3351results about How to "Reduce human error" patented technology

The invention provides a first-aid platform work order management method based on digital twinning and artificial intelligence, and belongs to the technical field of information technology application innovation, and the method comprises the steps: collecting historical first-aid data and real-time data of a first-aid scene, and constructing a task scheduling system based on a knowledge graph; decomposing the task into a plurality of sub-tasks according to the work order data, and allocating an optimal first-aid resource combination for the sub-tasks; an optimization strategy is set to carry out collaborative allocation control on each resource, and task allocation is optimized; the optimized task allocation is monitored in real time, and meanwhile, in combination with real-time data flow monitored in real time, it is ensured that the change of the dynamic environment is responded at any time in the task execution process; and re-inputting the optimized task allocation and resource scheduling strategy into the knowledge graph, and carrying out closed-loop optimization. According to the invention, the problems of inaccurate task scheduling, weak real-time response capability, low resource utilization rate and the like in the existing work order management system of the emergency platform are effectively overcome, and the overall efficiency and the automation level of the emergency platform are greatly improved.

The invention provides an AR-based intelligent integrated production line special circuit control method and system, and relates to the technical field of production line control, and the method comprises the steps: collecting a real-time point cloud model of production line equipment through AR glasses, and carrying out the registration of the real-time point cloud model and a preset three-dimensional model, and obtaining the state deviation data of the equipment; and analyzing an equipment operation trend by using a time sequence convolutional network, and generating an operation state evaluation index and a control parameter correction amount. A to-be-adjusted circuit control node is projected and displayed in the AR glasses, a control instruction is generated according to eye movement tracking and gesture interaction operation of an operator, and a control model is formed by recording a corresponding relation between the instruction and an operation state evaluation index. And based on the model, an AR auxiliary control system is constructed by an edge calculation unit, a control instruction is generated through graph neural network reasoning according to a new operation state evaluation index, and operation guide information is displayed on an AR interface. And after the operator confirms, an instruction is issued to a production line controller, and an execution result is fed back to update the control model, so that closed-loop control is realized.

The invention relates to the technical field of data processing, and discloses an intelligent product page automatic generation method and system for the massive health industry. The method comprises the following steps: performing multi-modal analysis and augmented reality processing on a large health industry prototype graph and multi-source medical data to obtain augmented design information; performing dynamic knowledge graph mapping and causal reasoning on the enhanced design information to obtain semantic structure and knowledge associated data; performing adaptive micro-service deployment analysis on the semantic structure and knowledge associated data to obtain a containerized deployment strategy, and performing intention-driven API design and homomorphic encryption enhancement processing to obtain API interface specification data; performing component design and code generation processing on the API interface specification data to obtain a multi-modal interaction page code; and performing intelligent rendering and dynamic content filling on the multi-modal interaction page code to obtain a target product page. According to the method and the device, the efficiency and the accuracy of automatic generation of intelligent product pages in the large health industry are improved.

The invention discloses a screening efficiency online monitoring method, device and system based on a vibrating screen, and relates to the technical field of vibrating screen efficiency monitoring, and the screening efficiency online monitoring method comprises the following steps: collecting working parameter data of the vibrating screen in real time through a sensor arranged on the vibrating screen; the accuracy and stability of screening efficiency are improved by monitoring key parameters such as humidity, particle size distribution and vibration frequency in real time and combining a screening effect model and a dynamic correction algorithm. The system automatically adjusts equipment parameters, equipment overload or screen damage is avoided, the material passing rate is optimized, and production losses are reduced. Meanwhile, manual intervention is reduced through an automatic control mechanism, the automation level of a production line is improved, human errors are reduced, the equipment fault and shutdown time is shortened, the production efficiency is improved, and the service life of the equipment is prolonged.

The invention provides a method for automatically configuring resources of a data center, and relates to the technical field of dynamic resource allocation, and the method comprises the following steps: monitoring load data of the data center in real time, and obtaining the real-time use state of each resource, including the processor utilization rate, the memory occupancy rate, the network bandwidth utilization rate and the use condition of storage equipment; and according to the load data of the data center, collecting and analyzing demand data of a current running service and a to-be-online service in real time, including a service type, a state, resource consumption, predicted online time and an expected resource demand, so as to obtain a service analysis result. Through real-time monitoring, intelligent analysis and prediction, dynamic optimal configuration of data center resources is realized, the resource utilization rate and the service continuity are effectively improved, and the operation cost is reduced at the same time.

