1701 results about "Automatic processing" patented technology

The invention discloses an unknown pollutant non-target identification method and system based on mass spectrum and a generative model, and is applied to the technical field of environmental monitoring and analytical chemistry. The method comprises the following steps: collecting mass spectrum data of a water body sample to be detected; preprocessing the original mass spectrum data, and outputting standardized features; inputting the standardized features into a pre-trained generative model to generate a plurality of candidate molecular formulas; using chemical and physical constraints to eliminate candidate molecular formulas which do not conform to rules; executing a rule-driven algorithm to obtain candidate pollutant molecular structures; carrying out comprehensive scoring and sorting on candidate pollutant molecular structures through chemical prior and environmental prior; and semi-quantitative or relatively quantitative concentration determination is carried out. According to the method, a rule-driven expert system and a data-driven generation model are combined, unknown pollutants which do not exist in a standard library can be effectively recognized and analyzed, and full-process automatic processing from original mass spectrum data to pollutant structures and concentrations is achieved.

The invention provides an automatic processing method for real-time observation data of an ocean station, and belongs to the technical field of ocean observation data processing. A wavelet packet decomposition multi-scale noise separation algorithm is established to distinguish environmental noise and real signals, dual-sensor redundancy configuration is combined with Bayesian inference to identify sensor drift, and a calibration coefficient is updated in real time through a recursive least square method. A one-dimensional time sequence is mapped to a high-dimensional phase space by utilizing a phase space reconstruction algorithm to realize high-precision prediction of a chaotic signal, a hierarchical data storage architecture is established, and a data migration strategy is iteratively optimized through a hierarchical correlation degree function; the technical problem that time synchronization signals are difficult to reconstruct accurately according to asynchronous sampling data of multiple sensors of an ocean station is solved.

The invention relates to the technical field of intelligent aquaculture and automatic processing, in particular to an appearance characteristic-based hippocampus intelligent grading and pond-dividing culture method and system, and the method comprises the following steps: S1, collecting sparse visual data and multi-source physiological data of hippocampus; s2, generating a three-dimensional digital twinborn model based on the sparse visual data; calculating a growth state grading index based on the three-dimensional digital twinborn model; s3, calculating a physiological stress index based on the multi-source physiological data; s4, comparing the physiological stress index calculated in real time with a preset safety stress threshold value and a critical stress threshold value, and generating a hierarchical adaptive correction strategy; s5, according to a grading self-adaptive correction strategy, controlling a flexible mechanical arm to execute fishing and pond separation operation; according to the method, the appearance and physiological data of the hippocampus are synchronously collected in a non-contact mode, the technical problems that the real condition of the hippocampus cannot be evaluated and damage is possibly caused due to target stress response caused by traditional physical intervention are solved, and the authenticity and effectiveness of original data are guaranteed.

The invention discloses an integrated machining device suitable for a large marine propeller, which comprises a machining adjusting assembly, the machining adjusting assembly is composed of an X-axis moving mechanism, a Y-axis moving mechanism and a Z-axis moving mechanism, one side of the Z-axis moving mechanism is fixedly provided with a rotating mechanism, one end of the rotating mechanism is fixedly connected with a cutting assembly, and the other end of the rotating mechanism is fixedly connected with a cutter; according to the large marine propeller integrated machining device with the automatic machining function and the self-adaptive clamping function, through the integrated multi-axis linkage machining adjusting assembly and the three-dimensional scanner, automatic path planning can be conducted, and automatic operation is achieved; therefore, the dependence on advanced technicians is greatly reduced, the machining efficiency and the product consistency are remarkably improved, and meanwhile, through the collaborative design of the rotatable three-jaw chuck and the center supporting mechanism, simultaneous reliable supporting from the interior and the exterior of the workpiece can be automatically achieved during clamping.

The invention discloses a method for dynamically monitoring and automatically processing abnormity of an entrance and an exit of a parking lot, relates to the technical field of intelligent parking lot management, and aims to solve the problems that existing unattended parking lot entrance and exit management depends on manpower, abnormity processing is passive, and the misjudgment rate is high. The method is based on an information acquisition and execution layer-edge processing layer-cloud platform three-layer architecture, the core realizes high-precision scene understanding through a multi-algorithm fused visual perception module, multi-modal data weighted fusion is combined with a ground induction coil, a radar and the like, and the misjudgment rate is reduced; a sensing result is converted into an automatic processing action through a configurable intelligent rule engine; and meanwhile, the cloud platform stores passing data and an evidence chain, optimizes an AI model through incremental training and returns the AI model to an edge layer, so that closed-loop evolution is realized.

