1773results about How to "No human intervention required" patented technology

The invention provides a desilting robot intelligent control method and system based on deep learning, and relates to the technical field of intelligent control, and the method comprises the steps: collecting environment information through a multi-source sensor, extracting environment features through a convolutional neural network and a recurrent neural network, and building a three-dimensional dynamic model of a desilting robot operation environment; based on the model and a hierarchical reward function, training a dual neural network by using a depth deterministic strategy gradient algorithm to obtain an intelligent control strategy model; a motion track output by the model is optimized by an improved ant colony algorithm of a double-target pheromone updating strategy based on path length and energy consumption and then is input into a layered model prediction controller, and cooperative control over a dredging robot propeller and a dredging device is achieved. The working efficiency and the energy utilization rate of the dredging robot are effectively improved, and the dredging cost is reduced.

The invention provides an embedded device online test and remote maintenance method and system, and relates to the technical field of device maintenance, and the method comprises the steps: collecting multi-source heterogeneous data, selecting a sampling period based on Shannon entropy, employing wavelet transform and fractal theory to extract features, inputting an anomaly detection model to generate an anomaly degree vector, and carrying out the detection of the anomaly degree vector; extracting features by using a capsule neural network and performing fault type probability distribution prediction; calculating system state indexes by combining a phase-space reconstruction technology; inputting a causal reasoning network to generate a fault diagnosis report; retrieving a maintenance scheme based on the fault diagnosis report; and the maintenance effect is evaluated through the twin neural network, and the maintenance instruction is iteratively optimized according to the effect until the maintenance effect reaches the standard.

The invention discloses an AI model adaptive tuning method based on deep reinforcement learning, and belongs to the technical field of industrial process control, the method comprises the following steps: firstly, constructing a deep reinforcement learning environment comprising a state space, an action space and a reward function, the state space comprising a process variable measurement value, a controller parameter and a performance index; the action space is a parameter adjustment quantity vector, and the reward function comprehensively considers the stability, rapidity and accuracy of the system; then, based on a deep Q learning network of a dual-network structure, training data are stored and sampled by adopting an experience playback mechanism, and network parameters are iteratively optimized through a deep Q learning algorithm; and finally, realizing online adaptive adjustment of controller parameters by using the optimized deep Q network. The method has the advantages of being high in adaptability, good in optimization performance, high in practicability and the like, intelligent optimization control over an industrial process control system can be achieved, and the overall performance of the system is improved.

The invention relates to a metropolitan area network traffic prediction application method based on a neural network, and belongs to the technical field of network traffic. Dividing a training set, a verification set and a test set; 70%, 20% and 10% of data are used for model training, optimization and evaluation; inputting the traffic data into the double-layer stacked LSTM network, obtaining hidden state information and extracting time sequence characteristics and dependency of network traffic; capturing a long-term and short-term dependency relationship in the flow by using an encoder; global dependency features are extracted through a self-attention mechanism; gradually predicting flow data of a plurality of time points in the future by adopting a decoder; an early stop strategy is adopted in model training to prevent overfitting; carrying out anti-standardization processing on a model prediction result, and recovering an original scale; and evaluating a model prediction result. According to the invention, training and optimization of the deep learning model are carried out on the historical data and the feature data of the metropolitan area network, so that the accuracy of IP network traffic prediction is remarkably improved.

The invention provides an Internet of Things data processing method and system based on a block chain, and relates to the technical field of block chains, and the method comprises the steps that an Internet of Things device carries out the digital signature of an authentication request through employing a pre-stored private key, and generates a signed authentication request; the smart contract in the block chain network receives the signed authentication request, and the smart contract generates an authentication token including an authentication result, a validity period and an authorization level based on the historical authentication record, the credit score, the current timestamp and the challenge value; the Internet of Things equipment receives the encrypted authentication token and the intelligent contract address; the Internet of Things equipment configures own access authority and function limitation according to the authentication result, the validity period and the authorization level; and the Internet of Things equipment takes the intelligent contract address as an identity credential within the period of validity, and is used for subsequent secure communication and data exchange with other Internet of Things equipment or application programs.