The invention discloses an Internet of Things equipment access protocol component development method, which is used for quickly developing an Internet of Things equipment access protocol analysis and processing component at an Internet of Things platform side, and comprises the following steps: S1, constructing a protocol analysis and processing general framework according to the protocol analysis and processing component of an Internet of Things platform; s2, abstracting a specific logic processing part of a protocol in the general framework into a method / function interface; s3, constructing a protocol expert AI knowledge base for data learning; s4, constructing an AI large model and a multi-agent processing flow, selecting a specified large model, configuring related parameters, extracting required parameter extraction / coding logic, and generating an interface implementation code; s5, integrating each generated interface implementation code with the universal framework; and S6, testing, adjusting and optimizing the integrated access protocol analysis and processing component. According to the method, the unified development template can be provided, so that the development technical threshold is reduced, and the development efficiency is greatly improved.

The invention relates to the technical field of geological disaster evaluation, in particular to a mine geological disaster risk comprehensive evaluation method considering spatial distribution characteristics. The method comprises the following steps: acquiring mine multi-source spatial data; performing mine geological disaster risk distribution analysis on the mine multi-source spatial data to generate a mine geological risk distribution map; performing spatial region potential disaster probability analysis on the mine geological risk distribution map to generate mine geological distribution disaster probability data; and performing high-complexity spatial region screening on the mine geological risk distribution map through the mine geological distribution disaster probability data to obtain high-complexity spatial region data. According to the method, multi-source data are integrated, spatial distribution characteristics are emphasized, active and inactive areas are distinguished, ecological and water body changes are analyzed, and the accuracy and comprehensiveness of mine geological disaster risk comprehensive evaluation are improved.

The invention discloses a full-automatic laser welding forming system, which relates to the technical field of laser welding, and comprises a laser generation and light beam modulation module, a material conveying and positioning module, a welding execution module, a visual inspection and monitoring module, an intelligent self-adaptive control module and an energy recovery and reutilization module, the material module accurately conveys and positions materials; the welding module robot is accurate in operation; the visual module detects welding seams; the intelligent module performs self-adaptive control; the energy module recycles energy. The welding quality is improved, and defects are reduced; the production efficiency is improved and the cost is reduced; operation is simple, and manpower requirements are reduced; energy is saved, environment is protected, and green concept is met; real-time monitoring is achieved, and the product quality and the management level are guaranteed.

The invention discloses an intelligent detection method for medicine components and medicine quality, and belongs to the field of artificial intelligence. The method comprises the following steps: acquiring a drug sample solution and a control drug solution, and injecting the drug sample solution and the control drug solution into a high performance liquid chromatography system; determining whether operation parameters of the high performance liquid chromatography system need to be adjusted or not; determining operation parameter adjustment information, and continuously updating operation parameters of the high performance liquid chromatography analysis system until a complete drug sample chromatogram and a complete control drug chromatogram are obtained; determining medicine component information and impurity component information of the sample medicine; and determining whether the sample medicine reaches a preset medicine quality evaluation standard or not according to the medicine component information and the impurity component information, and if the preset medicine quality evaluation standard is reached, determining that the sample medicine passes quality detection. According to the scheme, the manual operation time and personal errors can be reduced, the detection efficiency and accuracy are improved, and the analysis result is more accurate and stable.

The invention discloses a character recognition and automatic auditing method and system, and the method comprises the steps: obtaining all to-be-audited document data including semi-structured and non-structured document data, guaranteeing the comprehensiveness of an auditing process, accurately recognizing the document content through an OCR technology, converting the document content into operable structured data, and carrying out the automatic auditing of the to-be-audited document data. Key information in a document is selected through two modes of rule extraction and model extraction, the efficiency and accuracy of information processing are improved, the information is compared with pre-established target structured text data, compliance check is automatically completed, the compliance of an auditing result is ensured, a confidence coefficient threshold value is updated in real time according to the complexity of the document, and the accuracy of information processing is improved. The method is suitable for document data with different complexities, the automatic auditing process remarkably improves the auditing efficiency, when a large amount of document data is processed, a large amount of time and manpower resources can be saved, the auditing result and the corresponding confidence rate can be output, a user can see the specific result of document analysis, and the auditing reliability and the credibility of the user are improved.

