127results about How to "Achieve refinement" patented technology

The invention relates to the technical field of riverway desilting, in particular to a riverway self-adaptive desilting system and method based on intelligent water level perception, and the method is executed by a central control unit and comprises the four steps of model construction and benchmark calibration, real-time monitoring and siltation diagnosis, precise survey and operation planning and closed-loop execution and model synchronization. The system comprises a central control unit, a water level intelligent sensing array, terrain scanning equipment and dredging machinery, according to the method, the three-dimensional digital riverbed model is constructed, the sedimentation state is dynamically judged in combination with the water level sensing data, an accurate desilting operation scheme is generated, and operation closed-loop control is achieved. According to the method, navigation and ecological riverway dredging requirements are considered, the dredging precision and automation level are improved, the operation cost is reduced, intelligent transformation of riverway management is promoted, and an efficient solution is provided for long-acting treatment of the riverway.

The invention provides a wooden door three-dimensional model parameterization design and numerical control code generation method and system, and relates to the technical field of woodworking numerical control machining and computer vision. A multispectral imaging technology is adopted at a raw material feeding station to obtain a wood board surface multiband image, and a high-definition wood characteristic spectrum is generated through algorithm processing; establishing a mapping rule base of the atlas and numerical control parameters in combination with historical data; the map and the three-dimensional embossment model are superposed, and a tool path and cutting parameters are adaptively adjusted according to texture features to avoid defects and optimize along grains; and finally, numerical control codes matched with wood characteristics are generated, the rotating speed of the main shaft is adjusted according to the hardness, a numerical control machine tool is driven to complete high-precision wooden door machining, and precise numerical control machining based on wood surface characteristic intelligent recognition and self-adaptive adjustment can be achieved.

The invention relates to the technical field of smart tourism, in particular to a personalized scenic spot content generation method, system and device based on a multi-modal knowledge graph and a medium, and the method comprises the steps: collecting multi-modal data of a scenic spot, and constructing a structured multi-modal scenic spot knowledge graph based on the multi-modal data; obtaining personalized data provided by the tourist, and constructing a personalized portrait of the tourist based on the personalized data; in response to an operation of acquiring an image in a scenic spot, identifying the scenery in the image, and extracting a corresponding initial knowledge subset from the multi-modal scenic spot knowledge graph according to an identification result; performing personalized screening and expansion on the knowledge nodes in the initial knowledge subset by calculating the matching degree between the knowledge nodes in the initial knowledge subset and the tourist interest in the personalized portrait of the tourist, and dynamically binding multi-modal resources to generate a personalized knowledge graph; and presenting the personalized knowledge graph. According to the invention, the multi-mode scenic spot knowledge experience of which the structure is matched with the interest and the knowledge background can be provided for tourists.

This invention proposes an ESG-based comprehensive governance assessment method, electronic device, storage medium, and product for shipbuilding enterprises. The method includes: collecting multi-source ESG data and operational data from the shipbuilding enterprise during the assessment period; calculating state baseline parameters based on the operational data according to preset time slices; converting the multi-source ESG data into standard evaluation units and forming ESG vector data corresponding to the preset time slices; matching corresponding ESG assessment parameters from a preset ESG assessment parameter library based on the enterprise size, ship type, or production organization method; if no match is found, adaptively calibrating the ESG assessment parameters to obtain calibrated ESG assessment parameters; calculating governance efficiency indicators for each time slice based on the ESG vector data, state baseline parameters, and ESG assessment parameters; calculating a comprehensive ESG governance efficiency coefficient based on the governance efficiency indicators for each time slice; and obtaining the ESG governance assessment result based on the comprehensive ESG governance efficiency coefficient.

The invention relates to the technical field of intelligent evaluation of garment flatness, and particularly discloses an automatic evaluation method of a non-ironing suit seam flatness grade, and the method comprises the steps: obtaining image data and physical parameter data of a seam region in response to a detection trigger signal of the seam region of a non-ironing suit; and performing key scale screening based on texture contribution degree on the image data, calculating a relevance index between feature distribution and flatness grade probability distribution under different texture scales, and determining the texture scale of which the relevance index meets a preset contribution degree condition as a target key scale. According to the method, the entropy screening mechanism based on the texture contribution degree is introduced, so that the key scale which is most effective for flatness representation can be locked from the multi-source data in a self-adaptive manner, and the refinement and pertinence of feature extraction are realized.