The invention provides a distributed storage and data warehouse permission synchronization method and system, and relates to the technical field of permission management, and the method comprises the steps: analyzing user operation data of distributed storage, training a machine learning model, and generating a directory permission intelligent mapping table; analyzing the structure information of the data table in the data warehouse, and generating a multi-dimensional table authority evaluation model; generating a self-adaptive permission rule base by combining the two, and deploying the self-adaptive permission rule base to each node of distributed storage; when the permission is changed, the system calculates an influence range according to the self-adaptive permission rule base and generates a permission updating instruction sequence; and the system monitors the instruction execution state, identifies abnormal nodes, and performs repair based on the permission propagation tree to ensure the permission consistency. According to the method, automatic synchronization of distributed storage and data warehouse authority can be realized, the authority management efficiency is improved, the manual intervention cost is reduced, and the data security is enhanced.

The invention discloses an unmanned aerial vehicle flight control method and system based on a target image, and relates to the field of unmanned aerial vehicle flight control, and the method comprises the steps: obtaining the relative position of an unmanned aerial vehicle in a flight region based on the target image and a position calculation algorithm, and judging the yaw state of the unmanned aerial vehicle through a position comparison method; analyzing the target image by using an identification processing technology based on yaw state judgment to determine a flight yaw angle of the unmanned aerial vehicle, and generating a yaw control quantity according to the flight yaw angle to control the flight state of the unmanned aerial vehicle; collecting a real-time target image of the unmanned aerial vehicle after the flight state is adjusted, analyzing the flight height of the unmanned aerial vehicle according to the real-time target image, and planning a landing track of the unmanned aerial vehicle based on the flight height; and generating an autonomous landing control instruction according to the unmanned aerial vehicle landing trajectory and a preset flight demand to complete autonomous landing flight control of the unmanned aerial vehicle. By collecting the target image in real time and analyzing the flight height, the landing track of the unmanned aerial vehicle can be accurately planned.

The invention relates to the technical field of pipeline welding seam identification and measurement, aims to solve the problem of uncontrollable data acquisition quality and the problems of robustness and precision of single-feature welding seam extraction, and provides a nuclear power station pipeline welding seam automatic identification and measurement method which comprises the following steps: accurately acquiring pipeline data under a self-adaptive front view posture; carrying out point cloud data processing on the collected data, and carrying out fitting of a pipeline model after segmenting out part of point cloud of the pipeline; after pipeline modeling is completed, a multi-dimensional data fusion method is adopted for weld joint recognition; and after the welding seam area is back projected back to the three-dimensional point cloud space, three-dimensional point cloud of the welding seam area is obtained, modeling is conducted on the welding seam area in combination with the pipeline model, and finally measurement data of the welding seam are obtained. According to the invention, automatic hand-eye calibration and multi-camera calibration of the guiding system can be realized without manual intervention.

The invention provides a logic modeling-based high-orbit satellite network dynamic optimization method and an SDN controller, and the method comprises the steps: constructing a logic model corresponding to a high-orbit satellite network according to the attribute information of physical equipment and satellite links in the high-orbit satellite network, collecting the real-time state data in the network, and carrying out the calculation of the real-time state data. Updating logic attribute information in the logic model based on the real-time state data; when it is determined that the resource adjustment requirement exists, generating a resource adjustment control instruction according to the updated logic attribute information, the topological structure of the logic model and a preset service priority; converting the resource adjustment control instruction into an operable command and issuing the operable command to physical equipment; monitoring execution results of the physical devices, and returning to the step of collecting the real-time state data of the physical devices and the satellite links and updating the logic attribute information in the logic model based on the real-time state data. According to the method, dynamic adjustment and closed-loop optimization of resources in the high-orbit satellite network can be realized, and the flexibility, reliability and service quality of the network are improved.

The invention discloses a trusted data flow evidence storage management system based on a block chain, and relates to the technical field of data communication. The intelligent management platform is in communication connection with an evidence storage data acquisition module, an evidence storage generation module, a node priority analysis module, a flow scheduling module, a data evidence storage management module and a monitoring maintenance module, and all the modules are in electric signal connection. According to the method, the integrity and authenticity of the data in the circulation process are ensured through tampering resistance of the block chain, circulation of each data is recorded on the block chain, an open and transparent data account book is formed, the source, the flow direction and the change history of the data become traceable, the circulation path and the state of the data are clarified, and in addition, the data circulation efficiency is improved. And through log recording and transaction processing condition analysis functions, the transparency of the data circulation process is further enhanced, so that the use of the data is more standard.

