235 results about "Research data" patented technology

The invention relates to the technical field of medical data analysis and processing, in particular to a medical scientific research auxiliary method and system based on a large model, a terminal and a medium, and the method comprises the steps: extracting theme meanings based on a natural language processing technology, sending retrieval requests to a plurality of medical literature databases based on the theme meanings, and returning retrieved related literatures; performing feature extraction on the related literatures, classifying the related literatures, and generating a literature review; determining an experiment type based on related literatures and medical knowledge maps in combination with the research problem and an expected target, determining an experiment process and an input demand, obtaining a precise search condition in combination with the input demand, and obtaining corresponding research data based on the precise search condition; a corresponding analysis method is selected for analysis processing, and an analysis result is obtained; and generating a preliminary framework of the thesis based on research data, analysis results and literature review in combination with a standard structure template. The efficiency and quality of medical scientific research are effectively improved, the cost is reduced, and the intelligence and systematicness of scientific research are enhanced.

The invention discloses a project performance evaluation and risk early warning method for multi-source heterogeneous scientific research data, and relates to the technical field of scientific research project management, and the method comprises the steps: collecting the multi-source heterogeneous scientific research data, cleaning, converting, filling missing values, and storing in a unified format; extracting performance and risk features, and fusing to obtain a fused feature set; combining an analytic hierarchy process, an entropy weight method and the like to construct a dynamic weight performance evaluation model; constructing a multi-modal risk early warning model by adopting multiple algorithms and optimizing a threshold value; collecting data in real time to update a feature set, and dynamically adjusting the model; and visually outputting a result, generating an improvement suggestion, and forming closed-loop feedback. According to the method, the multi-source data processing efficiency and evaluation accuracy are improved, the risk early warning timeliness and adaptability are enhanced, a management closed loop is formed, and the problems of difficult data integration, evaluation lagging, insufficient early warning and the like of a traditional method are solved.

The invention relates to the technical field of artificial intelligence, and discloses an artificial intelligence-based spleen and liver trauma model establishment method, which comprises the following steps of: S01, acquiring target data; step S02, obtaining research data; s03, inputting research data into the improved U-Net network model, and performing organ segmentation to obtain a target organ contour; s04, performing three-dimensional reconstruction to obtain a trauma model corresponding to the target organ, and performing hemodynamic analogue simulation; through the step S03, construction of the improved U-Net network model is facilitated, compared with a traditional U-Net network model, the improved U-Net network model can significantly improve the accuracy and robustness of organ segmentation, the effectiveness and accuracy of the spleen and liver contour are enhanced, and an effective foundation is laid for subsequent three-dimensional modeling based on the spleen and liver contour.

The invention discloses an ion adsorption type rare earth ore prospecting method based on a multi-element composite mineralization mode, and belongs to the technical field of rare earth ore geological exploration. The method comprises the following steps: firstly, collecting the existing exploration and research data of the known granite weathered crust type rare earth deposit; analyzing the ore-forming basic elements of the known granite weathering crust ion adsorption type rare earth ore deposit; then field geological survey and sample collection are carried out on the known granite weathered crust ion adsorption type rare earth ore deposit; determining each metallogenic mode element by utilizing analysis test data and field survey data; analyzing the formation cause of the ore deposit, establishing a prospecting mark, and constructing a multi-component composite mineralization mode of the granite weathering crust type rare earth ore deposit. And finally, prospecting target area prediction is carried out. For the known high-altitude granite weathering crust ion adsorption type rare earth deposit, multiple exploration technologies are organically fused, the special environment of the high-altitude area is optimized, a multi-element composite mineralization mode is constructed, and brand-new theoretical guidance and technical means are provided for prospecting of ion adsorption type rare earth ore in the high-altitude area.

The invention relates to a total primary productivity high-precision downscaling method based on a multi-scale attention mechanism, and belongs to the technical field of remote sensing. According to the method, the technical problems of fuzzy details, fuzzy boundaries and insufficient fitting precision of the existing GPP downscaling technology in a complex terrain region are solved. According to the technical scheme, an Enhanced Multi-scale Residual Attention Network (EMSRAN) model is constructed, multi-source remote sensing data including a medium-resolution imaging spectrometer (MODIS) GPP product and a terrestrial satellite auxiliary factor are integrated, data preprocessing, sample generation and model training and optimization are carried out, and a high-resolution GPP image is output. Technical effects include significant improvement of spatial detail reduction ability, enhancement of heterogeneous ecosystem adaptability, enhancement of boundary definition expression, and improvement of carbon cycle research data reliability.