A power plant cable whole life cycle monitoring method based on whole-process identification and mobile terminal code scanning belongs to the technical field of cable monitoring. The method constructs a four-layer architecture of "perception layer-network layer-platform layer-application layer", uses Ecode128 coding of GB / T31866-2023 standard as the unique identification of the cable, and realizes whole-process identification binding by combining two-dimensional code and digital character combination identification carrier. The mobile terminal code scanning is used to realize paperless collection of field data, which is uploaded to the management platform based on the SpringBoot framework through 4G / 5G / Wi-Fi / data line and other transmission modes. The platform adopts front-end and back-end separation design, the back-end integrates SpringMVC and MyBatis-Plus, and the front-end realizes visual display through Vue.js. The function modules of design, construction, operation and maintenance, state monitoring and retirement are developed and designed, and the whole life cycle digital closed-loop management of the cable from design to retirement is realized. The present application effectively solves the technical problems of information dispersion, low efficiency, single monitoring and extensive management in the traditional cable management mode, and significantly improves the fine and intelligent level of cable management.

The application relates to the technical field of chip design, in particular to an AI-based DDR5 memory interface chip adaptive method and system.The method comprises the following steps: obtaining a configuration instruction stream, extracting current and historical configuration instructions, and predicting target pins, switching time and target modes.Before the switching time, target electrical parameters are calculated according to pin electrical characteristics, historical switching records and channel load characteristics.During the switching, the target parameters are loaded and the temporary impedance matching network is switched in.After the switching, a fine-tuning increment is generated according to the deviation of the signal quality and the threshold value, and the updated electrical parameters are obtained by superposition, and the matching network is disconnected after the updated electrical parameters are written back to the register.According to the timing error and the fine-tuning increment generated by multiple switching, the weight parameters are updated and deployed back to the chip.Through AI prediction and the dynamic switching and fine-tuning of the temporary impedance matching network, seamless, stable and low-delay mode switching of the memory interface chip in the reconfigurable computing system is realized.

This invention provides an arc-based additive and subtractive manufacturing method based on interlayer morphology reconstruction, belonging to the technical field of metal additive manufacturing. The method includes depositing an Nth layer of metal material on a substrate to form a deposition layer with a natural wavy morphology; acquiring actual morphology data to identify peak and valley distribution characteristics and planning a subtractive manufacturing path; selectively turning the deposition surface to obtain an anti-wavy substrate; detecting the surface temperature field of the anti-wavy substrate and cooling or preheating the substrate; and repeatedly performing arc-based additive deposition of the N+1th layer on the temperature-controlled anti-wavy substrate to complete the additive manufacturing process. This invention solves the technical problem in existing technologies where the wavy morphology between layers is not addressed, resulting in subsequent deposition layers covering and permanently remaining inside the workpiece, leading to a reduced yield. It achieves the technical effect of suppressing interlayer defects, reducing porosity by 90%, and improving internal quality.

This application discloses an image processing method, apparatus, device, medium, and program product. The method includes: acquiring an initial image containing a target object, and performing pose torsion processing on the target object in the initial image to obtain a pose torsion image; fusing the pose torsion image and the initial image to obtain a fused image; extracting a part image containing a specified portion of the target object from the fused image, and performing image super-resolution processing on the part image to obtain a super-resolution part image; and fusing the super-resolution part image and the fused image to obtain a target image. Using this application embodiment can improve the quality of the target object after pose transfer.

This invention primarily relates to the field of efficiency measurement technology. To improve the automation and accuracy of efficiency measurement for transport vehicles, this invention provides an information-based efficiency measurement method and system for transport vehicles. Its core is to monitor the vibration threshold range of the vehicle under different operational processes. Based on the vehicle's real-time vibration values, the system determines the time the vehicle spends in different operational processes such as loading, transporting, unloading, and standby. It also acquires the vehicle's load under each operational process; calculates the vehicle's actual transport mileage based on the vehicle's real-time location and a set mileage correction coefficient; and finally, based on the time and load of the vehicle in different operational processes, as well as the actual transport mileage, determines the vehicle's total efficiency and the efficiency of the vehicle under each operational process. Through the coordinated acquisition and fusion calculation of vibration, load, and location data, the entire process of efficiency measurement for transport vehicles is made information-based.

The invention provides a municipal road maintenance demand prediction method and system based on machine learning, and relates to the technical field of machine learning, and the method comprises the steps: obtaining the service starting time of a municipal road and the passing frequency and full load proportion of heavy-load vehicles in a plurality of sampling periods; difference calculation is carried out on the service starting time and the sampling time points in each sampling period, and a space-time incidence matrix is constructed; taking an attenuation coefficient in the space-time incidence matrix as a dynamic regulation factor to obtain a bit stream sequence; mapping the bit stream sequence as an observation sequence to a preset road grid map, and determining an optimal transfer path through optimal path planning; and determining a grid step length for transferring the road state to the maintenance state at the current moment from the optimal transfer path, and determining maintenance demand prediction information comprising a maintenance priority and a predicted maintenance date. The precision, objectivity and foresight of municipal road maintenance demand prediction are realized.