The invention discloses a fault co-seismic sliding surface inversion method and system based on Beidou and artificial intelligence. The method comprises the steps of collecting Beidou data and seismic waveform data of a target area in real time, and performing preprocessing to extract co-seismic displacement and waveform features; fusing the Beidou deformation features and the seismic wave features to form a multi-modal feature vector; a fault prediction model is constructed based on a graph neural network, forward modeling and historical earthquake example data training are utilized, and multi-modal features are input to obtain preliminary fault sliding distribution prediction; rapid optimization under physical constraint is carried out through the elastic dislocation model, and a final fault sliding model conforming to the geophysical law is obtained; finally, uncertainty quantification is carried out, and a visual product of the dynamic process including sliding distribution, seismic moments and fault deformation is generated. According to the system, full-process automatic processing is achieved through cooperation of all the units, the inversion speed, precision and physical credibility are improved, and reliable support is provided for earthquake emergency response and disaster assessment.

The invention relates to a constraint condition and multi-objective optimization fused investment attraction target enterprise screening method. The method comprises the steps of obtaining target industry field information and generating an initial target enterprise pool; obtaining regional resource constraint information and enterprise multi-dimensional information, and inputting the information into a constraint discrimination model to obtain a candidate enterprise set; inputting enterprise multi-dimensional information associated with the candidate enterprise set into the tendency evaluation model to obtain an enterprise comprehensive score set; obtaining optimization target information, and constructing a multi-target optimization function; obtaining optimization condition information, matching a corresponding multi-objective optimization algorithm and adjusting parameters; solving the multi-objective optimization function, generating an enterprise screening strategy scheme set, and generating an enterprise screening decision report; in conclusion, by fusing the regional resource constraint condition and the multi-target optimization mechanism, the automatic processing and objective evaluation of the enterprise screening process are realized, and the method has the advantage of improving the efficiency and objectivity of screening the investment attracting target enterprises.

The invention provides a simulation test key factor screening-oriented method and system and a computer program product. The method comprises the following steps: generating a structured configuration file; constructing a supervised learning data set based on the structured configuration file; based on the supervised learning data set, training a machine learning classification model to obtain a current key factor set; and repeating the steps, judging whether the current key factor set is converged or not, and if the current key factor set is converged, stopping simulation and outputting the current key factor set of the last round as a final key factor. According to the technical scheme of the invention, a high-dimensional, nonlinear and high-coupling complex system can be automatically processed; key factors are objectively recognized through machine learning, a small-batch iteration verification mechanism is adopted, and the screening accuracy and efficiency are improved while the number of times of simulation is remarkably reduced.

The invention discloses an online order full-process automatic processing system and method. The system comprises an order state analysis module, a cross-platform collaborative adaptation module, a resource scheduling planning module, an environment load evaluation module and a task scheduling optimization module. According to the invention, by analyzing the trend of the key time sequence change of the order life cycle, the circulation bottleneck can be identified and the time section exceeding the threshold value can be generated, so that the task sequence is matched with the system load, the scheduling coordination and the response precision are enhanced, the execution capability is dynamically compared to form the optimal distribution instruction, and the cooperation efficiency and the transmission continuity are improved. Based on a utilization rate change identification trend, resource distribution is balanced, scheduling flexibility and controllability are enhanced, resource and energy consumption cooperative adjustment is realized through environment load evaluation, operation stability and environment adaptability are improved, high efficiency and continuous optimization of an order flow are realized, and processing capability and operation toughness of a system under high concurrency are enhanced.

The invention discloses a heterogeneous document structured data extraction system and method based on multi-modal fusion, and the method comprises the following steps: S1, receiving a heterogeneous document, and carrying out the preprocessing; s2, extracting visual and semantic modal information based on the visual backbone network and an OCR module, and fusing spatial coordinates, text content and layout features; s3, receiving a dynamic target mode Schema, executing field-level semantic matching, and calculating semantic similarity; s4, performing consistency verification, verifying and filling the field values, and correcting the associated fields; s5, converting the format into a data file in a specified format, and reserving fields to be mapped with an original document semantic block; s6, automatically switching a cloud mode and a local mode according to a deployment environment; and S7, outputting the data file of the target field. According to the method, high-precision and low-delay structured data extraction of the heterogeneous format document can be realized, and the automatic processing efficiency and the data credibility are improved.