The invention belongs to the technical field of computer software, and particularly relates to a data lake and warehouse management deployment method applied to a domestic operating system, which comprises the following steps: establishing a heterogeneous server cluster, deploying various domestic operating systems in the server cluster, and completing configuration of a network architecture and a basic software environment; the method comprises the following steps: carrying out localization adaptation on a software component source code, synchronously modifying package management logic of a self-research data lake and warehouse management platform, and further implementing intelligent compiling to generate a program package for different instruction set architecture and domestic operating system combination; automatically generating and executing a deployment script by utilizing a self-developed data lake and warehouse management platform to complete installation and configuration of each software component on a target node; and after deployment of each software component is completed, systematic deep tuning and component-level accurate tuning are automatically performed on the deployed system and each software component, and automatic verification is executed. The invention provides an efficient, stable, safe and controllable data lake and warehouse integrated solution for users, wherein the data lake and warehouse integrated solution can be used immediately after being opened.

The invention belongs to the technical field of ecological restoration evaluation, and provides a geological ecological restoration evaluation method and system for geological disaster prevention and control, electronic equipment and a storage medium. The method comprises the steps of research data acquisition, geological disaster type setting, initial evaluation, data preprocessing, model construction and training, risk determination before restoration, information acquisition after restoration, geological disaster risk prediction and geological ecological restoration evaluation. According to the method, the model is trained by using the remote sensing image, the sound wave data and the initial evaluation data, the evaluation result is predicted through the remote sensing image and the sound wave data, the risk evaluation difficulty and time are reduced, in addition, remote sensing and sound waves are combined, meanwhile, surface features and structural features are extracted, and the prediction effect of the model is optimized; through a multi-mode proximity perception model, the perception capability of the surrounding environment is improved, and the prediction precision of a single block is improved; and through the repair effect evaluation rule, a repair effect evaluation mechanism is optimized.

The invention provides a teaching document anti-copy protection method and system based on OCR interference resistance, and belongs to the technical field of information security and digital copyright protection. According to the method, anti-OCR font processing is applied to document characters, invisible disturbance symbols are inserted between characters or paragraphs, watermark information is embedded in document typesetting or font strokes, and finally a standard PDF or DOCX file is compiled. Watermark information is embedded through stroke thickness change, paragraph row spacing indentation perturbation and other modes. The system comprises a font disturbance module, a character disturbance module, a watermark embedding module, a compiling output module and a verification module. According to the method, the human eyes can normally read the document, but messy codes or disorder can occur when the OCR tool extracts the document, and the document cannot be directly reused; meanwhile, watermark information cannot be stripped, so that leakage tracking is facilitated; and the output file keeps a standard format and is compatible with the existing office teaching process. The method is suitable for anti-copying protection of teaching documents, scientific research data, test papers, contract files and the like.

The invention relates to an intelligent hospital management system based on clinical scientific research integration, and the system comprises a clinical scientific research integration platform which is provided with a special disease database data service module which is used for integrating patient clinical data with a patient as a center; the special disease database data service module comprises a special disease scientific research data center which is used for storing high-quality multi-dimensional structured patient data processed by an artificial intelligence technology; the regional decision application module is used for collecting multi-hospital-area data and carrying out hospital diagnosis and treatment and multi-dimensional analysis of medication data; the regional collaborative application module is used for realizing medical resource sharing of multiple hospital areas; and the regional multi-center-line image integration module is used for acquiring image system data of a plurality of courtyards and realizing sharing and mutual recognition. According to the invention, multi-center medical data integration and scientific research collaboration are realized, and the collaborative work and collaborative diagnosis and treatment efficiency is improved.

The invention discloses a disaster prevention and control refined division method based on map data. The method comprises the following steps: step S10, subdividing an evaluation unit based on map data, landform data and administrative division; step S20, comprehensively selecting prevention and treatment alternative areas through risk assessment, vulnerability assessment and disaster assessment; step S30, constructing an index system from three dimensions of dangerousness, exposure and vulnerability; s40, performing index quantification based on the map data and the investigation and survey data, and calculating the weight of each index in combination with the information entropy; step S50, calculating a comprehensive index of each evaluation unit by adopting a Jenks natural fracture method; and step S60, finely delimiting disaster prevention and control key areas in combination with actual management department experience and comprehensive indexes. The method is convenient for later-period management, avoids a large amount of repeated work, and has relatively high objectivity and reference value.

