269results about How to "Reduce omissions" patented technology

The invention provides a wind power plant topographic surveying and mapping method and system based on an unmanned aerial vehicle, and relates to the technical field of topographic surveying and mapping. Comprising the following steps: according to topographic characteristics of a wind power plant, adopting a multi-objective optimization model to respectively generate preliminary surveying and mapping routes for a plurality of unmanned aerial vehicles; the multi-objective optimization model takes coverage rate maximization as an optimization objective, and takes cross minimization and path length optimal solution among a plurality of unmanned aerial vehicle routes as constraint conditions; according to the real-time meteorological data, performing dynamic optimization on the preliminary surveying and mapping routes, and generating dynamically optimized surveying and mapping routes for the multiple unmanned aerial vehicles; the multiple unmanned aerial vehicles fly along the dynamically optimized surveying and mapping route, and surveying and mapping data are acquired through the data acquisition equipment. According to the wind power plant terrain complexity and the real-time meteorological data, the surveying and mapping route with the maximum coverage rate is generated for each unmanned aerial vehicle, and blind areas are eliminated through real-time supplementary measurement, so that the completeness of terrain data in the surveying and mapping area is ensured, and the missing of key terrain information is reduced.

The invention provides an unmanned aerial vehicle route layout method and device for complex terrains, equipment and a medium, and relates to the technical field of unmanned aerial vehicle aerial photogrammetry. The method comprises the following steps: carrying out preliminary region division on a terrain region to be surveyed, and determining a plurality of region units; clustering the area units according to topographic observation data to obtain survey sub-areas; determining a survey priority corresponding to each survey sub-region, and matching a basic flight route corresponding to the unmanned aerial vehicle according to the survey priority; and splicing the different types of basic flight routes corresponding to the survey sub-regions, and performing optimization adjustment on the spliced basic flight routes to obtain a flight route of the target unmanned aerial vehicle so as to perform topographic survey on the topographic region to be surveyed. According to the technical scheme, the route planning of the unmanned aerial vehicle can adapt to various types of landform features, and the safety and aerial survey efficiency of the unmanned aerial vehicle are ensured while the integrity and accuracy of aerial survey data are improved.

The invention relates to the technical field of automatic inspection, in particular to an automatic road surface inspection robot control method and equipment, and the method comprises the steps: collecting environment data and robot motion state data through integrating a plurality of sensors, carrying out the preprocessing, carrying out the data fusion through employing a Kalman filtering algorithm, and generating a comprehensive road surface state map; a disease area is accurately identified and positioned through a convolutional neural network, dynamic path planning and polling strategy optimization are performed through a reinforcement learning algorithm, adaptive control of a complex road surface environment is realized through a fuzzy control algorithm, and meanwhile, a targeted road surface maintenance suggestion and an emergency processing scheme are generated according to real-time polling data, so that the real-time polling of a road surface is realized. According to the method, the scientificity and timeliness of road surface maintenance and traffic management are effectively improved, the road surface diseases can be accurately recognized and the inspection path can be optimized in a complex environment, and the road surface inspection efficiency and the intelligent level of road maintenance are remarkably improved.

The invention relates to the technical field of computers, and discloses a method for converting a C + + code into a CUDA-C code, and the method comprises the steps: receiving a C + + source code, carrying out lexical analysis and grammatical analysis, generating an abstract syntax tree, and carrying out semantic analysis to ensure that the source code is correct semantically; analyzing the abstract syntax tree, identifying a data dependency relationship among the calculation tasks, and determining loop statements and conditional statements in the source code; and converting a loop statement and a conditional statement in the source code into a kernel function, a thread block and a thread management code corresponding to the CUDA, and further generating a corresponding compilable source file. According to the method, the abstract syntax tree of the C + + code is analyzed, the parallelism in the abstract syntax tree is analyzed, the code is optimized, the CUDA-C efficient code is generated, then efficient automatic conversion of the code is achieved, and the method has great significance in accelerating program performance and shortening the development period.

