569 results about "Database construction" patented technology

The invention provides a carbon database construction method and system based on regional energy carbon emission prediction, and the method comprises the steps: eliminating the space-time reference deviation of an original data set, and generating an energy activity hologram spectrum with a unified space-time label; inputting the energy activity holographic spectrum into a non-linear correlation program, extracting a carbon release intensity characteristic curve of each energy carrier through a self-adaptive weight distribution mechanism pre-stored in the non-linear correlation program, and constructing a spatial-temporal characteristic network in combination with industrial operation cycle parameters and climate response factors in a target area; the spatial-temporal characteristic network establishes a dynamic coupling relationship between an energy flow mode and a carbon emission hot area to form a carbon emission associated topological structure with a self-organizing characteristic; a three-dimensional carbon database is formed, and the three-dimensional representation and deduction capability of space-time evolution of carbon emission is realized. The system comprises an atlas generation module, a structure construction module and a content fusion module. According to the invention, normal form transformation from static carbon accounting to dynamic carbon metabolism simulation is realized.

The invention relates to the technical field of dredge pump performance analysis, and discloses a numerical simulation and model test-based dredge pump performance analysis method, which comprises the following steps of: planning an analysis process, and determining numerical simulation (dredge pump internal flow field simulation) and model test contents (actually measured performance data under different working conditions); determining working condition types according to design parameters and working conditions; generating a performance analysis process set and determining an execution sequence; generating a simulation parameter setting list and a test scheme list of each working condition; and associating the data to generate an overall scheme. The method further relates to working condition analysis boundary determination, working condition type subdivision, dynamic adjustment of the process, test rule optimization, database construction and the like. According to the method, comprehensive and accurate analysis of the dredge pump performance is achieved through multi-dimensional data integration and a dynamic mechanism, the analysis efficiency and reliability are improved, and the method is suitable for evaluation and optimization of the dredge pump performance.

The invention relates to a smart city planning monitoring system, which comprises a multi-source data acquisition module, a database construction and management module, a planning analysis and monitoring module, a communication cooperation module and an interactive decision support module, the database construction and management module is used for constructing and managing a database of urban planning and monitoring data, the planning analysis and monitoring module is used for planning scheme evaluation and progress tracking, the communication cooperation module is used for data communication and module cooperation, and the interactive decision support module is used for data interaction, monitoring visualization and decision support. According to the smart city planning monitoring system, a city planning multi-source data fusion algorithm based on kernel density analysis is put forward to fuse multi-source data, and a smart city planning monitoring algorithm based on analytic hierarchy process and fuzzy comprehensive evaluation is put forward to monitor and evaluate smart city planning.

The invention provides a traditional Chinese medicine intelligent health diagnosis system and method based on multi-source data fusion, and relates to the technical field of health diagnosis. The system comprises a database construction module which is used for collecting condition data and historical disease data of a patient and constructing a traditional Chinese medicine holographic health database. And the multi-dimensional classification module is used for establishing a multi-source data classification standard and adding category fields to the multi-source data in the traditional Chinese medicine holographic health database from multiple dimensions to obtain associated field data. The importance classification module is used for constructing an importance degree judgment standard and judging the importance degree of different associated field data to obtain importance labels, and the exclusive customization module is used for classifying health states according to different importance labels to obtain current health data and formulating exclusive treatment strategies. According to the method, the data are classified and associated from multiple dimensions, the organization and utilization efficiency of the data is improved, and the importance degree judgment method can provide a basis for priority processing and analysis of the data.

The invention discloses an MES (Manufacturing Execution System) login authentication method based on a face recognition technology, which relates to the technical field of industrial information security, and comprises the following steps of: constructing an authentication data acquiring a face image of an authorized user of an MES, extracting a reference face feature template after preprocessing, and constructing the authentication database; performing associated storage on the reference feature template, user identity information, preset operation authority and affiliated production station information to form an authentication database; according to the method, spoofing attacks are prevented through multi-mode living body detection, and the problem that a traditional password / key is easy to leak and borrow is solved in combination with uniqueness of human face biological characteristics; a person-post-terminal binding mechanism further limits permission abuse, and internal operation risks are reduced; the non-contact authentication does not need to memorize a password or carry a physical key, and is suitable for a working scene that a workshop operator wears gloves and holds tools; and the recognition passing rate in a complex industrial environment is improved through dynamic threshold optimization.

