in long-term operation, and the data storage and calculation efficiency is improved.

The invention discloses an intelligent interaction method and system based on artificial intelligence, and the method comprises the steps: building an interaction database, collecting the comprehensive data of a sensor in real time, inputting the data into the interaction database, inputting the comprehensive information of a user room into the interaction database, and collecting the historical operation data of a user. Analyzing the historical operation data to obtain an adjustment threshold value corresponding to an operation habit of the user, collecting behaviors of the user after interaction with the smart home, analyzing the behaviors to obtain behavior habit characteristics of the user, analyzing voice characteristics of the user, matching a fuzzy instruction for the voice characteristics to obtain a fuzzy instruction set, and sending the fuzzy instruction set to the smart home; the fuzzy instruction set is screened according to the adjustment threshold value, the influence of the scene feature where the user is located and the behavior habit feature on the fuzzy instructions is analyzed, the priorities of the fuzzy instructions are obtained, and the fuzzy instruction with the highest priority is selected as an interaction instruction, and the method and device have the advantages of improving accuracy and user experience.

The invention provides a case analysis method and device, equipment, a storage medium and a program product, and the method comprises the steps: obtaining to-be-analyzed case information and medical model information, carrying out the case keyword extraction and feature vector extraction of the to-be-analyzed case information, and obtaining a case keyword set and an initial feature vector; determining a screening analysis knowledge base cluster according to the medical model information and the case keyword set, and inputting the initial feature vector and the screening analysis knowledge base cluster into a preset analysis model for case information screening analysis to determine a case analysis result; according to the method, the knowledge base subset suitable for the current case is screened by combining the medical model information and the case keyword set, the analysis precision and the efficiency of the analysis process are improved, higher-level semantic understanding and logical reasoning are carried out through the feature vectors, the accuracy and reliability of case analysis are remarkably improved, and the user experience is improved. And the quality and the credibility of the answers are improved, so that the user experience is improved, and the practicability and the reliability are enhanced.

The invention discloses a tunnel construction water inflow calculation method based on machine learning, and belongs to the field of high-precision prediction of tunnel water inflow disasters. Precise prediction of the tunnel water inflow is one of the focus problems concerned by underground engineering and is directly related to the engineering construction progress, the cavern stability and the safety of constructors. Therefore, a method for calculating the water inflow of the tunnel by constructing the prediction model by integrating multiple machine learning algorithms is provided. The method comprises the steps that a geological condition database is established for a tunnel section with the water inflow needing to be calculated according to drilling data, field investigation data and long-term observation data in the early stage, then screening analysis is conducted on the data in the database, influence factors are selected and preprocessed, iteration updating of a prediction model is conducted through the selected influence factors, and the prediction result is obtained. Finally, a high-precision tunnel water inflow prediction result can be obtained through calculation by inputting on-site investigation data of a tunnel construction area.

The invention relates to the field of high-frequency communication comprehensive detection of a pressure feedback type composite actuator, in particular to a high-frequency communication control detection method for the pressure feedback type composite actuator, which comprises the following steps: acquiring high-frequency communication control real-time data of the pressure feedback type composite actuator; establishing a signal flow dynamic database of the pressure feedback type composite actuator by using the high-frequency communication control real-time data; according to the signal flow dynamic database, multi-stage screening analysis processing is carried out to obtain a high-frequency communication control detection result of the pressure feedback type composite actuator, when any comparison abnormity exists, alarm processing is carried out, meanwhile, the abnormity is rechecked subsequently, and effective safety guarantee is made for the process safety of the stamping process.

The invention provides an influenza prevalence trend prediction and early warning method, which comprises the following steps of S1, collecting multi-source data consisting of monitored epidemic situation data, monitored event data and meteorological data, analyzing influenza epidemiological characteristics, and screening influenza prediction and early warning indexes; s2, analyzing the influenza epidemic situation, and predicting the influenza epidemic trend; and S3, analyzing the flu prevalence signal, and performing early warning on the flu prevalence abnormal signal. The method has the beneficial effects that the prediction and early warning model of the influenza epidemiology trend is established by analyzing the influenza epidemiology characteristics, and reference is provided for the public and related health departments to deal with the influenza in time.