An early screening system for chronic obstructive pulmonary disease based on blood routine test data. It belongs to the technical field of digital medical treatment, and specifically relates to the technical field of intelligent early screening of chronic obstructive pulmonary disease. It solves the technical problem that the generalization ability of a COPD prediction model is limited due to differences between different research data sets. The system comprises a data collection module that collects blood routine test data of a plurality of chronic obstructive pulmonary disease patients and blood routine test data of a plurality of normal personnel; a data preprocessing module that performs standardization processing on the blood routine test data to obtain a standardized data set; a screening model training module that trains N classification models using the standardized data set and calculates the prediction accuracy of each classification model; and a screening model application module that obtains the fusion weight of each model by using a normalization processing method based on the prediction accuracy of each classification model, fuses the risk scores predicted by the multiple models, and obtains a final screening result.

The invention discloses a tumor medical record time axis generation method based on multi-modal recognition and dynamic cue words, which thoroughly solves the problem of disordered stage division of a traditional method by introducing a dynamic cue word mechanism into an operation discrimination node. Through a multi-mode OCR + NLP fusion strategy, the accuracy of medical record information extraction is greatly improved; the medical compliance of the time axis is ensured through time sequence verification and field completion driven by the knowledge graph; and through front-end mind map or medical history outline visualization, the complex medical record can be clearly displayed. Practice shows that compared with manual arrangement, the time consumption of sequential output of the complete medical record is reduced by more than 90%, the item missing rate is reduced by more than 80%, and the method can be widely applied to scenes such as clinical decision support, follow-up visit management, scientific research data integration and medical insurance quality control.

The invention discloses a teacher teaching ability evaluation method based on big data analysis, and relates to the technical field of monitoring analysis, and the method comprises the steps: data collection: collecting teaching data and scientific research data of a teacher through a big data platform; data processing: analyzing and processing the teaching data and scientific research data corresponding to the teacher, evaluating the teaching ability of the teacher based on an analysis and processing result, and determining a comprehensive evaluation coefficient corresponding to the teacher based on an evaluation result; early warning management: monitoring the teachers based on the comprehensive evaluation coefficients corresponding to the teachers, and performing early warning on the teachers based on monitoring results; and feedback estimation: estimating the teaching quality of the teacher according to the comprehensive evaluation coefficient corresponding to the teacher. The method has the effect of improving the teaching ability evaluation efficiency of teachers.

The invention relates to the field of multi-currency quotation, in particular to a multi-currency quotation calculation method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining an original data set related to quotation; acquiring instant and historical exchange rate data of the transaction currency to form a market data set; calculating a cost currency estimated value of each cost composition item and summarizing to obtain a direct cost total amount; analyzing the research data to obtain a risk level, and providing a corresponding insurance cover scheme; calculating a cash flow estimated value under the influence of the exchange rate by combining the cash flow, the historical exchange rate and the insurance cover scheme, generating and sorting a contract quotation amount sample set according to a preset gross profit rate, determining the minimum contract quotation by combining the confidence coefficient, and obtaining the final contract quotation amount according to the premium parameter. According to the method for calculating the multi-currency quotation, the problems that the traditional quotation exchange rate has no standardized calculation logic and the decision is lack of quantitative support are effectively solved, accurate cost accounting and risk management and control are realized, and enterprise profit and market competitiveness are balanced.

The embodiment of the invention discloses a data processing method and device, electronic equipment, a storage medium and a product. The method comprises the following steps: inputting attribute information corresponding to scientific research data into a pre-trained watermark generation model to obtain watermark information corresponding to the scientific research data; wherein the watermark generation model comprises generation of a resistance network model; embedding the watermark information into the scientific research data to obtain encrypted data; and performing data processing on the encrypted data based on a data sharing request sent by a data sharing party. According to the technical scheme of the embodiment of the invention, the imperceptibility and robustness of the watermark can be improved, the reverse engineering attack of the model can be resisted, and the data security of the scientific research data during sharing is ensured.