The invention relates to the technical field of medical image processing, and discloses a CyclGan-based multi-modal medical image elastic registration system, which comprises a multi-modal medical image data preprocessing module, a CyclGan-based elastic registration module, a CyclGan-based elastic registration module and a CyclGan-based elastic registration module, a module for training the CyclGan model on the basis of training strategies of medical image data of different modalities; a module for performing elastic transformation and resampling on the preprocessed medical image based on an output grid of the model; and a post-processing module is used for post-processing the deformed medical image. Through the above operations, automatic elastic registration between medical images of different modalities and fusion of medical images of different modalities after registration and alignment can be realized, a doctor is helped to obtain more comprehensive information and more accurately position a lesion area, and thus the accuracy and efficiency of diagnosis are improved.

The invention relates to the technical field of window opener chains, in particular to a window opener chain strength testing device based on electric window opener production and a testing method.The window opener chain strength testing device comprises a frame and a testing window opener, a simulation window is arranged on one side of the frame, and the top of the simulation window is fixedly connected with a rotating shaft rotationally connected with the frame; a window opener chain is mounted in the test window opener, one end of the window opener chain is fixedly connected with the simulation window through a connecting seat, a mounting cylinder is arranged in the frame, the outer surface of the mounting cylinder is in sliding connection with a rotating ring, one end of the rotating ring is fixedly connected with a pull handle rotationally connected with the simulation window, and the other end of the rotating ring is fixedly connected with the test window opener. A mounting cylinder is arranged in the frame, a resistance assembly is arranged in the mounting cylinder, a straight plate is arranged on one side of the frame, a pressure applying plate for applying resistance to the simulation window is arranged at the bottom of the straight plate, sliding seats are slidably connected to the two ends of the frame, and pressure assemblies acting on the straight plate are arranged on one sides of the two sliding seats.

The invention, which relates to the technical field of image processing, discloses a method for converting a 2D image into a 3D image, comprising the following steps: step 1, obtaining a 2D image; step 2, monocular depth estimation is carried out on the 2D image to obtain a relative depth map; 3, determining the longitudinal depth and the zero parallax surface of the scene according to the content of the 2D image; 4, carrying out value domain transformation on the depth map; 5, calculating the parallax of each pixel of the 2D image according to the transformed depth map, and then rendering an image of a virtual viewpoint according to the parallax; and step 6, repairing the cavity. According to the method for converting the 2D image into the 3D image, the watching experience is improved, the stereoscopic impression is enhanced, the ghosting phenomenon is reduced, and the proper proportion scale is kept; the conversion efficiency and the automation degree are improved, and manual intervention is reduced; meanwhile, the generalization ability is enhanced; in addition, the hole repairing effect is optimized, so that the converted 3D image is more natural and perfect.

The invention discloses a method for automatically keeping a chassis of mobile intelligent equipment horizontal on a slope, and relates to the technical field of mobile intelligent equipment.The method comprises the following specific steps that terrain detection is conducted, specifically, the current terrain condition is detected in real time through a sensor system installed on the mobile intelligent equipment, and the terrain condition is determined; comprising slope angles, soil types and rock distribution information; by integrating the sensor system and the central processing unit, real-time monitoring and intelligent analysis of slope topography and road surface conditions are achieved, mobile intelligent equipment can rapidly sense and adapt to various complex topographies including soft soil slopes, rugged rock slopes and the like, and by automatically adjusting the level of the chassis, the slope topography and the road surface conditions can be monitored and analyzed in real time. And the stability and the operation performance of the equipment on different terrains are ensured, so that the terrain adaptability of the equipment is remarkably improved, the mobile intelligent equipment can play a role in a wider environment, and the application range and the practicability of the equipment are improved.

The invention discloses a judicial field semantic abstracting method, system and device based on a large model and a storage medium. The method comprises the steps that voice recognition is conducted on a court trial video, voice is converted into a court trial text, the court trial text is labeled, and a labeled text set is obtained to serve as a training set; training the large model by using the labeled text set, and finely adjusting the large model after each round of training; performing voice recognition on the actual court trial video, converting the voice into an actual court trial text, and extracting a timestamp; utilizing the trained large model to identify the court hearing process of the actual court hearing text, and reasoning a court hearing process text; matching the reasoned court hearing process text to timestamps by using a matching algorithm, and generating video anchor points when the timestamps at the starting positions of all the processes in the court hearing process text correspond to the anchor points of the processes of the court hearing video; abstracting the reasoned court hearing process text; and combining the abstract text with the video anchor points to generate structured court hearing information. According to the invention, the court trial video processing efficiency is improved.