The utility model relates to the technical field of cement fineness detection, and discloses an improved cement fineness negative pressure screen analysis instrument which comprises a cyclone tank, a filter plate is installed in the cyclone tank, a dust collection tank is installed at the lower end of the cyclone tank, a negative pressure mechanism is arranged on the right side of the cyclone tank, and a screen analysis mechanism is arranged on the left side of the cyclone tank. An anti-blocking mechanism is arranged below the filter plate in the cyclone tank; the cement powder is screened through the analysis screen, so that the cement powder with smaller particles passes through the analysis screen and falls into the dust collection tank through the gravity of the cement powder, and the cement powder with extremely small particles is discharged through the filter plate and is discharged into the water box; the negative pressure airflow impacts fan blades in the anti-blocking mechanism, the fan blades drive a brush to rotate through a rotating rod, the brush cleans the surface of a filter plate, cement powder which is small in mass, is sucked by negative pressure and cannot penetrate through the filter plate is prevented from being accumulated on the surface of the filter plate, and therefore blockage of the filter plate is avoided.

A method for screening a key stratum for overburden separation grouting in a coal mine includes: selecting overall analysis objects based on coal mine planning; conducting a primary screening of the analysis objects based on a scope of a subsidence zone; conducting a secondary screening of the analysis objects based on whether there is an old goaf; determining key stratums for screened-in analysis objects, prioritizing the key stratums based on a number of separation spaces and a range of a separation height, setting a safe height based on a diversion fissure zone, and prioritizing numbers of groutable layers based on a potential separation space and a water resistance of a rock stratum; prioritizing the groutable layers based on a fault impact; and comprehensively analyzing grouting priority levels of the key stratums based on results of the three prioritizations, and grouting separation layers of the key stratums in order of priority.

The invention relates to the field of network associated data risk screening analysis, in particular to a network associated data risk screening analysis method based on a neural network, which comprises the following steps: collecting real-time network associated data, and respectively establishing a fixed association feature and a time-sharing association feature of the real-time network associated data; establishing a network association data potential risk analysis model based on a neural network by using the fixed association features and the time-sharing association features; and obtaining a network associated data risk screening analysis result by using the network associated data potential risk analysis model, improving the efficiency and accuracy of risk screening, and processing and analyzing network associated data by using an advanced neural network model. The method comprises the following steps: firstly, carrying out deep preprocessing on original data to ensure the data quality, then extracting and expanding the internal characteristics of the data through the strong learning ability of a neural network, and ensuring the accuracy and reliability of an analysis result.

The invention discloses an intelligent logistics management method and system, and the method comprises the steps: analyzing the influence of environment data on the temperature change in a refrigerator car, analyzing the influence of the temperature change in the refrigerator car on the form of goods, obtaining the vulnerability degree grade of the goods, analyzing the path characteristics between the refrigerator car and a transfer station, and obtaining the vulnerability degree grade of the goods. Analyzing the predicted transportation time of the transportation paths based on the path characteristics, screening the transportation paths based on a set time threshold value, analyzing the jolting characteristics of the transportation paths and the influence of the cargo vulnerability degree on the score of the transportation paths to obtain a comprehensive score of the transportation paths, and selecting a target transportation path according to the comprehensive score, the method comprises the steps that the running time of a refrigerator car in a target transportation path is analyzed in real time, proofreading is conducted on the basis of the running time and predicted time, the influence of the bumping degree of the transportation path and the goods vulnerability degree on cost loss is analyzed to obtain loss cost, and the transportation path is adjusted according to the loss cost. The method has the characteristics of reducing cost and improving accuracy.

The invention discloses an advertisement visual element intelligent matching system and method based on big data, and relates to the technical field of big data advertisement analysis, and the method comprises the steps: obtaining the historical advertisement watching record data of a user, and determining a periodic user characteristic advertisement data set based on the personalized screening analysis of the user; extracting corresponding advertisement texture element features, constructing a texture element feature path of the user characteristic advertisement data of the corresponding period, analyzing the score of the corresponding advertisement data, and determining the optimal user characteristic advertisement data of the period; taking the texture element characteristic path nodes of the periodic optimal user characteristic advertisement data as reference nodes, respectively carrying out clustering processing on the texture element characteristic path nodes corresponding to the periodic user characteristic advertisement data, and analyzing adaptive texture element characteristics of the texture element characteristic path nodes of the optimal user characteristic advertisement data; comprehensively determining an adaptive advertisement data recommendation scoring interval of the corresponding user; according to the invention, accurate user delivery and reasonable element matching of advertisements can be realized.

The invention discloses a dynamic special effect processing method and device, a storage medium and related equipment, which are applied to the technical field of dynamic special effect rendering, and are used for performing plot analysis on an obtained to-be-processed video to obtain a video plot background, an emotional tone in the plot and a key plot node, and performing dynamic special effect processing according to the video plot background and the emotional tone in the plot. The method comprises the following steps: respectively performing emotion reasoning and emotion trajectory construction to obtain an emotion label and an emotion trajectory of a role, identifying a plot turning point through the emotion trajectory of the role and a key plot node, and obtaining a bullet screen analysis result corresponding to a video to be processed according to the emotion label, the obtained emotion intensity, the emotion association role, the plot turning point and the to-be-processed video. And determining a triggering opportunity, a triggering emotion and a triggering special effect, and performing emotion special effect rendering through the triggering opportunity, the triggering emotion and the triggering special effect.