The invention relates to the technical field of river ecological toughness evaluation, and discloses a river ecological toughness evaluation method based on a water quality target and flood season pollution control. The method comprises: setting a water quality target of a target water area; collecting ecological research data of the target water area in the flood season, and dividing the ecological research data into historical research data and current research data according to time; performing statistical analysis on the historical research data to obtain first feature data of each flood season; training a neural network model based on all the first feature data, and generating a prediction model for estimating the water quality recovery time; and performing statistical analysis on the current research data to obtain second feature data, inputting the second feature data into the prediction model, obtaining estimated time for recovering the current initial water quality to a water quality target, and generating a river ecological toughness value according to the estimated time. The method can accurately predict the water quality recovery time under flood season pollution control, scientifically quantify the river ecological toughness, and improve the efficiency of river ecological toughness evaluation.

The invention discloses an automatic driving vehicle accident cause analysis method. The method comprises the steps of obtaining a data set of an automatic driving vehicle accident report; pre-processing the data set, wherein the pre-processing comprises abnormal value cleaning, error data correction and missing data repair; constructing an explanation variable system of an automatic driving vehicle accident, and carrying out statistical description on accident characteristics; an accident cause analysis model is provided by integrating existing automatic driving vehicle accident research data and conclusions based on a random parameter Logit method for solving a heterogeneity problem; based on priori knowledge and an analysis result, designing a random parametric variable, and constructing an RPL model: sampling a probability density function for multiple times by adopting a Monte Carlo method, and taking a simulated probability mean value as an integral approximate solution; and the analysis of the variable random parameter effect in the automatic driving vehicle accident is realized through the RPL model. According to the invention, the cause explanation of the heterogeneity of the important characteristics and influence factors of the accident of the automatic driving vehicle is realized.

The embodiment of the invention provides an e-commerce product market research method and system based on artificial intelligence, and the method comprises the steps: S1, analyzing user input information, converting the information into structured data, and decomposing the structured data into a plurality of subtasks; s2, analyzing the requirements of the sub-tasks and the dependency relationship between the sub-tasks by using the large language model, and generating an investigation strategy; s3, calling the MCP tool according to the investigation strategy to generate preliminary investigation data; s4, evaluating the preliminary investigation and survey data, judging whether each subtask reaches an expected investigation and survey requirement or not, and obtaining an evaluation result; s5, judging whether the preliminary investigation data is sufficient or not according to the evaluation result; and S6, calling a special statistical MCP tool according to the research result, and generating a research report. According to the method, data sufficiency is guaranteed through dynamic evaluation and supplementary investigation through a large language model and an MCP tool, an investigation report is finally generated, the whole investigation process is intelligent, and efficiency and conclusion credibility are improved.

The invention provides an electroencephalogram synchronous acquisition system compatible with nuclear magnetic resonance. The problem of interference of traditional equipment in a strong magnetic field environment is solved through innovative material selection and structural design. According to the system, a platinum-iridium alloy multi-contact implantable electrode probe is adopted and is matched with a nuclear magnetism compatible electrode wire formed by a silver-plated copper wire core body and a silver-plated nylon shielding layer, so that indoor and outdoor long-distance signal transmission of MRI (Magnetic Resonance Imaging) is realized. The signal acquisition and processing unit integrates a non-magnetic ceramic packaging pre-amplifier and an optical fiber isolation transmission data acquisition card, and is matched with a fan-free design computer, so that the influence of a magnetic field on signal processing is thoroughly avoided. According to the scheme, real-time electroencephalogram monitoring in experimental animal task state functional nuclear magnetism is supported, experiments prove that the signal-to-noise ratio is reduced by 30% or above, the distortion rate is controlled to be 2% or below, the advantages of high biocompatibility, low cost and operability are achieved, and the accuracy and reliability of scientific research data collection are remarkably improved.

The invention relates to the technical field of real estate evaluation, in particular to a building personalized dynamic rating method, system and device and a storage medium. The method comprises the steps of obtaining target building data and corresponding building information in a target region, collecting behavior data, related to building selection, of a target user at the same time, analyzing and mining potential preference point information of the user to form a set, and aiming at each preference point in the set, selecting a target user according to the preference point information, a weight algorithm is determined by combining the importance degree of target building selection and market research data, comprehensive rating calculation can be performed on target buildings according to the algorithm and building information, and single-item rating calculation can be performed on specific preference points according to needs. According to the method, multivariate data are comprehensively fused, personalized requirements of the user are accurately adapted, the problem that traditional building rating is static and single is effectively solved, an accurate and dynamically updated building evaluation reference is provided for the user, and house purchasing and renting decision efficiency and scientificity are greatly improved.