The invention discloses a reservoir bank slope inspection method and system based on an unmanned aerial vehicle laser radar, and relates to the technical field of unmanned aerial vehicle reservoir bank slope inspection, and the method comprises the following steps: 1, guaranteeing the normal working state of an unmanned aerial vehicle, starting the laser radar, connecting a ground GNSS reference station on the shore, calibrating the position of the unmanned aerial vehicle and a communication signal, an inspection area boundary and flight parameters are set; navigation data provided by a shoreside base station is utilized. According to the reservoir bank slope inspection method and system based on the unmanned aerial vehicle laser radar, the inspection efficiency is improved, and the endurance time is prolonged; the system is high in autonomy, reduces the labor cost, achieves the whole-course autonomous navigation, path optimization, obstacle avoidance and dynamic adjustment, does not need manual intervention, effectively reduces the workload and operation difficulty of inspection personnel, reduces the labor cost, improves the intelligent level of inspection tasks, and improves the autonomous adaptability of the unmanned aerial vehicle to complex terrains.

The utility model discloses a transplanter duckbilled planter and brush transmission mechanism with a soil cleaning function, which comprises a mounting plate, a comprehensive transmission mechanism is mounted on the mounting plate, a brush support is further mounted on a frame of a transplanter, a swing plate is rotatably connected to the brush support through a hinge seat, a brush shaft is mounted at the other end of the swing plate, and the brush shaft is rotatably connected to the brush support through a hinge seat. The brush shaft is fixedly connected with a cylindrical brush, a brush transmission wheel is installed on the brush shaft, and the brush transmission wheel is in transmission connection with the brush driving wheel through a transmission chain. The comprehensive transmission mechanism is used for driving the duckbilled planting device to vertically rotate, driving the duckbilled planting device to periodically open and close and driving the brush to periodically swing along with the duckbilled planting device; an opening part and a closing part are arranged in the rotating track of the duckbilled planting device, and when the duckbilled planting device is located at the opening part in the rotating track of the duckbilled planting device, the brush swings along with the duckbilled planting device and is connected with the duckbilled planting device. When the brush rotates, the closed part in the rotating track of the duckbilled planting device is in close contact with the duckbilled planting device, soil impurities adhered to the inner wall and the outer wall of the duckbilled planting device are cleaned, the cleaning effect is good, the soil cleaning efficiency is high, manual cleaning can be carried out without shutdown, and the plant transplanting efficiency is remarkably improved.

The invention discloses a data processing method and device, computer equipment and a storage medium, relates to the technical field of data processing and database optimization, and can solve the problem that in the prior art, a compression strategy cannot be dynamically adjusted according to the characteristics of partitions, so that the data storage speed and the storage space utilization rate are affected. The method comprises the following steps: inputting a target data feature of a target partition in a current time period into a preset prediction model for prediction to obtain a query frequency corresponding to the target partition in a next time period; based on the frequency range to which the query frequency belongs, determining a compression strategy corresponding to the target partition in the next time period; and adjusting the compression ratio of the target partition based on the compression strategy.

The invention discloses a tower crane installation path planning method and system, a terminal and a medium, and the method comprises the following steps: collecting and preprocessing three-dimensional point cloud data and visual information in a tower crane installation area, fusing the point cloud data with image data, and generating a fused three-dimensional point cloud image which comprises distance and color information; a deep learning model is adopted to carry out obstacle detection on the fused three-dimensional point cloud image; an RRT algorithm is adopted, and a safety path is planned according to the obstacle detection result and the requirement of the hoisting task; and controlling the movement of the hoisting equipment according to the obtained safe path, and executing ascending, descending, horizontal moving and rotating actions of a lifting hook according to a path planning result. The method has the advantages that the safety and the efficiency in the hoisting operation of the power transmission tower are improved, and the quality and the reliability of power transmission line construction are improved.

The invention relates to the technical field of dirt cleaning, in particular to a cable self-cleaning assembly for a ship winch, which is mounted on a rack of the ship winch and comprises two mounting frames, a connecting rod is fixed between the two mounting frames and penetrates through a moving seat, a lead screw is screwed on the surface of the moving seat, and two ends of the lead screw are rotatably connected to the two mounting frames respectively. Two supporting plates are fixed to the top face of the movable base, a connecting plate is fixed between the top faces of the two supporting plates, two fixing plates are inserted into the surface of the connecting plate, and a wire guide roller is rotationally connected between the fixing plates and the movable base; the ship stranded wire correcting device has the beneficial effects that the position of the movable seat can be conveniently adjusted by rotating the screw rod, so that the distance between the wire guide rollers is adjusted, and ship stranded wires are corrected. And meanwhile, the cable can be automatically cleaned in the winding process through the design of the protective sleeve and the steel wire brush, the cable can be automatically oiled through the combination of the oil storage tank and the sponge core, manual intervention is not needed in the whole process, and the working efficiency is greatly improved.