The invention relates to the technical field of big data processing, in particular to a hydrological information forecast data collection automatic processing method, which comprises the steps of multi-source data automatic acquisition and access, data quality intelligent diagnosis processing and abnormity early warning, multi-index comprehensive drought evaluation model construction and drought trend intelligent prediction. GIS spatial analysis and visual display are carried out, and drought evolution is dynamically reflected; and user-defined configuration and adaptive learning are carried out. The equipment state can be displayed, and related personnel can be prompted to maintain the observation station in time; existing hydrological data of the hydrological bureau are fully applied, rainfall, river flow, soil moisture content and other single items are normatively determined to determine the drought level, and meanwhile, according to multiple indexes, comprehensive drought judgment is performed according to the proportion, and based on the GIS technology, an interpolation method and a proximity association method are utilized to determine a Xinjiang whole administrative division plane drought map; and according to the analysis data, automatically sorting out soil moisture content brief report materials.

The invention discloses an AI automatic editing method and related equipment, and the method comprises the steps: obtaining a video prototype template selected by a user, prompt information inputted by the user, and original materials uploaded by the user through a user interaction interface, and calling a language large model to generate a structured video script; performing association degree matching on the structured script and the original material through a target detection model, and screening the original material according to a matching result and a quality scoring model to obtain an original video clip; performing background music matching according to the video script to obtain background music, generating voice dubbing and a flower-character chartlet according to the video script, generating video subtitles according to the voice dubbing, performing time axis alignment on each video media element, and synthesizing into a finished video. According to the embodiment of the invention, full-process automatic processing from script generation to video synthesis can be realized, and a high-quality finished video meeting user requirements can be efficiently output. The method can be widely applied to the technical field of automatic editing.

The invention relates to the technical field of chicken cutting, in particular to an automatic processing method and processing equipment for cutting carcasses of iced and fresh yellow-feather chickens. Comprising a rack, a detection module, a material kicking module, a traction module, a tail cutting module, a head cutting module, a wing spreading module, a wing cutting module, a half cutting module, a leg cutting module and a leg unloading module. The traction module is arranged on the rack and provided with a driving unit arranged on the rack in a surrounding mode and a plurality of mounting frames vertically arranged on the driving unit at equal intervals. The detection module, the material kicking module, the tail cutting module, the head cutting module, the wing spreading module, the wing cutting module, the half cutting module, the leg cutting module and the leg unloading module are sequentially and fixedly arranged on the rack at equal intervals in the driving direction of the driving unit. All parts of the yellow feather chicken can be fully automatically cut, cutting is uniform, and the cutting efficiency is high.

The invention provides a method and device for extracting report data based on a large model technology, and relates to the field of batch data processing, and the method comprises the steps: carrying out the intelligent table splitting processing of obtained report image data through a pre-constructed intelligent report prompt word project, and obtaining an effective target report; carrying out metadata dynamic extraction processing on the effective target report by utilizing a pre-constructed data extraction cue word project to obtain a report label; performing multi-dimensional data integration processing on the effective target report by utilizing a pre-constructed data integration prompt word project and the report label to obtain a report data dictionary; and performing subject semantic mapping on the effective target report according to the report data dictionary to obtain a required data report. According to the method, a complete automatic processing flow can be constructed, and intelligent report splitting, metadata dynamic extraction, multi-dimensional data integration, subject semantic mapping and the like are realized by combining an optical symbol recognition technology with a large model technology.

The invention provides a river sediment physical habitat evolution identification method, device and system and a medium. The method comprises the following steps: acquiring a multi-temporal remote sensing image and hydrological data (flow Q, water level Zw and slope S), screening and other hydrological condition image pairs; extracting a water surface range, and calculating the average width B of the main groove; deducing the average water depth h by using a Manning formula, and calculating the riverbed elevation zbed by combining the Zw; the difference value delta zbed of zbed in different periods is calculated, and the substrate state is judged according to the difference value delta zbed and a threshold value epsilon; and performing segment processing along the center line to output a spatial distribution result. On-site measurement is not needed by relying on conventional data, and consumption is reduced; water level interference is eliminated through equal hydrological condition matching, and comparability is ensured; water depth inversion and differential analysis directly reflect scour deposition and quantitatively reveal rules; long-distance automatic processing improves space-time coverage capability and precision, and provides a basis for river regulation, ecological restoration and drainage basin management.