The invention relates to the technical field of data information extraction, in particular to a bidding document qualification information intelligent extraction method based on a knowledge graph and hybrid retrieval, which comprises the following steps: a document preprocessing and partitioning step: preprocessing and partitioning a bidding document to obtain a plurality of document blocks; a vector database construction step: vectorizing the document blocks, storing the vectorized document blocks into a vector database, and constructing an index; a knowledge graph construction step: extracting triads from the document blocks, writing the extracted triads into a graph database to construct a knowledge graph, and constructing an index; a mixed retrieval step: carrying out mixed retrieval in combination with the knowledge graph and the vector database; a qualification information extraction step: taking the plurality of document blocks returned by mixed retrieval and the corresponding knowledge graph sub-graphs as contexts, and enabling an Agent agent to perform extraction based on the contexts and an extraction template; and finally, structured qualification item information is output. According to the method, high-quality structured extraction of the qualification information in the bidding document can be realized.

The invention belongs to the technical field of medical imaging and digital twinning, and discloses a thoracic cavity whole organ system level lung four-dimensional EIT detection digital motif and a library building method, and the method comprises the following steps: S1) segmenting multiple organs such as double lungs, heart, sternum, rib and thoracic vertebra central axis skeleton, main bronchus and esophagus based on an individual CT image, and building a three-dimensional geometric model integrated with an EIT electrode array; s2) simulating breathing dynamic deformation by using a solid mechanical model; s3) establishing a coupling relationship between deformation and conductivity, and generating dynamic three-dimensional conductivity distribution; s4) solving an electromagnetic field positive problem, and generating a virtual EIT voltage database synchronous with respiration; the invention also covers pathological model integration and data enhancement strategies. According to the method, a high-fidelity, large-scale and diversified EIT virtual data set can be generated, core data support is provided for training and verifying an AI intelligent reconstruction algorithm, and a model foundation is laid for developing a lung function dynamic digital twinning system.

The invention discloses a sewage data management system and method based on kitchen garbage treatment, and relates to the technical field of data management. The system comprises a data acquisition and historical database construction module, a correlation analysis and dynamic response rule construction module, a sewage data trend pre-judgment module and an operation regulation and data updating module. The data acquisition and historical database construction module is used for acquiring garbage treatment load and sewage data and constructing a historical database covering time period fluctuation and seasonal periods; the correlation analysis and dynamic response rule construction module constructs a dynamic response rule and determines the time delay duration; the sewage data trend pre-judging module is used for acquiring load data in real time and pre-judging a future sewage change trend; and the operation regulation and data updating module adjusts parameters of the sewage treatment system, collects effluent data to construct a new sample, supplements a database and updates a dynamic response rule. According to the invention, accurate sewage data management is realized, and the operation efficiency and stability of the sewage treatment system are improved.

The invention belongs to the technical field of composite material design, and discloses a polyimide-based composite material design method and system based on experiment-machine learning collaborative optimization. The method comprises the following steps: S1, experimental database construction and machine learning performance modeling; S2, machine learning model construction and training; S3, model evaluation and performance index output; and S4, intelligent design of the polyimide-based composite material. The multi-objective performance collaborative optimization design and preparation of the polyimide-based ternary carbon heterostructure composite material are carried out by taking experimental data as a main material and machine learning as an auxiliary material. According to the method, an experiment-model-optimization closed-loop iterative design system is constructed based on an experiment-machine learning collaborative optimization method, the method has the advantages of high prediction precision, high optimization efficiency, good multi-target adaptability and the like, the development efficiency of the polyimide-based composite material is remarkably improved, and the development cost of the polyimide-based composite material is reduced. The method is suitable for intelligent design and large-scale application and popularization of the high-performance heat-conducting electromagnetic shielding material.

The invention relates to a knowledge graph-based teaching resource database construction method and system, and belongs to the technical field of data resource processing, and the method comprises the following steps: S1, obtaining and preprocessing a multi-source heterogeneous teaching resource: carrying out the natural language processing of an unstructured text to recognize the association of an entity and a key concept, analyzing the user behavior log to extract hidden knowledge point association; s2, defining a multi-dimensional teaching knowledge graph mode layer: constructing a multi-dimensional graph mode layer; s3, collaborative extraction and fusion of graph entities and relationships: collaborative extraction of core teaching entities and specific relationship types from the preprocessed teaching resources to construct a knowledge graph; s4, adaptive graph updating and teaching path generation: taking the constructed knowledge graph as an underlying database, and responding to knowledge state query of a user; the method has the beneficial effects that massive and heterogeneous teaching resources and the knowledge graph are effectively fused.