The invention relates to the technical field of bolt mounting equipment, in particular to an angle steel tower bolt perforation mounting method. By means of autonomous navigation of the installation robot and flexible operation of the mechanical arm, rapid positioning and taking-out of bolts and nuts are achieved, and the risk of manual climbing and operation is reduced. Accurate insertion and preliminary positioning of the bolt are ensured through accurate control of the mechanical arm, then the fastening effect is enhanced by combining impact tightening with the intermittent hammering technology, the fit clearance between the angle steel is effectively eliminated, and the bolt is prevented from loosening. The whole process is highly automatic, personal errors are reduced, and the mounting quality and the working safety are improved.

The invention relates to the technical field of safety engineering and artificial intelligence, in particular to a limited space operation safety risk assessment method and system, and aims to effectively improve the core defects of the prior art through a machine learning technology and a data analysis method. Due to the real-time monitoring and evaluation capability, the system can respond to environmental changes in time; the model can identify and adapt to new risk factors due to high adaptability; the accuracy and objectivity of evaluation are improved through a data driving method; an iterative optimization mechanism ensures that the model can be evolved continuously, the effectiveness of risk management is enhanced, a more efficient, more accurate and more reliable safety risk assessment method and system are provided for limited space operation, a solid technical support is provided for guaranteeing operation safety, and the method and the system have good application prospects. And an important step of intelligent and digitized development of the security risk assessment field is marked.

The invention relates to the field of intelligent auditing data, in particular to a standard intelligent auditing and compliance checking method and system, a terminal and a medium. Dividing the to-be-audited document into a plurality of document elements based on the to-be-audited document and a preset classification rule; analyzing the to-be-audited document based on the plurality of document elements and a preset auditing direction corresponding to each document element; and generating an auditing report and an auditing manuscript based on the auditing result of each document element. According to the method, the document auditing efficiency and accuracy are improved.

The invention discloses a long-distance communication trunk optical cable fault positioning method and system, and the method comprises the steps: determining a monitoring demand, configuring an optical power meter, an optical spectrum analyzer and an OTDR, installing the optical power meter, the optical spectrum analyzer and the OTDR at a node, connecting monitoring equipment and a data collection system, configuring collection frequency, a threshold value, a storage and transmission strategy, configuring a data analysis algorithm, and starting the monitoring system to collect data. The optical cable performance is monitored in real time, data are automatically analyzed to identify abnormity, a fault alarm is generated and notified to maintenance personnel, and the data are integrated to automatically calculate the fault position. The fault detection and positioning efficiency is improved, the network reliability and maintenance efficiency are enhanced, and guarantee is provided for stable operation of the optical cable network.

The invention provides a construction method, a control method and a system of a flight control network, and the method comprises the steps: employing a depth deterministic strategy gradient algorithm, building an attitude control network of an unmanned aerial vehicle in a flight process based on the state information and a target flight value of the unmanned aerial vehicle in the flight process, employing a depth reinforcement learning algorithm, and carrying out the attitude control of the unmanned aerial vehicle in the flight process. Based on the state information and the information of the environment where the unmanned aerial vehicle is located, a path planning network and an intelligent avoidance network of the unmanned aerial vehicle in the flight process are built respectively; based on the attitude control network, the path planning network and the intelligent avoidance network, constructing a hierarchical deep reinforcement learning network of the unmanned aerial vehicle in the flight process; and training the hierarchical deep reinforcement learning network by adopting historical flight data of the unmanned aerial vehicle in different flight environments and a preset flight reward mechanism to obtain a flight control network of the unmanned aerial vehicle. According to the invention, the adaptability and flexibility of the unmanned aerial vehicle in the flight process can be improved.