The invention provides an electric power operation and maintenance work ticket intelligent collaborative auditing system based on a large model, and relates to the technical field of data acquisition management, and the system comprises a data acquisition module which is used for collecting related influence parameters of a work ticket; the intelligent model processing module is used for constructing an influence mathematical model and outputting an influence coefficient; the execution difficulty quantification module is used for collecting resource data required when the to-be-processed power operation and maintenance work ticket is executed, and obtaining an execution difficulty index; and the auditing output module is used for setting an auditing judgment cardinal number and judging whether manual auditing intervention is needed or not. According to the invention, the accuracy and timeliness of information are ensured through real-time data acquisition and automatic processing, and manual errors and delay are reduced; the auditing efficiency and reliability are greatly improved, the adaptive auditing decision is triggered in the rule engine, so that resource allocation is optimized, whether the work order is executed smoothly or not can be considered more fully, the work order execution smoothness is improved, and the task completion rate is increased.

The invention relates to a traditional Chinese medicine syndrome intelligent identification method and system based on multi-modal data fusion, and belongs to the technical field of medical systems, and the method comprises the following steps: S1, multi-modal traditional Chinese medicine data acquisition: obtaining at least two different types of original data related to traditional Chinese medicine; s2, performing cleaning, denoising, normalization and data alignment processing on the various types of original data acquired in the step S1 to obtain standardized multi-modal data; s3, multi-modal data fusion is carried out, and a feature layer fusion or decision-making layer fusion mode is adopted; s4, identification model training: matching the fusion feature vector with a corresponding traditional Chinese medicine syndrome label, and inputting the matching result into a preset deep learning model for training to obtain a traditional Chinese medicine syndrome identification model; and S5, intelligently identifying the traditional Chinese medicine syndromes, and outputting a corresponding traditional Chinese medicine syndrome identification result. According to the method, full-process automatic processing and closed-loop optimization are realized, and the dependence on the professional level of operators is greatly reduced.

The invention discloses a system for generating structured data based on natural language processing to drive UI dynamic rendering. The system comprises a voice acquisition and recognition module, a natural language processing module, a UI dynamic rendering driving module, a control logic automatic binding module and a rendering execution module. User voice or text instructions are automatically analyzed into structured JSON data through natural language processing, Jetpack Compose is driven to dynamically generate UI components, service logic is bound, zero-code interface construction is achieved, in addition, the system is combined with a local AI model, a factory mode and a reflection mechanism, multi-end adaptation, bidirectional data binding and event automatic processing are supported, and the system is suitable for large-scale popularization and application. According to the method, the development threshold is remarkably reduced, the iteration efficiency is improved, the method is particularly suitable for scenes such as smart homes and vehicle-mounted central control which need to quickly customize UIs, and meanwhile offline availability and cross-device consistency are guaranteed.

The invention relates to the technical field of artificial intelligence, and particularly provides a heterogeneous data preprocessing method, system and device and a storage medium, and the method comprises the steps: obtaining multi-source heterogeneous original data, and analyzing the multi-source heterogeneous original data into intermediate format sample data; calling a large language model to generate a field semantic tag; converting the original field into a standard field in a standard field library through a field mapping rule; cleaning abnormal values by using a machine learning model to obtain a primary sample data set; performing semantic analysis on the unstructured text fields to generate structured feature vectors, and adding the structured feature vectors into a data set; and finally, performing feature derivation on the structured field according to the data type and the semantic tag, and outputting a final data set. According to the method, automatic processing from the original data to the training ready data set is realized, and the data preprocessing efficiency, the automation degree and the reliability are remarkably improved.

The invention provides a rapid broadband signal detection and identification method and device based on a time-frequency graph, and the method comprises the steps: converting a broadband signal into a time-frequency graph, and inputting the time-frequency graph into a YOLO-X network for signal time-frequency positioning after the time-frequency graph is preprocessed; constructing a complete signal instance containing a Welch power spectrum based on a positioning result; outputting signal category and confidence evaluation through two-stage feature analysis; and finally, realizing automatic processing or expert secondary discrimination according to a confidence threshold. According to the method, deep learning and signal processing technologies are fused, and the signal detection speed, the recognition accuracy and the decision reliability in a complex electromagnetic environment are remarkably improved.

