49 results about "Screening algorithm" patented technology

The invention belongs to the technical field of artificial intelligence algorithm and bioinformatics crossing, and relates to a drug interaction prediction method based on multi-modal molecular characterization. According to the method, through the edge perception GCNII architecture and the Hop2Token multi-hop coding mechanism, effective modeling of atomic-level and bond-level local environments and a cross-substructure high-order dependency relationship in drug molecules is realized, and the accuracy and robustness of drug interaction prediction are improved. According to the method, Mol2Vec and MolT5 cross-modal molecular characterization is integrated, fusion of molecular overall semantics and substructure grammar semantic association is achieved, and the generalization ability of the model to complex molecules and unknown medicine combinations is remarkably improved. According to the method, the dynamic feature screening algorithm driven by the SHAP value of the artificial intelligence technology is adopted for biological verification, the feature redundancy problem is effectively solved, the molecular biological information analysis processing calculation efficiency and the model transparency are improved, and the traceability of the prediction process is guaranteed.

The invention discloses an interactive lattice radiotherapy planning method and system based on a functional image, and relates to the technical field of radiotherapy, and the method comprises the steps: obtaining a radiotherapy positioning CT image of a patient and a functional metabolism image after the space registration with the radiotherapy positioning CT image; based on the radiotherapy positioning CT image and a preset safety boundary parameter, determining a candidate area of lattice layout in the tumor target area; for each candidate position in the candidate region, adaptively calculating lattice parameters for the position based on the corresponding SUV value of the position in the functional metabolism image; determining a final lattice center set from the candidate positions through an iterative screening algorithm on the basis of the calculated lattice parameters of the candidate positions and preset geometric constraints and biological constraints, and generating a lattice target region set on the basis of the final lattice centers and the lattice diameters corresponding to the final lattice centers; and outputting the lattice target region set for dose calculation of a radiotherapy planning system. Individualized dosage improvement really based on tumor internal heterogeneity is achieved.

The invention relates to a batch material transfer method, system and equipment based on a workbin robot and a medium, and the method comprises the steps: obtaining the original code scanning data of a plurality of workbin robots for a target workbin, updating the original code scanning data based on a verification screening algorithm, and obtaining the target code scanning data; acquiring transfer sensing data of a target material box in a transfer time period based on the material box robot, determining a first transfer parameter of the target material box, and determining a second transfer parameter of the target material box according to the target code scanning data; and according to the first transfer parameter and the second transfer parameter, based on an accuracy prediction neural network, an accuracy parameter of the material transfer information in the target material box is determined, and the accuracy parameter is used for representing the accuracy degree of the material transfer process in the production plan.

The invention provides a Web-based single-cell RNA sequencing data intelligent analysis system and method. The method comprises the following steps: receiving a cell group through a Web interface; performing differential gene analysis on the single-cell RNA sequencing data contained in the cell group to obtain an original differential gene list, and filtering the original differential gene list by adopting a multi-threshold screening algorithm to obtain a target differential gene list; performing species automatic identification processing on the target differential gene list, calling a target local gene set database based on a result of the species automatic identification processing, and performing parallel enrichment analysis independent of network connection on the target differential gene list according to the target local gene set database to obtain a gene enrichment analysis result; and generating an interactive chart by adopting an intelligent label anti-overlapping algorithm so as to visualize the interactive chart. According to the method, the problems of high operation threshold, low batch analysis efficiency, unstable result and poor interactivity in the prior art are solved.

The invention discloses a human body infrared spectrum intelligent screening feedback device and immune enhancement and anti-inflammatory application thereof, and relates to the technical field of human body feedback devices. The human body infrared spectrum intelligent screening and feedback device comprises an infrared detection unit, at least one biomarker sensor, a central processing unit and an infrared feedback unit. According to the human body infrared spectrum intelligent screening and feedback device, the infrared detection unit and the biomarker sensor are integrated, multi-source information is subjected to fusion analysis through the central processing unit, comprehensive judgment of the human body immune or inflammation state is achieved, the device dynamically calls a matched infrared spectrum screening algorithm according to the judgment result, and the human body infrared spectrum intelligent screening and feedback device is suitable for being applied to human body health. The infrared feedback unit is driven to carry out targeted irradiation, real-time sensing analysis and dynamic screening are achieved, the information is accurately fed back to uncomfortable body parts, and the problems that in the prior art, diagnosis and treatment are disjointed, and intervention parameters are solidified are effectively solved.