The invention provides an automatic software testing method and system based on a visual attention mechanism, and relates to the technical field of automatic testing, and the method comprises the steps: obtaining an initial interface of to-be-tested software, carrying out the preprocessing, inputting an enhanced interface image into an interface detection model, and recognizing control information through the analysis of the enhanced interface image; inputting the control information into a pre-trained attention mechanism model, generating semantic association and context information between controls based on the control information, determining an execution sequence and execution parameters of test actions, sequentially simulating manual test actions, and performing test operation on the controls according to the execution parameters; interface feedback information of the to-be-tested software is obtained, text content in the interface feedback information is extracted based on a character recognition algorithm, semantics corresponding to the text content are determined in combination with a pre-constructed semantic understanding model and compared with a preset expected result, and a test conclusion corresponding to the test operation is generated.

The invention discloses a power transmission unmanned aerial vehicle self-adaptive inspection method and system based on AI auxiliary photographing, and relates to the field of power transmission inspection, and the method comprises the following steps: obtaining historical inspection photos and annotation information, and collecting original position information and actual photographing point information corresponding to the historical inspection photos; training an AI image recognition model by using the historical inspection photos and the annotation information, and training a position deviation correction model by using the historical inspection photos, the original position information and the actual shooting point position information; correcting a shooting point location of the unmanned aerial vehicle by using a position deviation correction model; adjusting the angle and position of the unmanned aerial vehicle during shooting; defects in the image are automatically detected and marked; the system comprises an information acquisition module, a model training module, a position correction module, a shooting adjustment module and a defect detection module. Through unmanned aerial vehicle position correction and multi-angle shooting, the unmanned aerial vehicle inspection image quality is improved.

The invention discloses an AADL model automatic generation method based on a large language model. The method comprises the steps that a safety key field AADL knowledge base is constructed; injecting the constructed safety key field AADL knowledge base into a local large language model through a fine tuning technology to obtain a fine-tuned large language model; plug-in the safety-critical field AADL knowledge base to the fine-tuned large language model to obtain a special large language model for the safety-critical software; inputting cue words into the special large language model of the safety-critical software to obtain an AADL model generation result; meanwhile, the invention provides a prompt framework based on a natural language demand limiting template, and the performance of a large language model in an AADL model automatic generation task is remarkably improved. The measures not only optimize the understanding of the model on AADL specifications and safety requirements, but also enhance the automatic generation capability of the model in complex system architecture description, thereby improving the generation accuracy and practicability of the model while ensuring the system safety and reliability.

The invention discloses a high-frequency partial discharge type identification method and system, and the method employs a multi-channel collection and fine signal processing mode, can comprehensively capture partial discharge signals, reduces the signal missing, and improves the detection accuracy. A strategy of dynamically adjusting a threshold value is adopted, so that the system can adapt to the change of the environment, and the phenomena of false alarm and missing alarm caused by the change of the environment are effectively reduced; the adaptive capacity and robustness of the system under various working conditions are improved by comprehensively considering spectrum characteristics and dynamically adjusting a threshold value; when the system operates, abnormal signals can be recognized in real time, alarm can be automatically triggered, and maintenance personnel can be notified in time, so that the equipment fault risk is reduced, and safe operation of the power system is guaranteed.

The invention discloses an intelligent compilation system and method of a building construction scheme, and the system comprises a data preprocessing module which is used for obtaining historical construction scheme text data of each building engineering project category; the knowledge base construction module is used for constructing a construction scheme knowledge base of each construction engineering project category by establishing a vector index of a construction scheme vector database of each construction engineering project category; the retrieval information extraction module is used for performing keyword extraction on the construction scheme retrieval statement of the construction engineering project input by the user, and mapping and recalling the construction scheme text data of a plurality of corresponding construction engineering projects; and the construction scheme compiling module is used for obtaining a construction scheme compiling basis of the construction engineering project. Associated storage and value utilization of previous engineering construction schemes are achieved, the scheme compiling efficiency and reliability are improved through intelligent generation of the scheme compiling basis, and effective guarantee is provided for the scheme compiling quality.

The invention discloses a digital twin model evolution method and system based on constructional engineering. The invention relates to the technical field of constructional engineering. Related data of the long-distance water conveyance project are collected, wherein the related data comprise BIM model data, oblique photography three-dimensional model data and GIS data; meanwhile, the data are preprocessed, including format conversion, coordinate unification and denoising, so that the quality and consistency of the data are ensured. A three-dimensional BIM model of the engineering facility is constructed based on Autodesk Revit according to a design drawing and collected data, the facility and equipment in the BIM model are coded according to a KKS coding rule, and a coding database is updated; according to the method, the BIM model data, the oblique photography three-dimensional model data, the GIS data and other multi-source data are fused, a refined three-dimensional scene model is constructed, and comprehensive integration of engineering facility information is achieved. Therefore, data sharing and collaboration among different departments and professions are facilitated, and the overall working efficiency is improved.