The invention discloses a ton bag feeding device and method, belongs to the technical field of ton bag feeding, and solves the problems that an existing device is low in intelligence, high in manual dependence degree and low in feeding precision and efficiency. The device comprises a supporting frame, a feeding mechanism, a clamping mechanism, an AI visual monitoring module and a master control module. The supporting frame is provided with a camera and an electric conveying frame, the feeding mechanism comprises a feeding assembly with a telescopic pipe and a stirring assembly, the clamping mechanism comprises a liftable adsorption clamping assembly, the AI visual monitoring module is connected with the camera, and intelligent monitoring of the position, the in-place state, the bagging state and the bag opening falling state of the ton bag is achieved. And the master control module is linked with each mechanism to complete automatic operation. According to the method, unattended operation is achieved through full-process closed-loop operation of equipment initialization, ton bag feeding, AI visual monitoring and positioning, clamping mechanism adjustment, adsorption fixing, bagging monitoring, clamping fixing, real-time feeding monitoring, automatic abnormity processing, mechanism resetting and ton bag discharging.

The utility model relates to poultry automatic processing equipment technical field, including compound manipulator who can move laterally, compound manipulator includes the snatch claw who can snatch / loosen poultry gizzard, the esophagus connected on poultry gizzard can be suspended with poultry gizzard moves, the snatch claw below is equipped with oiling unit and cutting unit along poultry gizzard conveying direction in proper order, oiling unit includes at least two groups of oiling mechanism who sets in proper order along poultry gizzard moving direction, two groups of oiling mechanism all include two scrapers who can clamp / loosen esophagus and set up oppositely, and the transverse interval of two groups of oiling mechanism scraper is no more than the length of the esophagus to be oiled, cutting unit includes the cutting knife who cuts open esophagus, the esophagus under the action of oiling unit, receives segmented type oiling effect, and at least can carry out twice oiling operation continuously, protects the integrity of esophagus and improves the oiling effect, the whole processing of esophagus, simple operation, reduces the assembly, debugging and control difficulty, improves the efficiency.

The invention relates to the technical field of automatic machining equipment, in particular to bending equipment which comprises a rack, a first bending unit and a second bending unit, the first bending unit is arranged on the rack, the first bending unit is provided with at least one first bending part, and the first bending part is arranged in a lifting mode in the first direction; the jacking mechanism is configured to receive the flexible structure and jack the first bending position of the flexible structure, so that the flexible structure forms a first bending structure at the first bending position; the second bending unit is arranged on the rack, the second bending unit is provided with at least one second bending part, and the second bending part is arranged in a translation mode in the second direction and is configured to receive the flexible structure from the first bending unit and push the flexible structure to be close to the position of the second bending position; and the flexible structure forms a second bending structure at the second bending position. The main purpose of the invention is to provide a bending device for realizing secondary bending of a flexible structure.

The invention discloses a medical business system processing method based on multi-agent cooperation, a medium and equipment, and belongs to the technical field of medical informatization. In the method, a task analysis agent receives a medical service request, calls a large language model to analyze a user intention, and generates a standardized task description; the routing scheduling agent decomposes the task and distributes the task to the corresponding service execution agent according to the task type and the service rule; the plurality of service execution agents process respective responsible subtasks in parallel, and call corresponding medical information system interfaces to complete specific service operation; and the result summarizing agent collects the processing results of the execution agents, and the processing results are integrated to generate a final service response. According to the invention, through specialized division and cooperation of multiple agents, automatic processing of complex medical services is realized, and the processing efficiency and the intelligent level of a medical information system can be significantly improved.

The invention relates to a self-adaptive mixing precision quantification method and device, equipment and a medium, and the method comprises the steps: carrying out the comprehensive sorting through the product of the cosine similarity difference value of adjacent layers and the sensitivity weight of each layer, so as to guarantee that bottleneck layers which are liable to be influenced by quantification and are crucial to the final precision can be accurately recognized; therefore, precise positioning of a protection target is realized, an iterative optimization loop is introduced, an optimal solution meeting a preset performance target can be spontaneously found finally by continuously evaluating a time-precision balance point of an overall model and automatically adjusting configuration, and a suboptimal result caused by improper primary configuration is avoided; and the input of the user is simplified into a visual final performance target, and the complicated layer sorting and selection process is automatically processed in the system, so that the use threshold of the technology is reduced.