The invention discloses an intelligent bid evaluation method and system based on a large model, and a related product, relates to the technical field of purchase bid evaluation systems, and solves the problems that an existing intelligent bid evaluation system is difficult to understand a complex logical relationship and semantic connotation and cannot provide a comprehensive and accurate scoring result. According to the technical scheme, the method comprises the steps that S1, bidding and tendering files are obtained; s2, performing disassembly processing based on the bidding and tendering file to obtain a plurality of bidding and tendering data pairs; s3, performing instruction construction on the bidding and tendering data pair based on a historical bidding and tendering database to obtain a prompt instruction of the bidding and tendering data pair; s4, processing the prompt instruction of the bidding and tendering data pair based on the large model after training and fine tuning to obtain the score of the bidding and tendering data pair, and accumulating the scores to obtain the score of the bidding file; through the method based on the large model, the scoring effect is effectively improved in the intelligent bid evaluation work, the efficiency is improved, manpower and material resources are saved, and meanwhile interference caused by human factors is avoided.

The invention discloses an automatic quality-supplementing correction method and system for the unbalance amount of a fan, and the method comprises the following steps: collecting geometric parameters and material characteristics in a static state of the fan, and constructing a mechanical distribution model of the fan; the method comprises the following steps: collecting vibration signals and airflow characteristics in real time in a dynamic operation state, calculating the amount of unbalance in operation and decomposing the amount of unbalance into a primary component and a secondary component; on the basis of the unbalance prediction trend, determining a quality supplementing range, carrying out multi-point quality supplementing operation through a dispensing technology, and monitoring a quality supplementing effect by using an optical fiber sensor; and if the residual unbalance amount after quality supplementation still exceeds the standard, real-time compensation adjustment is carried out through the electromagnetic torque regulation and control module. Full-process automatic correction from static state to dynamic state and from quality supplement to fine adjustment is achieved, the method has the advantages of being real-time, accurate and intelligent, vibration and noise in the fan operation process can be effectively reduced, the operation stability of equipment is improved, and the service life of the equipment is prolonged.

The invention relates to the technical field of plant extraction, in particular to an intelligent plant extraction control method and system, and the method comprises the following steps: based on historic plant extraction data, including temperature, pressure and pH value during extraction, analyzing the long-term trend of parameters, predicting the requirements of plant extraction conditions by simulating parameter reactions under various conditions, and obtaining a plant extraction result; and obtaining a parameter prediction result. According to the method, long-term trend prediction of parameters such as temperature, pressure and pH value is realized through analysis of historically recorded plant extraction data, so that the parameters of extraction equipment are adjusted in advance, changes of different plant materials and environmental conditions are effectively adapted, the extraction efficiency is optimized, and by dynamically simulating the expression of the extraction efficiency in various time periods, the extraction efficiency is improved. According to the innovative scheme, an optimal extraction time window is mined, resource consumption and extraction time in the extraction process are reduced, and meanwhile the quality and consistency of extracts are kept.

The invention relates to a concrete surface crack detection method and system based on a machine learning algorithm, and the method comprises the steps: obtaining concrete wave velocity, frequency, amplitude, strength, elastic modulus, temperature and linear expansion coefficient, analyzing characteristic parameters, building a mathematical relation model, fitting data through a machine learning algorithm, determining model parameters, and calculating the concrete surface crack detection result. Relevant parameters of to-be-detected concrete are input into the multi-parameter digital quantity plate model, the model calculates potential risks and predicted values of cracks, the multi-parameter digital quantity plate model is applied to real-time detection of the concrete structure to achieve quality evaluation and crack prediction, the concrete structure is monitored regularly, and model data are updated; the system comprises a data acquisition module, a data preprocessing module, a feature extraction module, a crack measurement module, a multi-parameter digital quantity board model establishment module, a multi-parameter comprehensive analysis module, a real-time monitoring and early warning module, a database management module and a user interface and interaction module.

The invention discloses a light guide plate film covering method, device and equipment, and the method comprises the steps: responding to the detected size, material and surface condition of a light guide plate, and judging whether the light guide plate meets a film covering standard or not; commanding the robot to grab the membrane material, accurately positioning the alignment operation of the light guide plate and the membrane material through a visual guidance system, and adjusting the fitting position; controlling the membrane material to be preliminarily attached to the light guide plate, and adjusting pressure and adsorption force in real time according to material characteristics; analyzing data of the visual detection system, commanding the intelligent fluid dynamics control device to process bubbles or wrinkles, and meanwhile, re-scanning the processed area to ensure that the defoaming effect is qualified; and controlling the curing time, the curing temperature or the UV light intensity according to the used curing mode. According to the technical scheme, the laminating quality is improved, and bubbles and flaws are reduced.