The invention provides a device and a method for on-line detection and precise regulation and control of the sowing depth and the sowing amount of a peanut precision seeder. An ultrasonic distance measuring sensor, an optical fiber counting sensor, a double-shaft tilt angle sensor, a linear displacement sensor, a photoelectric rotary encoder and the like are used for acquiring operation information such as the seeding depth, the seeding quantity, the seeding machine tilt angle, the expansion amount of an electric cylinder telescopic mechanism, the machine tool speed and the seeding frequency of a seeding machine in real time; through digital signal processing and conversion, STM32F103ZE single-chip microcomputer processing, control algorithm optimization, on-line detection of the seeding depth and the seeding condition of the seeder, real-time adjustment of the seeding depth and real-time reseeding, real-time accurate regulation and control of peanut seeding are realized, and it is ensured that peanut seeding meets the requirements for consistency of the seeding depth and the seeding distance; meanwhile, the whole sowing process is more automatic and efficient, manual intervention is not needed, manpower and material resources are saved, and good economic benefits are achieved.

The invention belongs to the technical field of bacterial culture, and discloses a high-throughput automatic monoclonal screening and picking workstation, which comprises a protective box for protection and isolation, and a workbench is arranged in the protective box; the plate stack module comprises a rotating plate stack arranged at the bottom end of the workbench, and a plurality of columns of culture dishes are arranged on the rotating plate stack in a lifting manner; the transfer module is arranged on the workbench and used for transferring culture dishes; the pipetting module comprises a pipetting assembly and a material storage assembly, and the pipetting assembly is used for transferring strains in the culture dish into the material storage assembly; the identification module is used for identifying and positioning the strains in the culture dish and then controlling the pipetting assembly to accurately transfer the strains. The device is simple in structure and flexible and convenient to use, high-throughput screening and picking of strains can be fully automatically carried out in a clean closed environment, manual intervention is not needed, the screening efficiency is high, strain pollution caused by manual intervention is avoided, the screening precision is high, the screening cost is reduced, and experiments are greatly facilitated.

The invention provides a home planting assembly and control system based on a fourth-generation residence, and relates to the technical field of intelligent gardening planting, the home planting assembly comprises a balcony plane, a planting area and a vine climbing area, a cushion table is placed at the bottom of the inner back of the balcony plane, and square side piles are clamped to one side and the middle of the top of the cushion table; a bearing plate is connected between the side piles on the two sides in a mortise and tenon joint mode, embedded blocks are embedded in the two sides of the bearing plate, clamping openings are formed in the side edges of the embedded blocks, and the clamping openings are matched with the side piles. Through organic combination of the data acquisition module, the environment regulation and control module, the irrigation management module, the illumination optimization module, the pest control module, the remote monitoring module and the power supply support module, the problems of single function, lack of systematicness, resource waste, low management efficiency and the like in the prior art are solved.

The invention discloses a large-model-driven intelligent biosynthesis system and method, and the system employs a centralized multi-large-model intelligent agent architecture, and executes a task through a modularized intelligent agent. The system is composed of a man-machine cooperation interaction module, a global task management module, a general information retrieval module, a reverse path planning module, a protease modification module, a metabolic pathway optimization module, a wet experiment tool execution module and a code execution module. Each module integrates different tools and data sources for specific task fields. By means of the system, complex biosynthesis experiment design, planning and execution can be completed autonomously, functional modules and wet experiment feedback can be dynamically adapted, and the flexibility of experiment planning is ensured.

The utility model discloses an automatic charging cable take-up and pay-off device which comprises a charging gun, a motor mounting plate, a slip ring mounting plate, a cable guide piece, a gear motor, a spiral winding roll and a plurality of roller rotating shafts, and the motor mounting plate and the slip ring mounting plate are oppositely arranged at the two ends of the cable guide piece in parallel. A plurality of roller rotating shafts are oppositely arranged on the inner walls of the motor mounting plate and the slip ring mounting plate, the gear motor is mounted on the motor mounting bracket, the spiral winding roll is driven by the gear motor, a main body of a charging cable of the charging gun extends along the spiral groove, and the other end of the charging cable extends out of the spiral winding roll and is connected with the charging head. The device is compact in overall structure, small in occupied space, stable and safe, and the cables can be wound and unwound without manual intervention.