The invention discloses a military crane chassis fault reproduction and practical training system based on working condition simulation, and relates to the technical field of military equipment practical training, and the system comprises an entity chassis building unit which selects and uses entity parts of subsystems of a military automobile crane to be arranged and installed according to a real automobile, retains a key relation, presets an interface, defines a safety threshold value and the like; the dual-mode fault generation unit constructs an initial library, and an intelligent agent is embedded to generate a fault; the multi-dimensional data acquisition unit responds to the trigger signal to acquire multiple types of data; the fault diagnosis practical operation unit is used for trainees to operate; the training evaluation and fault iteration unit generates a report and feeds back optimization suggestions; according to the invention, a dual-mode fault generation unit is constructed, an initial fault library and an intelligent agent exploration capability are integrated, a screening algorithm is matched, and multiple fault scenes are provided; a complete practical training system is built, multi-dimensional data acquisition is achieved, practical operation and evaluation iteration are standardized, the practical training quality is improved through closed-loop design, and the military crane chassis fault practical training requirements are met.

The application discloses a data screening, large language model output acceleration method, device, medium and product. The data screening method comprises the following steps: selecting a thread bundle and determining a local comparison value of the thread bundle; triggering each thread bundle to execute an operation of comparing the numerical value between each current probability value and the baseline value of itself, and updating the key value of itself using each current probability value greater than the baseline value of itself; comparing the screening threshold of a target screening algorithm with the key value of each thread bundle; if the screening threshold and the key value of each thread bundle do not match, updating the target set and the current probability value set according to the identified first thread bundle and second thread bundle; and if the screening threshold and the key value of the third thread bundle match, updating the target set according to the third thread bundle as a screening result. The technical scheme of the embodiment of the application effectively reduces the calculation complexity of the data screening algorithm in a soft and hard cooperative manner, and maximally utilizes the parallel computing hardware in the artificial intelligence acceleration computing chip.

The invention relates to a retrieval enhancement generation method, system and device based on information optimization and a storage medium. Aiming at the technical problems of high calculation cost and damaged generation quality caused by context information redundancy and noise accumulation due to simple Top-K retrieval in the existing retrieval enhancement generation technology, the invention creatively introduces the concept of ''in engineering thermodynamics, establishes isomorphic mapping of information retrieval and thermodynamics, and improves the information retrieval efficiency. A high-value information unit is preferably selected from a retrieval result by calculating an'information 'value fusing semantic correlation (information temperature) and redundancy (information invalid performance) and adopting a self-adaptive dynamic screening algorithm based on marginal maximization and dead-state temperature threshold truncation. According to the scheme, the length of the input context and the calculation cost can be remarkably reduced while the generation quality is ensured, the robustness of the system in a noise environment is improved, and high-efficiency and high-quality retrieval enhancement generation is realized.

The invention discloses a two-dimensional image feature extraction method under adaptive polar coordinate mapping. The method comprises the following steps: step 1, intercepting a short-time sequence by using a short-time sliding window function; step 2, generating a time domain signal short-time matrix energy-time distribution map; step 3, positioning a key signal sequence representing fault characteristics through a peak screening algorithm; step 4, adaptively adjusting scale parameters of polar coordinate mapping, and constructing a multi-scale polar coordinate space; 5, generating a two-dimensional image under adaptive polar coordinate mapping; and step 6, eliminating the influence of rotation speed fluctuation on image features through normalization processing. And step 7, extracting spatial features by using a convolutional layer, and realizing adaptive diagnosis under a variable-speed working condition. According to the method, the fault features of the rotating equipment under the variable-speed working condition can be effectively extracted, and the features have robustness in a time-varying speed strong noise environment.

The invention relates to a fixed asset investment screening method and system, and the method comprises the steps: displaying a user interaction interface in response to a preset operation, and obtaining and displaying a plurality of fixed asset data from a database in response to an input operation on the user interaction interface; a setting interface is displayed in response to the trigger operation, a corresponding investment priority and a capital demand of each fixed asset every year are set for each fixed asset corresponding to each fixed asset data in response to an input operation on the setting interface, and the capital demand comprises a capital source and a requested capital amount; obtaining fund information for fixed asset investment from a database, wherein the fund information comprises a plurality of fund sources, a fund available amount of each fund source and a fund use constraint condition; and based on an investment screening algorithm, fund distribution screening is performed on each fixed asset by using the fund information, the investment priority corresponding to each fixed asset and the annual fund demand of each fixed asset to obtain an invested fixed asset list.