The invention discloses an agricultural disease and pest dialect speech intelligent recognition method based on a deep learning technology, and the method comprises the steps: combining a Mel-frequency cepstral coefficient with a convolutional neural network, and dividing a whole process into two stages, the pre-training stage comprises the steps of recording and storing a long voice file, extracting the characteristics of voice signals in the file and training a neural network model, and the retraining stage comprises the steps of recording and storing a short voice file, extracting the characteristics of the voice signals in the file, verifying a test result, adjusting model parameters and storing an optimal model; the dialect voice information reported by monitoring personnel in an agricultural field is intelligently recognized by considering accent of people in different regions, so that the recognition accuracy of complex dialect voice signals is effectively improved, and the recognition method is particularly suitable for understanding related terms of agricultural diseases and insect pests.

The present application proposes a standard-based data asset governance method, including extracting link descriptions and link IDs of a data governance process; accessing a standard library that the data asset process depends on to obtain standard file descriptions and standard file IDs that constrain the data governance process; performing attention analysis on link descriptions and standard file representations to obtain a standard compliance matching graph; constructing a standard metadata model based on the standard compliance matching graph, and encoding the standard metadata model to obtain a standard mapping table to construct a standard data governance rule engine; assigning roles to a data-based governance organizational structure, and establishing a workflow control model between the assigned roles and link descriptions; establishing an object collaborative mapping framework between the workflow control model and the standard data governance rule engine to perform standard data asset governance tasks based on the object collaborative mapping framework.

The invention discloses wood floor plain plate surface defect intelligent control repairing and shaping equipment and method.The wood floor plain plate surface defect intelligent control repairing and shaping equipment comprises a supporting frame, a first U-shaped frame is fixedly installed on the upper surface of the supporting frame, multiple sets of supporting wheels are rotatably installed in the first U-shaped frame, a transverse rod is fixedly installed on the upper surface of the supporting frame, and two sets of transmission mechanisms are slidably installed on the outer surface of the transverse rod; an overhead rod is fixedly installed at the other end of the upper surface of the supporting frame and is arranged at the upper end of the periphery of the transmission mechanism in an overhead mode, and a repairing mechanism is fixedly installed on the upper surface of the overhead rod. Through the design of the transmission mechanism and the repairing mechanism, the flatness of the surface of the plain plate can be automatically detected in the plain plate conveying process, the part needing to be repaired can be automatically filled with a repairing material, and pits or cracks filled with the repairing material can be trimmed and stricken after the repairing material is filled; and the flatness of the surface of the plain board can be maintained.

The invention discloses a method for inverting the Cu content of agricultural land soil by using multispectral data. The method comprises the following steps: acquiring Sentinel-2 satellite Level-2A remote sensing image data; the method comprises the following steps: constructing a decision tree by using a soil pH value, humidity and organic matter content, and dividing samples into different range groups through the decision tree; calculating the importance of the characteristic variables by adopting a continuous projection algorithm SPA and a Boruta algorithm, and finding the most suitable spectral index form; a gradient boosting tree XGBoost algorithm is adopted as an inversion model of the Cu content in the soil, and inversion models of a pH interval, a humidity interval and the organic matter content are established in combination with an Optuna framework; and classifying through the decision tree, and inputting the spectral index of the soil to be detected into the inversion model with good prediction performance to obtain a prediction value. According to the method, the accuracy of inversion of the content of the heavy metal Cu in the soil is improved by means of a comprehensive resampling strategy, a multi-dimensional spectrum transformation form, classified data, classified modeling and the like.

The invention relates to the technical field of artificial intelligence and the field of financial science and technology, and discloses a negative public opinion information extraction method, which comprises the following steps of: forming a preliminary data set by acquiring public opinion information data related to a target subject; defining an information extraction structure, labeling the public opinion data set, and generating a training data set; performing multi-round iterative training on the basic pre-training model based on the training data set to generate a negative public opinion information extraction model; and constructing a processing framework based on the model, inputting the to-be-processed public opinion data into the processing framework, automatically identifying negative public opinion information, and generating structured entity, relationship and event data. According to the method, by obtaining the public opinion information data related to the target subject, defining and labeling the information extraction structure and combining the pre-training model of multi-round iterative training, key entities, relationships and events in the public opinion data can be accurately recognized, and automatic extraction of negative public opinion information is achieved. The accuracy and comprehensiveness of negative public opinion information extraction can be effectively improved.