The utility model relates to the technical field of cement negative pressure screen analysis instruments, and discloses a full-automatic cement negative pressure screen analysis instrument which comprises a machine body, a fixing plate is fixedly connected to the top of the inner wall of the machine body, a first stepping motor is fixedly connected to the center of the bottom of the fixing plate, and the output end of the first stepping motor is fixedly connected with a lead screw. A lifting rod is in threaded connection with the outer ring of the lead screw, a lifting frame is fixedly connected to the top of the lifting rod, a screening tool is arranged on one side of the inner ring of the lifting frame, a screen is arranged at the bottom of the inner wall of the screening tool, and a linear bearing penetrates through and is fixedly connected to the center of the bottom of the fixing plate. The left side of the bottom of the fixing plate is fixedly connected with a second stepping motor. According to the vibrating screen, the bearing frame is driven by the first stepping motor, the lifting frame, the screen tool, the screen cover, the vibrator and the second stepping motor to rotate, materials are weighed, the first stepping motor is started to work, the lead screw is driven to rotate, and the screen tool is driven to move downwards.

The invention relates to a screening device and method for recycled concrete sand making in the technical field of sand making screening, the screening device comprises a vibration screening chamber, a subdivision chamber, a material detection mechanism and a screening intelligent controller, and an inner cavity of the vibration screening chamber is rotationally connected with multiple layers of inclined screening nets; the subdivision chamber is arranged between the output end of the screening net and the separated material outlet; the material detection mechanism comprises a screen detection mechanism matched with the screening net and a receiving plate detection mechanism matched with the material receiving plate, and the screen detection mechanism comprises an adjusting plate connected with the screening net, a telescopic piece and an adjusting shaft abutting against the adjusting plate; the intelligent screening controller comprises a screening analysis module, a screen regulation and control module and a subdivision module, by the adoption of the structure, the amount and the specification of materials entering the screen can be judged, the materials are controlled to enter the smashing assembly to be smashed and screened again according to requirements, and the amount and the specification of the materials screened out through the equipment can meet the engineering requirements.

The invention discloses an intelligent furniture design production method and system, and relates to the technical field of furniture production, and the method comprises the steps: obtaining the design demand data of a customer, carrying out the semantic analysis of the design demand data based on a semantic analysis model, extracting the design elements of the design demand data of the customer, and importing a basic furniture model, setting an initial size of the basic furniture model according to the spatial data; dividing the plurality of design elements into a plurality of design element groups according to a design direction; adjusting the initial size of the basic furniture model based on the plurality of design element groups to generate a plurality of initial design schemes; and extracting process parameters of the initial design scheme, screening and analyzing based on production feasibility, and outputting a furniture design production scheme meeting the production feasibility. Design elements of customer design demand data are extracted through semantic analysis, production feasibility analysis is carried out in combination with furniture materials, efficient and full-automatic intelligent furniture customization operation is achieved, and the intelligence of furniture design production is improved.

The invention provides a noise processing method and system based on artificial intelligence, and relates to the technical field of noise processing. The method comprises the following steps: acquiring historical voice noise processing data, and performing noise feature extraction based on an environment background to form background noise feature data; according to the background noise feature data, performing denoising processing on the to-be-processed voice information to form initial denoised voice information; and noise screening analysis based on smoothness and semantics is carried out on the initial de-noised voice information, and target voice information is extracted. According to the method, the feature data of the environmental background noise is established by using the big data, so that the noise in the recorded voice can be identified and most of the noise can be screened out more effectively, and clear target voice information can be obtained.

The invention relates to the technical field of molecular docking, in particular to an automatic molecular docking and screening analysis method which comprises the following steps: S1, aligning protein structures; s2, processing the receptor protein file; s3, carrying out batch molecular docking; s4, calculating the distance between the substrate and the catalytic site; s5, performing combined screening on the combination energy and the spatial relationship; and S6, summarizing and visualizing results. According to the method, a large-scale molecular docking task can be efficiently and accurately completed, and powerful technical support is provided for the fields of drug design, enzymology research and the like.