The invention provides a log anomaly detection method and system based on deep learning, and relates to the technical field of log analysis and operation and maintenance monitoring, and the method comprises the steps of log access and preprocessing, connectable testing, data screening and analysis debugging; carrying out log mode recognition and anomaly detection, adopting a dynamic algorithm aggregation mode, eliminating noise and grading anomalies; aggregating alarms and faults, generating alarms, and analyzing cross-service line faults; intelligent analysis: constructing a knowledge base, generating an intelligent report and optimizing the intelligent report; and fault overview and disposal, operation and maintenance data display, and full-life-cycle operation support. According to the invention, by fusing the dynamic similarity aggregation and the mode stability screening algorithm, the log mode recognition accuracy is improved, the false report and the missing report are reduced, and the anomaly detection efficiency is improved; and meanwhile, an exclusive knowledge base and a business adaptation retrieval algorithm are constructed, intelligent fault analysis is realized in combination with a large language model, the troubleshooting and repairing period is shortened, a closed-loop optimization mechanism is formed, and the operation and maintenance efficiency is improved.

The application provides a graph question answering method and system based on context semantic retrieval and a computer readable medium, comprising: performing error correction processing on a question input by a user to generate a question sentence conforming to a format requirement; constructing a pre-training model based on context semantic retrieval to perform semantic retrieval on the question sentence to obtain candidate S, P and O; performing fine screening on the candidate S, P and O in combination with a multi-layer sliding window fine screening algorithm to obtain target S, P and O; judging a question type of the target S, P and O, generating a graph query statement corresponding to the question type through a graph query statement generation module; executing the graph query statement on a graph database and analyzing a query result to generate a question answer conforming to a format requirement to feed back to the user. The method solves the demand for a large amount of labeled data and model training to adapt to a scene in which an existing knowledge graph system needs to quickly experience a question answering effect and lacks training data.

The invention discloses a drug virtual screening task scheduling method and device based on an intelligent agent and a medium. The method comprises the steps that drug virtual screening task information is received; a directed acyclic graph of at least one task execution path is determined according to the medicine virtual screening task information through the trained intelligent model, the directed acyclic graph of the task execution path is composed of a plurality of cascaded atomic task nodes, and each atomic task node is responsible for a corresponding medicine virtual screening sub-task; according to the directed acyclic graph of the task execution path, determining a calling sequence of services matched with the atomic task node; and calling the services according to the calling sequence of the services so as to execute the medicine virtual screening sub-tasks in charge of the atomic task nodes through the services, and the services matched with the atomic task nodes are obtained by packaging a medicine virtual screening algorithm or tool through a model context protocol (MCP). Automation and intelligentization of the whole process of virtual drug screening are achieved, the use threshold is greatly lowered, and the drug research and development efficiency is improved.

This invention discloses an AI monitoring and evaluation method and system for nitrogen reduction in wastewater treatment, relating to the field of wastewater treatment technology. The method includes: collecting multi-dimensional parameters related to nitrogen reduction in wastewater treatment; screening and calibrating parameters using a nitrogen feature independent component screening algorithm; determining the parameter importance ranking using the SHAP nitrogen feature contribution analysis algorithm; constructing a dissolved oxygen coupled nitrogen conversion prediction model based on the calibrated parameters and their contributions to predict nitrogen conversion rate and efficiency; inputting the prediction results and real-time operating parameters into the SOURATP nitrogen process intelligent early warning and judgment platform to identify abnormal operating conditions; and finally generating an AI monitoring and evaluation report. The system comprises six units. This method and system eliminate the need for manual sampling and offline detection, enabling real-time capture of parameter changes, improving monitoring real-time performance. The integration of multiple algorithms for collaborative analysis enhances the accuracy and comprehensiveness of the evaluation. It can also provide early warnings of anomalies and pinpoint influencing factors, improving anomaly response efficiency and facilitating efficient management and control of nitrogen reduction in wastewater treatment.