The invention discloses an active infrared thermal imaging wind power blade detection device applied to an unmanned aerial vehicle, and the device comprises a carrying ring which is detachably connected with the unmanned aerial vehicle; the three adjusting rods are circumferentially arranged at equal intervals and are arranged in a sliding manner relative to the carrying ring; and the carrying disc is arranged among the three adjusting rods and is used for fixedly loading the infrared thermal imaging equipment. According to the method, the virtual midpoint formed among the three contact points in contact with the wind power blade is set, the infrared thermal imaging equipment always corresponds to the virtual midpoint, the three moving contact points correspondingly move by means of the special radian design of the wind power blade, and therefore the formed virtual center correspondingly moves; and the carrying disc loaded with the infrared thermal imaging equipment is changed through conduction of the adjusting rod, so that the carrying disc correspondingly deviates to form angle self-adaptive adjustment, the infrared thermal imaging equipment loaded on the unmanned aerial vehicle can adjust the self-detection angle in real time along with the special radian on the wind power blade during detection, and missing of defects is reduced.

The invention discloses a Java-based intelligent document generation method, and belongs to the technical field of intelligent generation, and the method comprises the steps: S1, constructing a deep learning model: constructing a natural language processing model based on large-scale legal text data set training by using a deep learning framework integrated by a Java platform, the natural language processing model is used for understanding complex legal concepts, terms and logic relations, in the method, deep law understanding ability is achieved, deep understanding of legal texts is achieved through application of the deep learning model, a shallow processing mode of traditional template filling is exceeded, efficiency is improved, the legal document preparation time is greatly shortened, and the method is suitable for popularization and application. The workload of legal professionals is reduced, the accuracy is enhanced, document errors and omissions are reduced, the specialty and compliance of legal documents are ensured, standardization is promoted, the standardized process of legal document writing is pushed, the consistency and quality of legal services are improved, personalized services are achieved, and the special requirements of specific clients or cases are met.

The invention relates to a cloud network resource tree auditing method and device. The method comprises the following steps: receiving resource tree data; abstracting the resource tree data into a resource tree routing graph according to a preset verification rule; and traversing all nodes and paths in the resource tree routing graph based on a depth-first search and backtracking algorithm. According to the method, all nodes and paths can be comprehensively and accurately audited, the risks of omission and errors are reduced, and the subsequent audit efficiency is improved.

The invention discloses an intention-based server management method and device, a medium and a product, and relates to the field of servers. The method comprises the following steps: receiving server management intention information sent by an administrator; determining target performance data of a business server according to the server management intention information; generating a server management strategy based on the target performance data; adjusting resource configuration, application program configuration and / or service tasks of the service server according to the server management strategy; obtaining the adjusted real-time performance data of the business server; and when the real-time performance data is matched with the target performance data, server management task completion information is returned to the administrator. The server configuration is automatically adjusted to meet the performance requirement by accurately matching the management intention of the administrator with the target performance data, the management difficulty of the server is reduced, the task completion is confirmed to the administrator after the performance reaches the standard, and the efficiency and the accuracy of server management are improved.

The invention relates to the technical field of AI large models, in particular to a large model resume screening system and method for the human industry, and the system consists of a working post analysis module, a candidate resume analysis module, a matching degree analysis module and a personal information module. The working post analysis module is used for deeply analyzing and extracting key requirements of working posts; the candidate resume analysis module is used for comprehensively analyzing the uploaded candidate resumes and extracting key information; the matching degree analysis module is used for carrying out accurate matching degree analysis in combination with working post requirements and candidate information and giving a comprehensive ranking; the personal information module is used for the user to manage personal information and account setting; the large model resume screening system and method for the human industry have the beneficial effects that efficient screening and processing of a large number of resumes are achieved through an automation technology, so that the working pressure of a human resource department is remarkably reduced, and the screening efficiency is greatly improved.