The invention discloses a grinding control system for reducing the surface stress difference of a workpiece, relates to the technical field of workpiece grinding, and can dynamically monitor the state change in the grinding process by collecting temperature, vibration, cutting force and stress data in real time to ensure timely response to potential problems. The collected data is cleaned and standardized, the data quality is improved, the index cutting force fluctuation coefficient Kf, the stress distribution coefficient Sd and the mechanical vibration frequency fv are extracted, and a reliable basis is provided for subsequent analysis. And the grinding strategy optimization module dynamically adjusts the feeding speed Vf and the grinding depth d based on feedback information, fine control is achieved, the surface stress difference of the workpiece is reduced, and the surface quality is improved. The surface stress difference is reduced, the use performance and the service life of the workpiece are remarkably improved, grinding parameters are adjusted in real time, defects in the grinding process can be effectively reduced, the rejection rate is reduced, the grinding parameters and the stable operation process are accurately controlled, and the overall production efficiency is improved.

The invention provides a data flow-based runtime text context transmission and task instance dynamic scheduling method, which relates to the technical field of data processing, and comprises the following steps of: receiving a task scheduling request, constructing a data flow dependency graph containing task nodes and a data flow direction relationship, and obtaining runtime context information of task instances corresponding to the task nodes, comprising task instance identification, state information and input and output parameter information. And establishing a mapping relationship between task instance input and output parameters by analyzing a data flow dependency graph and runtime context information, and generating a parameter transfer rule. According to the method, task instance state information is monitored, when the state of an upstream task changes, an upstream output parameter is transmitted to a downstream input parameter according to a parameter transmission rule, and when the downstream input parameter is complete, dynamic scheduling execution of a downstream task instance is triggered, so that data flow driven task scheduling is achieved, and the scheduling efficiency and flexibility are improved.

The invention discloses a tunnel crack tiny defect detection method based on a generative adversarial network. The method comprises the following steps: S1, acquiring a space-time crack data set containing tunnel surface tiny crack information; s2, generating a preprocessed space-time fracture data set; s3, generating a crack expansion image data set; s4, designing a generative adversarial network model which comprises a generator and a discriminator; s5, inputting the preprocessed space-time crack data set into the generative adversarial network model; s6, deploying the trained generative adversarial network model into a tunnel monitoring system; s7, performing classification according to the form, size and expansion trend of the crack, and dividing the crack into different risk grades; and S8, according to the crack detection result and the expansion trend thereof. The tunnel crack detection accuracy and the crack propagation prediction capability are improved, the automation level of the system is remarkably improved, and efficient and accurate crack detection and monitoring can be realized in a complex environment.

The invention discloses an official document generation system and method based on a large model, belongs to the technical field of artificial intelligence, and aims to solve the technical problems of low official document format and content accuracy, poor material failure and poor content innovation in official document generation. Comprising a model training module used for performing model training on an official document generation model based on official document samples in an official document sample library; the model fine tuning module is used for performing layered fine tuning on the trained official document generation model; the cue word optimization module is used for carrying out cue word matching on user input based on a built-in cue word set; the outline generation module is used for calling a final official document generation model to generate an official document outline based on the cue word combination and user input; and the official document generation module is used for calling the final official document generation model to generate and output an official document body based on the user input and the final official document outline, and calling the privacy data shielding module to shield the privacy data in the official document body.

The invention relates to the technical field of data management, in particular to a data asset sorting method, which comprises the following steps: preliminarily classifying all data assets in an enterprise, performing quality evaluation on the preliminarily classified data assets, generating a quality evaluation report, and performing data redundancy detection and optimization based on the quality evaluation result. Cleaning redundant data by adopting a deduplication algorithm and an optimization algorithm, carrying out data correlation analysis, generating a data correlation graph through a graph model and a statistical model, and determining the relationship between data sets; and finally, according to a correlation analysis result, integrating the data sets with high correlation into a unified data set by adopting a data fusion algorithm, and reducing a storage space through a data compression technology. According to the method, the accuracy of data classification and management can be improved, the data redundancy is reduced, the data storage and access efficiency is optimized, and the data security and privacy protection are enhanced through security evaluation and protection measures.