The invention discloses a Chinese character structure and geometric space interactive writing method, which relates to the technical field of interactive writing methods, and comprises the following steps: carrying out geometric classification processing on Chinese characters by adopting a structural analysis method to obtain a Chinese character type set comprising a left-right structure, an up-down structure and a surrounding structure; carrying out geometric rule definition processing on the obtained Chinese character type set to obtain a geometric constraint rule base containing component proportion, gravity center alignment and stroke topological relation; performing structured storage processing on the obtained geometric constraint rule base by adopting a database construction method to obtain a dynamically-called Chinese character writing template database; the writing process of the user is monitored in real time, and a writing feature data set containing stroke coordinates, writing speed and pressure data is obtained; performing matching processing on the obtained writing feature data by adopting a dynamic grid generation method to obtain a self-adaptive reference grid corresponding to the currently written Chinese character; and carrying out deviation detection processing on the obtained self-adaptive reference grid by adopting a computer vision method.

The invention relates to a product carbon footprint basic database construction method. According to the method, government supervision data, enterprise live-action data and industry standard data are integrated, a carbon footprint model of a production stage and a full life cycle is constructed in combination with a life cycle evaluation method, data cleaning is performed on original data, carbon footprint factors are graded and dynamically updated based on an energy efficiency level, and a carbon footprint model is obtained. Accurate calculation of industrial chain carbon footprint factors, effective integration of multi-source heterogeneous data and dynamic iteration of a database are achieved, the problems that an existing database is insufficient in regional representativeness, poor in timeliness and low in technical transparency are solved, and finally a localized carbon footprint basic database which is comprehensive in coverage, traceable and compatible with international standards is established. And reliable data support is provided for carbon accounting and international trade barrier coping.

The invention discloses a CKD special disease database construction method and system, and relates to the technical field of database construction, and the method comprises the steps: obtaining and predicating a multi-source heterogeneous atomic fact; constructing and fusing three sets of ontology models; verifying and deducing facts in a layered manner according to a multi-layer priority rule base; calling a constraint completion engine to generate inference facts for missing or conflicting fields; streaming follow-up visit, test and intervention logs into events and triggering graded alarms; an anti-fact intervention scene is simulated for the high-risk patient, and pilot groups are screened; dynamically evaluating and adjusting the rule priority; and based on a causal chain and an event mode, clustering patients and constructing a generality map, and recording a whole-process operation chain. Semantic management is realized through fusion of ontology, anti-fact intervention simulation is performed on high-risk patients by means of multi-layer rule verification, and database semantic consistency, reasoning depth, decision support and traceability are improved through causal atlas driven clustering.

The invention relates to the technical field of intelligent recruitment management, and discloses an intelligent matching recruitment management system based on a large model. The system comprises a talent database construction module which collects multi-dimensional ability characteristics of job seekers and enterprise post demand data and generates a three-dimensional recruitment data set containing ability, post and time dimensions; the personnel post adaptation field modeling module performs dynamic integrating degree analysis on the data set, constructs a three-dimensional personnel post adaptation field, and identifies adaptation field critical point distribution and a flowing path; the key feature screening module extracts core adaptive features meeting a threshold value; the large model matching engine module inputs the core adaptive features into a pre-training large model generator, introduces adaptive field topology and feature continuity constraints, and outputs optimized dynamic adaptive field distribution; the environment variable compensation module fuses the dynamic indexes of the labor market to generate compensation parameters, and corrects the core adaptation features; and the strategy generation module generates a post matching strategy set and a talent optimization path to adapt to the requirements of the recruitment market.