The invention relates to the technical field of time length detection, and discloses a news simulcasting time length detection alarm method based on voice recognition, which comprises the following steps: S1, noise reduction: integrating an advanced digital signal processing technology and a professional noise reduction algorithm to form a refined processing system adaptive to'news simulcasting 'audio, according to the system, aiming at collected useless components such as environment noise and equipment noise, noise characteristics are captured through a multi-dimensional signal analysis model, an effective information core identifier is defined, a differentiated characteristic database of signals and noise is constructed, and a technician sets scientific noise reduction parameters according to the differentiated characteristic database. And accurate noise identification and stripping: integrating an advanced digital signal processing technology and a professional noise reduction algorithm, capturing noise characteristics through a multi-dimensional signal analysis model, accurately stripping environmental noise (such as studio echo and external interference sound) and equipment noise (such as sound recording equipment floor noise and transmission link electromagnetic interference), and simultaneously retaining the original texture of effective audio.

The invention provides an airport engineering BIM (Building Information Modeling) forward design method based on a general data environment, which belongs to the technical field of digital construction of airport facilities and comprises the following steps of: customizing a design workspace into the general data environment; drawing a design object in the design work space, and generating geometric information of a design element object; calling design element information to associate the design element information to the design element object, wherein the design element information is stored in the general data environment; judging whether abnormal information exists in the design object or not according to a design standard; and if the abnormal information exists, positioning the abnormal information, modifying the geometric information according to the abnormal information and the positioning of the abnormal information, and / or modifying the design element information and updating a general data environment. The invention further provides an airport engineering BIM forward design device based on the general data environment, electronic equipment and a storage medium. By the adoption of the technical scheme, the technical problems that in the prior art, airport engineering BIM design is large in workload and low in efficiency can be solved.

The invention provides a tumor medical image classification method of zero sample evolution NAS based on double-index collaborative evaluation, which comprises the following steps: collecting tumor medical image data, and constructing a data set containing a tumor focus image and a normal tissue image; constructing an extended search space based on a cell structure, wherein the search space comprises a basic operation set, the cell structure and a network overall structure; steady-state evolution algorithm parameters are set, and steady-state evolution initialization is carried out to obtain an initial candidate architecture; taking a double-index comprehensive score calculated by the information rate and the FIM stability as a comprehensive index for evaluating the current candidate architecture, updating the candidate architecture through a steady-state evolutionary algorithm based on a dynamic optimization mechanism until the maximum evolutionary algebra is reached, and obtaining an optimal architecture; and training the optimal architecture by using the data set, and carrying out tumor medical image classification by using the trained optimal architecture. According to the method, the dependence on the annotated data is reduced, the consumption of computing resources is reduced, and meanwhile, the diagnosis efficiency and accuracy are improved.

The invention relates to the technical field of acrylonitrile catalyst production, in particular to a pulping device and a pulping process for acrylonitrile catalyst production, the pulping device comprises a homogenizing mechanism, the homogenizing mechanism comprises a tank body and further comprises a sealing cover arranged above the tank body and used for feeding, a stirring pulping assembly used for stirring slurry is arranged above the sealing cover, and the stirring pulping assembly is arranged above the tank body and used for stirring the slurry. The slurry extrusion device comprises a tank body and an extrusion box arranged below the tank body, an extrusion plate used for pushing slurry and a driving assembly used for driving the extrusion plate are arranged in the extrusion box, and the extrusion plate can extrude the slurry in the extrusion box; the extruded slurry can be discharged into the tank body through the first guide pipeline to realize circulating conveying of the slurry, so that one-way circulating operation by adopting a circulating pump is avoided, the maintenance frequency of each circulating part is reduced, synchronous circulation of the slurry on the left side and the right side of the tank body can be realized in a linkage manner, and the production efficiency is improved. And compared with a traditional circulating pump, one-way circulation is more efficient.

The invention relates to the technical field of crude lead refining, in particular to an energy-saving crude lead continuous refining furnace and a refining method.The energy-saving crude lead continuous refining furnace comprises a mixing mechanism used for conducting high-temperature stirring on molten lead so as to promote reaction of internal impurities; the mixing mechanism comprises a reaction tank, a stirring assembly arranged in the middle of the reaction tank and an adding assembly arranged on the periphery of the reaction tank; the reaction mechanism is arranged at the bottom of the reaction tank and is used for promoting full contact of oxygen and impurities and improving the impurity removal effect; the filtering mechanism is arranged on the reaction mechanism and is used for filtering solid impurities generated after the reaction; the feeding mechanisms are arranged at the upper end and the lower end of the reaction tank and used for controlling input of lead powder and output of lead liquid. The technical problems of poor tin impurity removal effect and low efficiency are solved.