The application relates to an orchard robot binocular vision inertial positioning method, device, equipment and medium, which comprises the following steps: screening the line features based on a preset line feature length screening algorithm to determine the line features with a preset length threshold, adopting a preset line feature matching screening algorithm to match the front and rear frames of the orchard images of the left eye or the right eye according to the line features with the preset length threshold to determine the line feature matching pairs, extracting the key frames of the orchard images according to the point feature matching pairs and the line feature matching pairs to determine the key frames in the orchard images, performing triangulation processing on the line features of the key frames to construct line feature re-projection residuals, fusing the line feature re-projection residuals with the cost functions of the prior residuals, IMU residuals and point feature re-projection residuals to minimize the cost functions, and completing the binocular vision inertial positioning of the orchard robot. The application significantly improves the positioning accuracy of the orchard robot.

The invention provides an icing micro-topography area identification method and device, and aims to accurately identify an icing micro-topography area of a monitoring area. The icing micro-topography area identification method comprises the following steps: acquiring digital elevation model data of a plateau mountain area and digital elevation model data of a monitoring area according to a remote sensing satellite image; based on the digital elevation model data of the plateau mountain area, extracting feature data of different types of icing microtopographies; an orthogonal line buffer area screening algorithm is combined with the feature data to determine area sample data corresponding to different types of icing microtopographies, and the orthogonal line buffer area screening algorithm is used for dividing buffer areas according to feature lines fitted by the feature data and orthogonal lines with preset lengths so as to determine different types of icing microtopography areas; training a terrain recognition model by using the regional sample data; and inputting the digital elevation model data of the monitoring area into the terrain recognition model to obtain an icing micro-terrain area in the monitoring area.

The application discloses a kind of based on scene driving's retired battery controllable screening method and device, the method includes: the electrochemical characteristic data of each retired battery monomer is collected;Mathematical transformation processing and outlier detection are carried out on electrochemical characteristics, and retired battery screening dataset is established;According to the characteristic requirement of recycling scene, determine screening strategy, including screening algorithm type and the weight coefficient of each electrochemical characteristic;Input the group configuration parameter expected in recycling scene, including target classification cluster total number and the battery quantity constraint of each cluster;After retired battery screening dataset is normalized, screening model is constructed based on screening strategy and the result is output.The application can solve the problems existing in current retired battery screening, such as screening standard and recycling scene disconnection, uncontrollable screening quantity, etc., so that the retired battery screened is closer to the demand of actual recycling scene for grouping quantity, consistency and battery performance, and the scene adaptability and controllability of retired battery screening are improved.

The invention provides a newborn congenital heart disease multi-index integration screening algorithm. The newborn congenital heart disease multi-index integration screening algorithm comprises the following steps: a, data acquisition: acquiring vital sign data of a newborn in real time through a sensor; b, data preprocessing and standardization: performing data cleaning and de-noising processing on the collected vital sign data; and c, intelligent analysis and multi-index integration: performing intelligent analysis on standardized data based on a machine learning algorithm, and integrating various indexes by using a weighting function to generate a congenital heart disease risk assessment value. According to the newborn congenital heart disease multi-index integration screening algorithm, the physiological state of the newborn is comprehensively evaluated through multi-index integration analysis, various potential risk factors are incorporated, and the screening precision of the newborn congenital heart disease is remarkably improved.

The present application relates to the technical field of underwater acoustic target recognition, in particular to a kind of underwater acoustic target recognition method and system based on beam perception, first extract acoustic statistical initial feature from beam domain signal, and then propose beam perception feature screening algorithm, the central echo and other beam features are comprehensively analyzed, and the preferred feature subset with cross-beam discrimination ability is screened;Subsequently, the spatial prior information is embedded using the self-defined beam perception position coding, and the beam perception attention mechanism is designed to capture the differences between beams, thereby realizing the effective fusion of multi-beam features;Finally, the recognition result is output by the classifier.The present application significantly reduces the false alarm rate of the system while maintaining the target recognition recall rate, and improves the robustness and generalization ability of the recognition model in complex underwater acoustic environment.

The application provides a phased array antenna beam broadening method, electronic equipment and a readable storage medium. The method comprises the following steps: constructing an optimization fitness function suitable for a phased array antenna, wherein the optimization fitness function comprises a normalized weighted combination of a beam width term for guiding an optimized half-power beam width to approximate a target beam width and a sidelobe level term for guiding an optimized sidelobe level to approximate a sidelobe suppression reference level; setting array physical parameters and beam optimization target parameters; initializing a meta-heuristic algorithm and generating an initial population, each individual in the initial population corresponding to a phase configuration scheme of all elements in the phased array antenna; starting an iterative optimization cycle, and in the case that the fitness value of each individual in the current population does not satisfy an iteration end condition, sequentially performing elite population screening, algorithm parameter updating, mutation operation, crossover operation and greedy selection operation to obtain a population of the next iteration.