The invention discloses a high-speed rail vehicle body aluminum alloy material corrosion fatigue performance simulation method and system, and belongs to the technical field of material corrosion fatigue testing. The method comprises the following steps: acquiring multi-source data of a high-speed rail body aluminum alloy material on an actual service route; establishing a material corrosion conversion coefficient database; obtaining an equivalent mapping relation based on the service environment and the load input set; generating a laboratory equivalent accelerated environment spectrum; and executing the laboratory equivalent accelerated environment spectrum, obtaining material failure data, and if the comparison difference is not less than a preset threshold value, correcting the calculation parameters of the equivalent mapping relation and regenerating the spectrum system. Through synchronous acquisition and fusion analysis of the multi-source environmental data and the mechanical load and in combination with the corrosion conversion coefficient database construction and closed-loop verification optimization method, the problem of test result distortion caused by separation of a laboratory simulation environment and an actual service condition in the prior art is solved.

The invention belongs to the technical field of composite material design, and discloses a polymer composite material design method based on LLM knowledge database construction and reasoning optimization, and the method comprises the following steps: S1, target performance setting; s2, constructing a knowledge database; s3, constructing a reverse design model; s4, constructing a performance verification module; and S5, performing multi-round test-verification design loop optimization. According to the method, an intelligent design method integrating target setting, semantic knowledge database construction, a design assistant, a performance verifier, a prompt engineering module and a language model material knowledge system is provided, closed-loop reasoning and feedback of structure-mechanism-performance are achieved through multiple rounds of DA-VM collaborative optimization, and the design efficiency is improved. The method has the advantages of high design efficiency, strong structure generation rationality, accurate performance prediction, knowledge evolvable and the like, and is suitable for intelligent rapid development of the high thermal conductivity-wave absorbing-shielding-mechanical integrated functional polymer composite material.

The invention relates to a diabetes management system, equipment and a medium. The method comprises the steps that a data processing module collects multi-modal medical data, dynamic time sequence features are extracted through a graph neural network to label semantic tags, and a structured patient information data set is formed; in the database construction module, a data fusion unit performs cross-modal feature alignment, redundancy elimination and feature enhancement on the structured data set, and establishes a dynamic and unified health record database; and the risk assessment unit extracts individual features by adopting an improved random forest algorithm based on the database, and generates a personalized health risk assessment report. And the health management module customizes a health management scheme through a generative adversarial network according to the evaluation report, and dynamically updates intervention measures according to real-time monitoring data. By adopting the system, the accuracy and individuation degree of risk prediction can be improved, accurate and dynamic whole-cycle health management service is provided for diabetics, and the management efficiency and the medical quality are effectively improved.

The invention discloses a compound structure identification database construction method, system and device and a medium, and the method comprises the steps: inputting a model training data set into a plurality of retention time prediction models for training, and obtaining a plurality of trained retention time prediction models; verifying the plurality of trained retention time prediction models by adopting a model verification data set, and selecting an optimal retention time prediction model; inputting the migration training data set and the migration verification data set into the optimal retention time prediction model for migration learning to obtain a target retention time prediction model; inputting to-be-predicted compound structure data into the target retention time prediction model for prediction to obtain predicted retention time; and constructing a compound structure identification database according to the predicted retention time. The data in the compound structure identification database can be perfected, and the accuracy of the compound structure identification database is improved, so that the database performance is improved.

The invention relates to the technical field of ecological environment monitoring, in particular to a grassland environment resource database construction method, which comprises the following steps of: arranging a multi-modal sensor in a fractal multi-scale grid and synchronously collecting; obtaining a standard frame by adopting quantum random walk compression and space-time registration; extracting a topological bar code through neuromorphic pulse coding and persistent coherent topology analysis, and generating a unified potential space tensor and a missing mask in combination with weighted mutual attention and optimal transmission; constructing an energy function containing carbon and nitrogen conservation and topological deviation, and reconstructing a complete ecological submerged space tensor through Hamiltonian Monte Carlo-diffusion combined sampling; ecological indexes and abnormal events are reasoned in the Shenchang differential graph database, sampling scheduling is driven by prediction errors, closed-loop updating of data, models and sampling is achieved, and therefore the grassland monitoring precision and early warning timeliness are improved.

The invention relates to an aircraft control surface oscillation alarm method and system based on airframe response, which have enough monitoring capability and can make corresponding identification and alarm in different oscillation fault scenes. The airplane control surface oscillation alarm method comprises the following steps: a database construction step: acquiring airplane body response data after various control surface oscillation faults occur, and constructing a database of a relationship between control surface oscillation and airplane body response; a data acquisition step: arranging an acceleration sensor and / or a strain sensor at a specific position of the airplane so as to acquire actual response data of an airplane body in the operation process of the airplane; a fault identification step: comparing the actual response data of the aircraft body with the response data of the aircraft body in the database, and identifying the oscillation fault of the control surface and the oscillation information of the control surface; and an alarm judgment step: judging whether the control plane oscillation alarm information is provided or not based on the control plane oscillation information and the allowable oscillation angle limit value.