The invention relates to the technical field of biological research data analysis, and discloses a computational biological research data analysis display method, which comprises the following steps of: extracting total RNA (Ribonucleic Acid) from biological tissues or cells, reversely transcribing the RNA into cDNA (Complementary Deoxyribonucleic Acid), constructing a library, and sequencing the library by utilizing a high-throughput sequencing platform to obtain a large number of short sequences. According to the method, the number of the short sequences mapped to the same genome coordinate interval is compared and the threshold value is judged, so that the abnormal repeated area can be effectively identified, whether the gene expression difference result is credible or not is clearly judged, and when the number of the abnormal sequences exceeds the preset repeated sequence threshold value, the influence operation of the repeated sequences is eliminated, and the accuracy of the gene expression difference result is improved. That is to say, completely identical and overlapped short sequences are removed under the condition that the FPKM value is relatively high, and the updating result is compared again, so that the problem of expression quantity distortion caused by repeated reckoning can be corrected.

The invention discloses a data modeling system based on research data, which relates to the technical field of data modeling and comprises a research data acquisition module, a research data cleaning and conversion module, a research data encryption module, a model building, screening and optimizing module and a modeling algorithm library. According to the method, dynamic model construction algorithm selection can be carried out according to research data, model construction processing is carried out, the flexibility and diversity of research data modeling attachment forms are improved, the research data are finely analyzed, reasonable screening of the model construction algorithms can be carried out according to specific data characteristics, and the model construction efficiency is improved. According to the method, the intelligence and coordination of model optimization processing are powerfully supported and guaranteed, higher convenience is also provided for calling and checking of subsequent models, encryption processing is performed on the structured data set by using the AES symmetric encryption algorithm, the attention on data transmission and storage security is improved, and the method is suitable for being used in the field of data transmission and storage. And reliable guarantee can be provided for safe storage of data.

The invention discloses a multi-modal clinical scientific research data processing method and system based on neural symbol hybrid reasoning, and belongs to the field of medical informatization and artificial intelligence. The method comprises the steps of receiving a natural language analysis instruction; analyzing the instruction into a structured formal problem description data object through a language understanding unit by utilizing a nerve-symbol hybrid inference engine, and selecting a data analysis algorithm according to an expert rule base through a symbol inference unit; then, generating a directed acyclic graph analysis flow based on the selected algorithm; and finally, according to the directed acyclic graph analysis flow, processing the multi-modal clinical scientific research data stored in the database, and generating an analysis report containing quantitative indexes. The technical problems that in the prior art, a clinical scientific research data analysis process is split, efficiency is low, and a semantic gap exists in man-machine interaction are solved, automation and intelligence of scientific research analysis are achieved, and the efficiency, depth and scientificity of data processing are remarkably improved.

This application discloses a method, equipment, medium, and product for comprehensive evaluation of equalization of basic medical services, relating to the field of medical geography. The method includes: spatial processing of research data to construct a unified geospatial database; calculating multiple evaluation index values ​​representing the spatial allocation level of medical resources and the spatial convenience of residents' access to medical care through spatial analysis to form an original decision matrix; using the entropy weight method, calculating the objective weights of each evaluation index based on the degree of variation of the multiple evaluation index values ​​across different evaluation areas; processing the original decision matrix using the objective weights based on the TOPSIS model to calculate the comprehensive evaluation index of equalization of basic medical services for each evaluation area; and performing spatial hierarchical mapping based on the comprehensive evaluation index of equalization of basic medical services to generate a multidimensional diagnostic report, thereby avoiding evaluation distortion, accurately reflecting residents' comprehensive employment opportunities in accessing medical services, and enhancing public credibility.

The invention discloses a hospital performance evaluation system based on multi-source scientific research data collaboration, and the system comprises a multi-source data collection module which is used for collecting scientific research performance original data from an internal information system of a hospital and an external scientific research database; the data collaborative processing module is connected to the multi-source data acquisition module and is used for cleaning, integrating and standardizing the scientific research performance original data to generate high-quality collaborative data; the performance indicator modeling module is connected to the data collaborative processing module and is used for calculating the high-quality collaborative data based on a data envelope analysis model and a radial basis function neural network to generate a performance evaluation result; and the performance management platform is connected to the performance indicator modeling module and is used for displaying the performance evaluation result. According to the invention, automatic acquisition, cooperative processing, intelligent modeling and visual management of scientific research data can be realized, and accurate, efficient and dynamic evaluation can be carried out on scientific research performance of hospitals, departments and individuals.