The invention relates to the technical field of holders, and discloses a self-stabilization holder searchlight tracking system, which comprises a holder autonomous stabilization subsystem, a tracking control subsystem and a searchlight subsystem, and is characterized in that the holder autonomous stabilization subsystem comprises a servo motor, a servo motor connecting arm, a servo controller and an attitude position sensor; one end of the servo motor connecting arm is fixedly connected with the servo motor, the other end of the servo motor connecting arm is fixedly provided with a fixing structure, and the top of the fixing structure is provided with a data transmission interface. According to the self-stabilizing pan-tilt searchlight tracking system, stable operation of a searchlight at different angles and in complex environments is achieved through the pan-tilt autonomous stabilizing system, the system can automatically adjust the direction and angle of the searchlight according to the position of a target, it is ensured that continuous tracking is conducted in the target moving process, and efficient illumination is provided; the design improves the precision of target tracking and the stability of illumination, and is suitable for various application scenes such as night monitoring, security patrol, search and rescue and the like.

The invention relates to an agricultural robot, and discloses an animal husbandry pushing robot autonomous navigation method based on a laser radar, which comprises a microsecond-level multi-sensor time synchronization architecture based on an FPGA (Field Programmable Gate Array); in a navigation layer, seamless switching between the GNSS and the laser SLAM is realized by constructing a virtual fusion observation value by utilizing extended Kalman filtering and a self-adaptive dynamic weight algorithm; in the sensing layer, an RGB-I multi-mode model fused with laser reflectivity and a biological micro-motion detection technology are adopted, and feed and biological obstacles are accurately distinguished; and in the execution layer, flexible self-adaptive material pushing is achieved in combination with material groove edge fitting and force-position hybrid control, and the navigation precision, the operation quality and the safety of the material pushing robot in the all-weather and unstructured pasture environment are effectively improved.

The invention discloses a database query plan optimization method and system, and belongs to the technical field of databases and artificial intelligence. AI model training: training the model by using the preprocessed historical query data according to a specific model architecture, a training mode and resource and time arrangement, and dynamically adjusting the model according to the change of the database; query analysis: evaluating the complexity of the query and the possibly involved data volume, and allocating a complexity level and a data access volume range for the query; query plan generation: generating and evaluating a plurality of candidate query plans based on prediction and query analysis results of the AI model, and selecting an optimal query plan as a final execution scheme; and performing query execution and monitoring. According to the method, the query execution time can be greatly shortened, and the database response speed is increased; system resources are utilized more effectively; dynamic changes of the database can be adapted, and the query plan is automatically updated according to structure and data distribution adjustment.

The invention provides a method and system for automatically generating a multilingual MOOC course based on recorded and broadcast courses, and relates to the technical field of digitization. Through the steps of intelligent noise reduction, voice recognition, voice recognition result correction, voiceprint training sample extraction, voiceprint model training and the like, multi-dimensional intelligent arrangement of courses and multi-language video synthesis are realized; comprising an intelligent noise reduction module, an intelligent voice recognition module, an intelligent voice recognition result correction module, an intelligent voiceprint training sample extraction module, a voiceprint model training module and a multilingual video synthesis module. The problems that in the prior art, when recording and broadcasting courses are converted into multilingual MOOC resources, a large amount of manpower and material resources are consumed, and rapid large-scale conversion cannot be achieved are solved; the recorded and broadcast course videos can be automatically converted into MOOC videos in different languages in batches without manual intervention, the robustness of the voiceprint model is improved, refined arrangement of course contents is realized, a large amount of manpower and material resources are saved, and rapid and large-scale course internationalization conversion is realized.

The invention discloses a batch task optimization method based on dynamic priority scheduling. The method comprises the steps of creating tasks, setting priority information of the tasks, adding the tasks into a scheduling queue of a task execution system, sorting the tasks according to an initial priority, scanning all the tasks in the scheduling queue at a set first time interval so as to obtain the priority of each task, performing resource data acquisition on the task execution system at a set second time interval to obtain a resource utilization rate of the task execution system, judging whether the resource utilization rate is lower than a corresponding safety threshold or not, if the resource utilization rate is lower than the corresponding safety threshold, controlling tasks with high initial priorities to be executed preferentially, and otherwise, controlling tasks with high initial priorities to be executed preferentially. And adjusting the initial priority of the task. The task sequence is dynamically adjusted according to the priorities and resource conditions of the tasks, so that the tasks with high priorities are processed preferentially, and the overall task processing efficiency and response speed are improved.