The invention is suitable for the technical field of identity authentication systems, and provides an identity authentication system based on multi-dimensional biological feature perception, which comprises a mobile terminal, a cloud management platform, a network interconnection module and a multi-dimensional authentication module, the multi-dimensional authentication module comprises a main chip, an infrared detection module, a password acquisition module, a fingerprint acquisition module, a voiceprint acquisition module, a binocular living body detection acquisition module, a palm print acquisition module, a vein acquisition module and a face acquisition module. According to the identity authentication system based on multi-dimensional biological feature perception, the face acquisition module performs face acquisition by using an infrared camera and an RGB camera, the voiceprint acquisition module performs voiceprint acquisition by using a microphone, the password acquisition module performs password acquisition by using a keyboard, and the fingerprint acquisition module performs fingerprint acquisition by using a fingerprint acquisition instrument; according to the technical scheme of the multi-dimensional authentication hardware module, various biological feature recognition technologies and a dynamic password authentication function are integrated, so that a safer and more flexible authentication mode is realized.

The invention provides a man-machine collaborative program repairing method based on a large language model, relates to the technical field of automatic program repairing, and remarkably improves the accuracy and success rate of program repairing. According to the method, a large language model is guided through preliminary analysis of manual teaching, errors in a program can be more accurately positioned and repaired by combining a repairing process of multiple iterations and more information introduced step by step, misjudgment and omission are reduced, and the program repairing efficiency is greatly improved. Compared with a traditional method, blind exploration of a large language model on complex problems is avoided through a man-machine cooperation mode, time and computing resources are saved, and adaptability of program repair is enhanced. According to the method, program defects of various types and complexity can be handled, and simple grammar errors or complex logic errors can be effectively handled through a step-by-step deep repair process.

The invention relates to the technical field of intelligent medical evaluation, in particular to an acute and critical disease auxiliary evaluation system based on machine learning, and the system comprises a data integration and feature extraction module which collects the medical data of an acute and critical disease patient, converts the medical data into a time sequence, analyzes the medical data change information in the time sequence, and outputs the medical data change information; and taking the medical data change information as medical indexes associated with the illness state of the patient, screening different medical indexes, and generating a key feature data set of the current critical patient according to a screening result. According to the method, the medical data is collected in real time and converted into the time sequence, the missing data is filled, the dynamic change of the medical indexes is analyzed, and the key feature data set of the patient can be effectively extracted. And more intuitive and meticulous abnormal data analysis is realized by combining the distribution state of the extreme data points in the time sequence and the record of the change interval of the extreme data points.

The present invention relates to the field of data processing technology, and specifically to an efficient data processing system and method based on multi-source data comparison, in which a self-checking associated data fusion analysis module performs self-checking on the configuration file of each data comparison party based on the data table configuration area, generates a data comparison self-checking associated data project set, and performs fusion determination processing on the elements in the data comparison self-checking associated data project set. The present invention supports flexible configuration of multiple association conditions and data formats to meet the comparison requirements in different scenarios; at the same time, the present invention realizes self-checking of the configuration file of the data comparison party during the comparison process, reducing the impact of interference data in the configuration file on subsequent comparison operations; and introduces fusion determination processing operations on data at different stages in the comparison process, realizing dynamic optimization and screening of data during the comparison process, and realizing effective management of comparison data.

The invention discloses an intelligent marketing system and method based on a large model, and the method comprises the steps: automatically replying a newest message in a preset time through a self-adaptive chat large model, obtaining the emergency degree of a current customer session according to the recorded message number and message keywords, and obtaining the current customer session according to the emergency degree; the session with the highest emergency degree is screened out to send emergency early warning to the staff; a client database of the current emergency client is connected according to the emergency early warning, and the intention degree of the current emergency client is obtained by using an intention evaluation large model; matching corresponding activities in a marketing activity database according to the intention degree of the current emergency customer, and directionally recommending the corresponding activities to the current emergency customer; and according to the customer levels and the car insurance expiration time in the customer database, acquiring customer IDs of a plurality of customers to be subjected to insurance renewal, and sending an insurance renewal message. The invention relates to the technical field of intelligent insurance marketing, and solves the technical problems that in an existing marketing method, intentional customers are difficult to screen, and stock customer management is incomplete.