The invention belongs to the technical field of intelligent monitoring of power distribution cabinets, and particularly relates to an intelligent monitoring system and method for a power distribution cabinet. According to the method, the historical operation data of the power distribution cabinet is subjected to orderliness analysis and association screening, a fault database is constructed, and the real-time operation state of the power distribution cabinet is accurately monitored and predicted, firstly, fault parameters and normal parameters can be accurately distinguished through classification processing of the historical operation data, and the fault parameters are accurately determined; the method comprises the following steps: firstly, determining the fault type according to the regularity of fault parameters, providing a basis for subsequent correlation analysis and prediction, secondly, performing correlation screening analysis on historical operation data under conventional faults, determining parameters closely related to the faults, constructing a fault database, improving the accuracy and efficiency of fault identification, and finally, performing fault diagnosis on the fault data. Through real-time monitoring and prediction analysis, the abnormal operation state of the power distribution cabinet can be found in time, the abnormal level is determined according to the abnormal difference, an alarm mechanism is triggered, and safe and stable operation of the power distribution cabinet is guaranteed.

The invention belongs to the field of bidding and tendering, relates to a data analysis technology, is used for solving the problem that various requirements of enterprise users cannot be met due to the fact that bidding project recommendation is provided for the enterprise users according to a single standard or basis in the prior art, and particularly relates to an enterprise competition management method and system based on bidding and tendering big data. The enterprise management platform is in communication connection with a document screening module, a user analysis module, a recommendation output module and a bidding database; the document screening module is used for performing preliminary screening analysis on the bid invitation documents: marking enterprise users performing bid invitation analysis as analysis objects, and extracting preliminary screening items from the bid invitation database through the analysis objects; according to different target tendency and operation tendency combinations selected by the enterprise user, secondary screening is carried out on the primarily screened items, the matching degree of the recommended items obtained through secondary screening and the requirements of the enterprise user is high, and therefore the auditing efficiency of the enterprise user and the selection probability of the recommendation result are improved.

The invention discloses an automatic information acquisition system and method for egg product parameters, and relates to the technical field of livestock and poultry breeding, and the method comprises the steps: obtaining a first screening analysis parameter and a second screening analysis parameter based on the egg product parameters, and obtaining a first screening judgment value and an internal stagger value; carrying out screening and acquisition processing to obtain a judgment value of the internal parameter; analyzing a sampling information acquisition result, and judging whether secondary sampling investigation is carried out or not; the method is used for solving the problems that in an existing egg product parameter automatic information acquisition method, in the aspect of egg product parameter sampling investigation, a method for judging the validity of data obtained through sampling is lacked, and consequently when the egg cardinal number is large and parameters corresponding to eggs obtained through sampling investigation cannot effectively reflect the overall egg product parameters, the whole egg product parameters cannot be effectively reflected. The problems that information collection is one-sided and data is not accurate enough are solved.

The invention discloses a combined drive control method and system for a functional concrete processing cycle, and relates to the technical field of intelligent control, and the method comprises the steps: carrying out the multi-dimensional feature collection of raw materials of concrete, obtaining the feature information of the raw materials, and carrying out the screening analysis of a combined drive control database through taking the feature information as a constraint, thereby obtaining a control reference database; dividing a control reference database; analyzing functional requirements of the concrete, and determining a functional evaluation plan; performing optimization traversal on the reference library without the additives to obtain a first optimal control strategy, and performing optimization traversal on the reference library with the additives to obtain a second optimal control strategy; and comparing the first optimal control strategy with the second optimal control strategy to obtain a target control strategy, and performing combined drive control on the concrete. The technical problem that the processing control strategy cannot be intelligently matched according to the characteristics of the concrete raw materials in the prior art is solved, and the technical effects of accurate matching and functional control optimization of the concrete processing strategy are achieved.

The invention discloses a dynamic security analysis and optimization method based on a network communication system, and relates to the technical field of dynamic security analysis, and the method comprises the steps: S10, obtaining log data of routers corresponding to all marked addresses; s20, predicting the real-time security index of the router corresponding to each marked address; s30, generating a network topology structure diagram of the target data packet; s40, obtaining a security index change coefficient of a next-level network topology node; s50, determining a screening condition of each network topology node in the network topology structure diagram of the target data packet, and obtaining a screening analysis set of each network topology node; s60, screening out a target transmission primary link and a target transmission secondary link of the target data packet; and S70, dynamically adjusting the target transmission primary link based on the target transmission secondary link. According to the invention, the dynamic selection of the router is realized based on the screening analysis set, and the transmission quality and transmission efficiency of the target data packet in the network can be ensured.