The invention discloses a flood forecasting method for constructing a dynamic unit line library based on rainfall flood data feature classification. The flood forecasting method comprises the following steps: S1, collecting historical data; s2, data cleaning and preprocessing; s3, constructing a flood data classification model; s4, unit line calculation and storage; s5, real-time flood forecasting; s6, performing visualization and verification; the method comprises the following steps: receiving short-term rainfall forecast of a meteorological department in real time, synchronously acquiring measured data of a rainfall station and a water level station in a drainage basin, counting current early-stage influence rainfall, performing feature analysis, establishing a CNN + K-means model, dynamically outputting a forecast result, generating a forecast flood hydrograph according to a calculation process, and continuously performing automatic rolling forecast according to real-time data. A forecasting result is automatically updated, and a real-time data and forecasting result chart is generated; a more scientific basis is provided for flood control decision making, and disaster loss caused by defects of a traditional method is effectively reduced.

The invention discloses an engineering quantity list comprehensive unit price rationality detection method and system, and belongs to the technical field of engineering cost. The invention discloses a bill of quantity comprehensive unit price rationality detection method and system. The method comprises the steps of extracting key factor features; obtaining a comprehensive unit price corresponding to the project name; constructing a project recognition library; s4, correcting and perfecting the prices of the abnormal items; calculating the comprehensive unit price of the new engineering project; the system comprises a unit price calculation module, a database construction module, a comprehensive unit price identification module and a new engineering project determination module. The problem that the comprehensive unit price of the new engineering project cannot be determined in the prior art is solved, the comprehensive unit price of the new engineering project can be calculated, pricing dispute caused by fuzzy feature description of the new engineering project can be reduced, the abnormal quotation can be effectively identified, and by correcting the abnormal quotation deviating from the rationality interval, the pricing efficiency of the new engineering project is improved. The construction period delay or claim risk caused by pricing errors can be reduced.

The invention discloses a battery material database construction method and system. The method comprises the following steps: manually inputting raw material and battery material information; automatically acquiring experimental data of the battery material; converting the acquired unstructured warehousing data into structured warehousing data; carrying out model training, testing and evaluation to obtain an optimized model; on the basis of the optimized model, online analysis is carried out on warehousing data, and the potential relation between the performance and the characteristics of the battery material is searched for actual prediction or classification tasks. According to the method and the system, the integrity and the richness of database information are ensured by collecting the relevant information of the whole life cycle of the battery material, a solid data foundation is laid for application, and by performing data mining and analysis on the warehousing data, the safety of the battery material is improved. And a scientific basis is provided for performance evaluation, life prediction and formulation of a personalized research and development scheme of the battery material.

The invention provides a material database construction method and system based on high-throughput experiment multi-modal data, and relates to the technical field of material database construction, and the method comprises the steps: building a standardized experiment data collection protocol; synchronously acquiring an original multi-modal experimental data set according to a standardized experimental data acquisition protocol; processing the infrared thermal imaging data, and extracting structured temperature characteristics of each catalyst channel; integrating the experimental metadata and the sensor time sequence data to generate a standardized sample-experiment-performance associated data record; and constructing a material database by adopting a three-layer logic architecture and a mixed physical storage strategy according to a standardized sample-experiment-performance associated data record and index information of an original multi-modal experiment data set. According to the method, the material database which is standard in data, accurate in feature, clear in structure and easy to manage can be constructed. The database can effectively support data retrieval, performance comparison and model construction in material research and development.

The invention discloses an information data analysis system based on engineering practice, which relates to the technical field of engineering data processing, and comprises the following modules: an engineering database establishment module for acquiring design stage data, construction stage data and completion acceptance stage data, establishing an engineering database, establishing a stage data set in the engineering database, and establishing a stage data set in the engineering database; the design stage data, the construction stage data and the completion acceptance stage data are stored in a stage data set in the form of three stage sub-data sets; the data is regularly screened, so that the phenomenon that only one copy of data is stored in a backup data set due to the fact that no data is lost in a stage data set, a structure data set and a change data set when the data is backed up in a singular data backup module is avoided, loss of single data is further avoided, and the data backup efficiency is improved. And meanwhile, more than two duplicated data which are not in the corresponding classification data sets in the engineering database are deleted, so that the storage space of the engineering database is conveniently saved.