The embodiment of the specification discloses a method and device for determining the distribution of suction holes of a printing suction platform and electronic equipment, wherein the diameter of the suction hole is determined according to the medium characteristics of a paper on the suction platform; the opening rate of the suction platform is calculated by force analysis on the paper; the initial distribution of the suction hole on the suction platform is determined by using a screening algorithm according to the diameter of the suction hole and the opening rate; and the position distribution of the suction hole on the suction platform is determined by optimizing the initial distribution of the suction hole on the suction platform.

The invention discloses a Chinese and English mixed text deduplication method based on density clustering and semantic verification. The method comprises the following steps: converting each text into each semantic vector, and obtaining a first cluster based on a density clustering algorithm; performing iterative optimization on the first cluster based on a binary search framework in combination with semantic verification of the large model to obtain a cluster threshold value; updating the first cluster based on a cluster threshold to obtain a plurality of second clusters; and based on a preset semantic screening algorithm and a preset expression screening algorithm, de-duplicating each second cluster to obtain a de-duplicated text list. By means of the mode, the optimal clustering threshold value can be obtained through automatic iterative optimization, the clustering threshold value does not need to be set manually, Chinese and English mixed texts with different semantic densities can be adapted, and semantic consistency in the same cluster is achieved; through the preset semantic screening algorithm and the preset expression screening algorithm, semantic uniqueness and expression diversity can be reserved, and expression similarity misjudgment caused by language structure difference is avoided.

The application discloses a FRER path selection method and system based on GRU and DQN, relates to the technical field of industrial internet communication, and comprises the following steps: establishing a TSN network model; determining constraint conditions of path transmission based on the TSN network model and a service level agreement SLA constraint; calling a gating recurrent unit GRU candidate path screening algorithm to screen a candidate path set from a path set based on the TSN network model and the constraint conditions of path transmission; constructing a bandwidth cost and path independence multi-objective optimization function based on the candidate path set, formalizing a frame replication and elimination FRER path selection problem; and calling a deep Q network DQN redundant path decision algorithm to select a redundant path set from the candidate path set based on the formalized FRER redundant path selection problem. The application realizes dynamic selection of FRER redundant paths in a time-sensitive network, and improves the flexibility of redundant transmission.

The application relates to the field of joint positioning, and discloses a UWB and IMU joint positioning method, equipment and a storage medium. The method comprises the following steps: receiving a ranging signal of a UWB base station, and reading angular velocity and specific force values of an IMU; performing screening and optimization processing on the ranging signal according to a preset UWB signal screening algorithm to generate an optimized ranging signal; constructing a high-dimensional state vector; performing navigation propagation processing on the high-dimensional state vector based on the angular velocity and the specific force values to obtain a predicted state vector, and obtaining a predicted covariance matrix according to a preset state propagation algorithm; performing residual calculation on the optimized ranging signal and the predicted state vector to obtain an observation residual and an observation Jacobian matrix; and performing Kalman observation update processing on the predicted state vector and the predicted covariance matrix to obtain an observation state vector and an observation covariance matrix. In the embodiment of the application, high-precision position and attitude information with anti-drift can be synchronously output without an additional sensor.

The invention relates to the technical field of medical image processing, in particular to a spatial segmentation radiotherapy ball target automatic generation method based on hexagonal closest packing. The method comprises the following steps: automatically loading and analyzing a medical image and structural data; reconstructing a three-dimensional target area model and calculating features of the three-dimensional target area model A candidate sphere center dot matrix is generated in the target area based on the hexagonal closest packing model, and a two-stage intelligent screening algorithm is adopted to ensure that all points are located in the contour of the target area; directly generating a high-precision sphere section contour in an image pixel coordinate system; and finally, synthesizing a standard DICOM-RT structure file which is strictly associated with the original image. According to the method, the problems of low efficiency, poor spatial distribution, insufficient sphere precision, complex and error-prone data association and the like in the prior art can be solved, so that high efficiency, distribution optimization and precision standardization of sphere target generation are realized.