The present invention discloses an animal rotational impact injury testing system. The above-mentioned animal rotational impact injury testing system includes a bearing assembly, a launching device, and an impact seat. The bearing assembly is used to bear and fix an animal. A launching track is provided on the launching device, and a launching port is provided at the end of the launching track. The bearing assembly is located within the launching track. The launching device can drive the bearing assembly to move along the launching track and be launched out from the launching port in a rotating state. The impact seat is arranged on one side of the launching port and is located in the tangential direction of the launching port. This animal rotational impact injury testing system can enable the animal to be impacted in a rotating state and provide appropriate research data for corresponding diseases.

This invention discloses a big data-based system for predicting and evaluating scientific and technological achievements, relating to the field of scientific and technological achievement prediction and evaluation technology. Specifically, it includes: a research and development process data collection module, an information technology achievement prediction module, and an information technology achievement comprehensive evaluation module. The research and development process data collection module collects historical research data, feature data, and network transmission performance data of scientific research projects in real time during the research and development process. The information technology achievement prediction module establishes a prediction model for the feature data of the research process of scientific and technological achievements, sets research process status indicators based on the feature data, and selects network transmission performance data within a stable time range for further training and optimization of the LSTM prediction model. The information technology achievement comprehensive evaluation module comprehensively evaluates the stability of the research process of information technology achievements by predicting real-time network transmission performance data and setting information research fluctuation indicators to predict the stability of the research process.

The invention provides a power dispatching strategy making method and device based on demand response, terminal equipment and a storage medium, and relates to the technical field of power dispatching. According to the method, historical operation data of a plurality of types of operation indexes of a power distribution network and behavior investigation and survey data of a plurality of users in a plurality of power utilization behavior indexes are obtained; constructing a standard evaluation matrix, quantifying the response potential of users participating in power dispatching through a foreground theory, calculating the comprehensive foreground value of each user, comprehensively evaluating the comprehensive capability of each user participating in power dispatching according to the deviation value and the comprehensive foreground value, generating a comprehensive evaluation result, and finally, determining the comprehensive capability of each user participating in power dispatching according to the comprehensive evaluation result. And grading the users, and formulating a power dispatching strategy. Therefore, the method can solve the problem that the formulated power dispatching strategy is separated from the actual condition of the user and is difficult to implement due to the fact that the response potential of the user side resources participating in power dispatching cannot be comprehensively reflected in the prior art.

The application relates to the technical field of data mining, and discloses an intelligent mining system for research data, which comprises a heterogeneous data acquisition module, a semantic association analysis module, a decision graph generation module, a time sequence feature correction module and a knowledge distillation optimization module. The heterogeneous data acquisition module captures data features and constructs a multi-layer topology through a multi-source data perception node and a dynamic dimension fusion network; the semantic association analysis module analyzes semantic association by using a concept topology modeling unit, a knowledge vector clustering unit and a multi-modal switching link; the decision graph generation module generates a core decision benchmark framework based on a strategy optimization node and a rule reasoning engine; the time sequence feature correction module performs time sequence correction and noise compensation on semantic association; and the knowledge distillation optimization module detects deviation through an entity relationship evaluation network and feeds back an optimized decision framework. The system realizes intelligent acquisition of multi-source data, dynamic analysis of semantics and adaptive generation of a decision graph, and improves the precision and efficiency of research data mining.

The application relates to a blockchain data collection method and device based on a multi-architecture NLP pre-training model, and relates to the technical field of artificial intelligence. The method comprises the following steps: training preset demand information by using a first pre-training model and a second pre-training model respectively to obtain two design schemes; analyzing the two design schemes to obtain a first analysis result, generating a first positive sample data set, and obtaining a final design scheme according to the first positive sample data set; analyzing market research data by using the first pre-training model and the second pre-training model respectively to obtain two preliminary data results; analyzing the two preliminary data results to obtain a second analysis result, generating a second positive sample data set, and obtaining a final data result according to the second positive sample data set; and generating a new block according to the first positive sample data set and the second positive sample data set, and responding to and authenticating the new block. The application has the effects of improving data processing efficiency and data accuracy.