The utility model discloses a kind of mineral screen analysis devices of automatically judging screening solution turbidity, including screening container, wet screening mechanism and industrial computer, the wet screening mechanism includes electric telescopic support, vibrating support and screen, the electric telescopic support is connected with vibrating support, vibrating motor is installed on the vibrating support, screen is equipped below the vibrating support;The screening container is transparent container, screening container support is equipped outside the screening container, camera is installed outside the screening container, reference plate is installed in the side corresponding to camera in the screening container.The utility model replaces artificial ore grinding screening, equipment state adjustment and result record by automation control, reduces artificial intervention link, avoids the error caused by operation fatigue or experience difference;Systematization controls vibration frequency, screening parameters such as duration, eliminates the result fluctuation caused by random nature in traditional wet screening due to artificial adjustment, ensures that data comparability under different batches, different operators.

The invention discloses a resume preliminary screening method and system fusing AI semantic analysis, and relates to the technical field related to data processing, and the method comprises the steps: receiving a resume screening item of a target post, and dividing the resume screening item into a semantic clear item and a fuzzy skill item; constructing a deblurring adaptation template library; resume reconstruction is carried out according to a preset resume template; performing primary screening on the reconstructed resume set; and carrying out secondary screening on the first resume set, carrying out context-aware core coefficient analysis on the second resume set, carrying out third screening, analyzing the adaptation degree of each resume in the third resume set and a target post, sorting the resumes, and recommending the resumes to a target HR terminal. The technical problems of low resume screening precision and efficiency caused by insufficient evaluation of fuzzy skill items in resumes, single screening dimension and lack of context correlation analysis in the prior art are solved, and the technical effects of realizing automatic, multi-level and high-precision resume preliminary screening and remarkably improving the resume screening efficiency and post adaptation accuracy are achieved.

The invention discloses a precision marketing label screening method and system based on high-dimensional interactive screening. The method comprises the following steps: S1, a user determines a core index variable y for measuring a service effect; s2, a user determines a to-be-screened label range and preliminarily selects a proper customer group to obtain a sample set x; s3, constructing a hierarchical screening model; and S4, the user selects a screening hierarchical mode: weak hierarchical structure screening and strong hierarchical structure screening. The system comprises an interactive display module, a data storage module, a screening analysis module and a feedback optimization module. According to the method, reference can be provided for bank marketing personnel when the marketing objects are determined, the situation that labels with information values are omitted when the labels are selected from numerous labels is avoided, and hidden interaction information among the labels can be explored.

The invention discloses a data security risk monitoring method and device, electronic equipment and a storage medium, and the method comprises the steps: executing an RPA engine, and obtaining a suspicious data set of a target network source according to a preset task arrangement process; sequentially screening and analyzing the suspicious data set by adopting a constructed early warning rule engine and a security risk identification model, and identifying risk data; and processing the risk data. By using the method disclosed by the invention, the whole-process intelligent closed loop from data acquisition to risk disposal can be realized, the labor cost of data acquisition is saved, and the data monitoring efficiency and the risk identification accuracy are improved.

The embodiment of the present application provides a screening method and a screening system, the screening method comprises the following steps: obtaining historical flow data of a plurality of target objects from a storage system, and extracting historical values of target variables of the plurality of target objects from the historical flow data; generating a predicted selection probability corresponding to the target objects according to the historical values of the target variables; inputting the predicted selection probability and the historical values of the target variables into an established expectation value model, performing screening analysis on the target objects, and generating expected values of the target variables of the plurality of target objects; and screening the target objects whose expected values of the target variables are greater than a preset threshold value, and storing the corresponding identification information of the target objects into a database. According to the predicted selection probability of the target objects, the expected values of the target variables are obtained by using the expectation value model, and the target objects are screened according to the expected values of the target variables, so that the required target objects can be quickly and accurately screened, and the screening quality is better.

The application provides an analysis method, device and equipment based on single-cell transcriptome sequencing data, which comprises the following steps: performing quality control, downstream analysis and visual display on single-cell transcriptome sequencing expression quantitative data, performing cell filtering by using Grubbs test method to obtain effective single-cell transcriptome sequencing quantitative data, performing initialization clustering analysis on the data to obtain single-cell subgroup classification results; performing screening on the single-cell subgroup classification results to obtain target single-cell subgroups, and performing re-clustering analysis to obtain single-cell sub-subgroup classification results; performing significant difference gene screening analysis on the single-cell transcriptome sequencing quantitative data between single-cell subgroups; and performing regression analysis based on characteristic genes of cell cycles to predict cell division periods corresponding to different cell types. The application effectively solves the technical complex problems of existing single-cell transcriptome sequencing quantitative data analysis, makes data analysis more simple and reliable, and reduces the difficulty of data analysis.