The invention belongs to the technical field of machine learning, and discloses an automatic quality inspection method for annotation information, electronic equipment and a storage medium, and the method comprises the steps: obtaining annotation information on a to-be-trained image; wherein the annotation information comprises coordinates of each annotation frame; the to-be-trained image and the corresponding labeling information are input into a trained large model, the trained large model is used for extracting the feature information of the to-be-trained image to obtain a feature map of the to-be-trained image, and according to the coordinates of all the labeling boxes, the feature map is cut in an equal proportion to obtain picture features corresponding to all the labeling boxes; and carrying out clustering analysis on the extracted picture features corresponding to each labeling box to identify abnormal labels and realize automatic quality inspection of the labeling information. According to the method, the quality inspection efficiency and accuracy of the annotation information can be improved, the dependence on manual auditing can be reduced, and a large amount of labor cost and time cost are saved.

The invention belongs to the technical field of shot blasting processes, and provides a self-adaptive aero-engine blade surface shot blasting control system and a shot blasting process. The system comprises a measurement module used for obtaining the three-dimensional geometrical shape of the complex surface of the blade and generating a digital three-dimensional model; the sensor module is used for monitoring and feeding back the shot blasting process condition in real time; the control module is used for dynamically adjusting shot blasting parameters by adopting a self-adaptive algorithm; the shot blasting execution module is used for executing a shot blasting process; the real-time monitoring feedback module is used for dynamically adjusting shot blasting parameters; the process comprises the steps that after the blade surface is cleaned, a three-dimensional model generated by a measuring module and surface data measured by a sensor module are fed back to a control module, a shot blasting injection parameter instruction is obtained through a fuzzy control algorithm, and a shot blasting machine execution module executes the shot blasting process. And the real-time monitoring feedback module dynamically adjusts shot blasting parameters until the shot blasting process requirements are met. According to the invention, accurate and uniform shot blasting treatment on the surface of the blade in a complex shape can be realized.

The invention proposes a semiconductor device test optimization method, and the method comprises the steps: initializing a test environment, obtaining the test data of a semiconductor, and automatically configuring the test environment; constructing a signal adjustment model to dynamically generate a preliminary test signal; designing a sensor network to monitor a preliminary test signal and response of the semiconductor device in real time, dynamically adjusting sensor data, and designing a data optimization acquisition strategy; dividing the parameters into a high priority and a low priority, dynamically compressing the parameters, implementing fast Fourier transform, extracting spectrum components as features, and analyzing the features; decompressing and preprocessing the compressed data, and performing deep fault analysis and positioning; and optimizing test data of the conductor, carrying out secondary test, and verifying a parameter adjustment result. According to the invention, the test quality and efficiency of the semiconductor device can be obviously improved, the product failure rate caused by insufficient test can be reduced, and the method plays an important role in semiconductor manufacturing industry, especially high-end chip production.

The invention discloses a CTC cell detection method based on a micro-fluidic chip, and belongs to the technical field of cell treatment. In order to solve the problems of high false positive and false negative rates, time consumption and low efficiency caused by difficulty in accurately distinguishing CTC from other cell types, the invention can efficiently and specifically capture CTC cells, reduce the possibility of false positive and false negative and improve the detection accuracy by constructing a specific capture chamber and filling specific antibodies and immunomagnetic beads. The multi-channel design allows a plurality of samples to be processed at the same time, the detection efficiency is improved, the micro-fluidic chip technology integrates a plurality of steps on one platform, automation and standardization of operation are achieved, personal errors are reduced, the stability and repeatability of detection are improved, the uniformity and stability of the detection process are ensured, and the detection efficiency is improved. The fluorescence imaging technology clearly displays CTC and obtains key parameters such as quantity, form and fluorescence intensity of CTC, thereby providing powerful support for cancer diagnosis and research.

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.