The invention provides a method for rapidly evaluating the residual strength of a damaged composite stiffened wallboard structure, which is applied to the evaluation of the residual strength of a composite stiffened wallboard in an undetectable area in an actual aircraft structure under possible accidental source damage, and comprises the following steps: (1) damage identification based on a piezoelectric sensing system; (2) carrying out damage equivalence on a damage identification result; (3) constructing a residual intensity database; (4) training a neural network model of the residual intensity database; and (5) quickly evaluating the residual strength of the actual damaged wallboard based on the sensing system and the neural network model. After a flight task of a flight product is completed, on the premise that database construction and model training are completed in the earlier stage of the ground, the method can greatly shorten the evaluation period of the residual strength performance of the composite material stiffened wall plate, and therefore the method serves for identifying the re-flight capacity of an aircraft.

The invention provides a kiwi fruit whole industry chain knowledge graph database construction method, which comprises the steps of S1, designing a relationship between top-level concepts and concepts of a knowledge graph database to obtain a knowledge graph concept mode; s2, constructing a kiwi fruit text data set, and performing BIO labeling by using a semi-automatic method to obtain a labeled data set; step S3, performing entity identification by using a BiLSTM-CRF model; s4, forming a triple by the extracted entities according to the guidance of the conceptual mode; step S5, the assembled triad is stored in a Neo4j database, and the visualization of the database is realized; s6, completing the design of the automatic recommendation method based on the knowledge graph under the support of the Neo4j database data; and S7, designing a recommendation system architecture, and constructing an available recommendation system. The method is low in cost, high in knowledge integrity and convenient to update and maintain, and the recommendation system obtains knowledge more simply and conveniently.

The invention discloses an intelligent identification and counting method, system and equipment for an industrial elevator and a medium, and the method comprises the steps: collecting an interference target negative sample, generating a diversified illumination scene sample, combining the interference target negative sample with the illumination scene sample, training and optimizing a detection model, deploying the trained and optimized detection model, and processing a video stream in real time. And judging the effective lifting behavior of the elevator, and intelligently counting the operation frequency of the elevator. According to the method, an adversarial training strategy and negative sample database construction are adopted, the discrimination capability of the model for an interference target is remarkably improved, the stable recognition performance of the system under the all-weather condition is ensured through developed illumination enhancement simulation, and the intelligent counting algorithm based on the state machine is used for realizing the intelligent counting of the interference target through a rigorous condition judgment mechanism. Accurate statistics of the work cycle of the elevator is achieved, a reliable automatic counting solution is provided for an industrial site, and the intelligent level of production management is greatly improved.

The invention provides a mechanical equipment structure key pressure-bearing component real-time simulation method based on digital twinning, which takes a cubic press hinge beam as an example, and combines finite element analysis, Latin hypercube sampling, a K nearest neighbor algorithm, Gaussian interpolation and an RBF (Radial Basis Function) proxy model to realize stress-strain rapid prediction and three-dimensional visualization. According to the method, an efficient prediction model is established through structure database construction, dimension reduction processing, neighbor search and interpolation calculation, a simulation result is presented in real time by utilizing Python and Unity interaction, the design efficiency and accuracy are improved, and the method is suitable for structure optimization analysis under complex working conditions.

The invention relates to the technical field of data information processing, in particular to a multi-modal medical database construction method and system, and the system comprises a data collection module, a data preprocessing module, a data storage module, and a multi-modal model construction module. According to the method, the deep learning diagnosis model based on multi-modal data fusion is constructed, so that accurate early warning of disease progress key nodes is realized; the model integrates multi-modal data such as clinical indexes, laboratory examination and iconography data, processing is performed through methods such as feature extraction, standardization and normalization, key information in each modal data is extracted, disease development rules and patient individual differences are captured, and high-risk patients are identified; particularly, the deep learning model is utilized to process and predict multi-time-point data, so that the timeliness and accuracy of the model are improved, early recognition and timely intervention are realized, and a better treatment opportunity is provided for a patient.