The invention relates to the field of underground water pollution tracing, in particular to an underground water pollution tracing method for an in-production enterprise. Firstly, obtained original concentration values of different pollution factors are standardized, after standardized concentration values of the different pollution factors are obtained, principal component analysis is carried out, a covariance matrix is calculated, characteristic decomposition is carried out, loads are obtained, and master control pollution factors are screened; then, based on the standardized concentration values of different pollution factors, adopting a pollution source candidate region preliminary screening algorithm to obtain pollution source candidate regions; and finally, on the basis of the pollution source candidate region, through a steady-state weighted convection-dispersion point source joint inversion algorithm, calculating the position coordinates of the final pollution source. The technical problems that dimension disasters are caused by multi-pollutant high-dimensional data, the calculation speed is low, the cost is high, the precision is low due to the fact that a pollution source preliminary positioning search space is too large, tracing weight distribution is unreasonable due to the fact that pollutant importance differences are neglected, and the underground water convection effect is neglected are solved.

The present application belongs to the technical field of hydrological data processing, and particularly relates to a water level data collating method and system and a computer readable storage medium, which comprises the following steps: S1, collecting original water level data of different sources, and performing data preprocessing on the original water level data to obtain standard water level data; S2, judging whether there is an anomaly based on the standard water level data; if yes, proceeding to step S3; if no, proceeding to step S4; S3, performing interpolation repair, and then proceeding to step S4; S4, performing data reduction through dynamic feature point screening threshold control and a feature point screening algorithm, retaining key feature points in the water level data, and obtaining reduced water level data; S5, performing line setting and flow pushing based on the reduced water level data, and obtaining collating results; wherein the collating results comprise water level collating data and flow collating data. Through the whole-process processing of data preprocessing, anomaly identification, interpolation repair, data reduction and line setting and flow pushing, efficient and accurate collation of water level data is realized.

This application discloses a radar signal open-set recognition method based on an adaptive seabird algorithm, belonging to the field of signal recognition technology. It constructs a radar signal sample library by selecting reliable samples through a sample screening algorithm, and then builds an adaptive threshold based on this library to improve the recognition rate and enhance its universality. Simultaneously, an adaptive seabird algorithm is designed to optimize the adaptive threshold weights, constructing an exploration direction factor. Combining spiral optimization search and linear optimization search expands the search range and strengthens the search capability. Adaptive weights and adaptive step sizes that change with the number of iterations are added to balance global and local search capabilities, improving the reliability of the radar signal open-set recognition method. Furthermore, an LSTM network is designed and trained to extract features and obtain embedding vectors, enhancing the network's generalization and adaptability, thus improving the accuracy and universality of the radar signal open-set recognition method and effectively increasing the accuracy of unknown signal recognition.

The invention relates to the technical field of network flow monitoring, and discloses a flow monitoring method, system, equipment and medium for an electric power communication backbone network, and the method comprises the steps: screening out a to-be-monitored service according to the risk score of each network service in the electric power communication backbone network and a service screening algorithm; generating reference data according to the digital twin network, and performing graph signal processing to obtain a graph Laplacian matrix; calculating a distance value between the real-time traffic data and the reference data according to the real-time traffic data and the graph Laplacian matrix; and obtaining an early warning score of each to-be-monitored service according to the distance value and the service weight, and obtaining a total early warning score of the power communication backbone network according to the early warning score of each to-be-monitored service. According to the method, on the basis of service screening, the digital twin network is utilized and graph structure characteristics are combined to carry out deviation evaluation, and the early warning score is optimally designed, so that the accuracy and timeliness of the early warning score are improved, and safe and reliable operation of the electric power communication network is ensured.

The invention relates to the technical field of natural language processing and database intelligent interaction, in particular to a method and system for achieving NL2SQL based on a large model, an index database is accessed, all data table metadata information under the database is automatically collected, and the metadata information comprises but is not limited to a data table name, a field name, a data type and a primary key and foreign key relation; the method has the beneficial effects that the deep understanding of database semantics is realized by automatically collecting and dynamically managing database metadata and combining a multi-level knowledge base construction and retrieval mechanism; based on intention recognition and a multi-table collaborative screening algorithm, a target data table is accurately positioned, and association logic is optimized; and the semantic generalization ability of complex query is improved by utilizing dynamic example matching and a large model process arrangement technology. According to the method, an efficient and extensible NL2SQL system is constructed, the SQL writing threshold of a user is reduced, meanwhile, the method adapts to dynamic changes of a database structure, and the accuracy and maintainability of SQL generation are remarkably improved.