The invention relates to the technical field of digitization systems, and particularly discloses an intelligent AI-driven archive digitization full-process processing system, which comprises a physical digitization module, an AI agent collaborative network and a digital resource management module which work cooperatively in sequence, and realizes automatic processing from an entity archive to a structured digital knowledge base; the physical digitization module is configured to perform high-fidelity scanning or shooting on the entity archive to generate an original digital image set; the AI agent collaborative network is a multi-agent system dispatched and managed by the central coordinator; according to the system, an end-to-end closed-loop processing flow from an entity file to a structured digital knowledge base is constructed through sequential collaboration of the physical digitization module, the AI agent collaboration network and the digital resource management module, connection of all links does not need to be manually intervened, manual review is only needed in a very few complex abnormal scenes, the labor cost is remarkably reduced, and the efficiency is improved. And the processing efficiency and the flow consistency are improved.

The invention discloses an automatic treatment device and method for metal workpiece surface polishing and application. According to the automatic environment-friendly electrochemical polishing device, the workpieces are automatically transferred through the automatic conveying device, automatic connection of all the procedures is achieved, and the automatic environment-friendly electrochemical polishing process of the metal workpieces such as the pure magnesium workpieces is achieved; and compared with the prior art, only water is used as a cleaning medium in the whole process, and toxic and harmful chemical agents are not needed. The environmental pollution risk is greatly reduced, and the environmental protection requirement is met. The environment-friendly polishing solution is adopted for electrochemical polishing, core components of the polishing solution are biodegradable non-toxic reagents such as ethyl alcohol and glycerinum, waste liquid treatment is simple, zero liquid discharge can be achieved, and the difficulty and cost of waste water treatment are remarkably reduced. According to the invention, the process flow is simplified, the consumption of chemicals and pollution emission are reduced, and the process efficiency is improved. According to the invention, whole-process monitoring and automatic operation from pretreatment to post-treatment are realized, the production efficiency and consistency are improved, and the method is suitable for industrial large-scale application.

A method of facilitating a skill learning process or improving performance of a task, comprising: determining a brainwave pattern reflecting neuronal activity of a skilled subject while engaged in a respective skill or task; processing the determined brainwave pattern with at least one automated processor; and subjecting a subject training in the respective skill or task to brain entrainment by a stimulus selected from the group consisting of one or more of a sensory excitation, a peripheral excitation, a transcranial excitation, and a deep brain stimulation, dependent on the processed temporal pattern extracted from brainwaves reflecting neuronal activity of the skilled subject.

The invention relates to the field of electronic design automation, provides a method for semi-automatically processing an EDA (Electronic Design Automation) project file and generating a YOLO format annotation data set, and aims to solve the technical problems of low efficiency and poor precision of the traditional pure manual data annotation data set. According to the main scheme, the method comprises the steps of reading an engineering file of a jia-creative EDA project, analyzing and extracting element information, generating a standardized CSV data format, converting the standardized CSV data format into a label in a YOLO format, calculating normalized bounding box coordinates of elements, and recognizing special original elements and supplementing labeling information in combination with a template matching technology; drawing a bounding box on the schematic diagram image according to a YOLO label, highlighting different element types by using different colors, and generating a visual annotation image; revising and combining the newly generated YOLO label and a preliminary YOLO label generated by the AI model to obtain a label set; then importing into Labelimg for manual correction, and generating a final label set; and training a target detection model by using the final label set, and improving the pre-labeling precision through data set expansion iteration.

The invention relates to the technical field of industrial adaptive control, in particular to an automatic processing parameter optimization method and system for a five-axis numerical control machine tool. The specific implementation process comprises the following steps: carrying out discrete analysis on machine tool parameters containing a cutter shaft vector and a translation shaft position coordinate, and generating time-varying geometric features; constructing a numerical control machine tool simulation model according to the material constitutive equation and the frequency domain response function, calculating a regenerative flutter prediction sequence, and dividing a real-time parameter feasible region by combining global rigidity and local flexibility data; and performing global iteration optimization on the processing parameter function group by using a multi-target optimization algorithm in the feasible region, and locking a Pareto optimal solution set to perform automatic optimization on the processing process. According to the method, the simulation model containing the physical dynamic characteristics and the real-time parameter feasible region are constructed, flutter and errors caused by stiffness matching imbalance are avoided, collaborative optimization of multiple target variables is achieved, and the productivity efficiency of the numerical control machine tool is remarkably improved on the premise that the machining precision is guaranteed.