The invention relates to the technical field of industrial equipment monitoring, in particular to a power equipment fault online monitoring system for polyester staple fiber production, which comprises a feature extraction module, a dynamic analysis module, an evolution prediction module, an anomaly recognition module, a feature construction module and a diagnosis matching module. The system collects operation data of power equipment in real time, extracts time sequence features and calculates a dynamic offset vector, and further predicts a state evolution track and identifies preliminary abnormality. The feature construction module traces back to extract feature fragments associated with the anomaly, fault component signals of different physical meanings are obtained through multi-level signal deconstruction and input into a fault feature spectrum generator, and a three-dimensional fault feature spectrum reflecting the fault evolution law is constructed. And the diagnosis matching module performs mode matching on the three-dimensional map and a preset fault knowledge base to determine a specific fault type and an evolution stage thereof. According to the method, early discovery of fault germination, accurate identification of fault types and dynamic judgment of fault evolution stages are realized.

This specification discloses a risk detection method and apparatus. The detection method, when detecting the risk of content itself, includes the following steps: First, the target content to be detected is input into a first large model to obtain a first prediction result, which indicates that the target content is high-risk, low-risk, or has an undetermined risk status. Next, in response to the first prediction result indicating an undetermined risk status, the target content and related risk discrimination rules are input into a second large model to obtain a second prediction result, which indicates a risk type to be detected or that the target content is low-risk. Then, in response to the second prediction result indicating a risk type to be detected, a third large model corresponding to that risk type is invoked to process the target content and related context information to generate a target risk detection result.

This invention relates to the field of chip inspection technology, and more particularly to a chip non-destructive testing system based on embedded current scanning. The system includes a current scanning module, an information acquisition module, a data analysis module, an abnormal scanning region generation module, and a scanning path generation module. Instead of simply performing a higher-density secondary scan of the entire chip, this invention intelligently filters out abnormal scanning regions requiring special attention based on the initial scan results and calculates their scanning priority. This allows valuable inspection time and computing resources to be concentrated on the most suspicious and severe areas, avoiding unnecessary repeated scanning in normal areas. The system dynamically selects the optimal scanning path based on the regularity of the region shape; for example, parallel lines are used for regular regions, and radial lines are used for irregular regions. This makes the scanning path more closely match the geometric features of the defect, obtaining a more complete region characterization with fewer scanning points, resulting in higher path planning efficiency.

The invention discloses a method and system for detecting the internal quality of a polyethylene pipeline hot-melt welding joint, and belongs to the technical field of pipeline quality detection.The method comprises the following steps that before a tensile test is carried out, ultrasonic quality detection is carried out on a casual inspection joint of a polyethylene pipeline set to be detected; dynamically determining an initial tensile rate based on the material grade and the material attribute parameter of the to-be-tested polyethylene pipeline group, and executing a first tensile test at the initial tensile rate; iteratively and dynamically adjusting the tensile rate of the tensile test of the next casual inspection joint based on the tensile test result of the previous casual inspection joint until the tensile test of each casual inspection joint is completed; dynamically executing fracture quality detection based on the fracture position and the fracture characteristic parameter of each spot check joint to obtain a fracture quality detection result of each first joint; and executing internal quality comprehensive detection based on the ultrasonic quality detection result, the fracture quality detection result and the tensile test result of each first joint.

The application discloses a ground wire insulator deicing starting decision method, and belongs to the technical field of power system transmission line ground wire icing monitoring and insulation safety evaluation. The application obtains ground wire basic parameters and design ice thickness, calculates ground wire equivalent icing thickness based on tension monitoring data before and after icing, establishes a correlation model of ground wire equivalent icing thickness and ground wire insulator icing thickness, combines air gap length of the ground wire insulator, environmental monitoring information and icing discharge characteristic formula, realizes quantitative evaluation of ground wire insulator ice flashover probability, and compares the ground wire insulator ice flashover probability with preset threshold value in combination with ground wire icing alarm information, to provide accurate starting criterion for deicing of the ground wire insulator covered with ice. The application significantly improves the pertinence, accuracy and safety of ground wire icing monitoring, and is suitable for icing risk evaluation and early warning of various ground wires and ground wire insulators.

The invention relates to the field of intelligent power grids and intelligent fusion terminals, in particular to a transformer health monitoring system based on an intelligent fusion terminal TTU, and the system comprises a waveform data collection module which is used for collecting the waveform data of a transformer; the environment data acquisition module is used for acquiring operation environment data of the transformer; the denoising and reconstruction module is used for carrying out denoising elimination and waveform reconstruction on the waveform data of the transformer; the feature extraction module is used for performing feature extraction, enhancement and fusion on the preprocessed waveform data and the operation environment data of the transformer to obtain a fusion feature vector; the state analysis module is used for inputting the fusion feature vector into a mixed regression model for health state prediction to obtain a transformer health index prediction value; and the TTU decision module is used for matching the control decision scheme and controlling the working state of the transformer. According to the invention, the accuracy and reliability of transformer health prediction and the reliability of overall operation of a power grid can be improved.

This application provides a third-party monitoring method for road transport safety management, including: a monitoring platform determining the status of a vehicle entering or exiting an assigned electronic fence based on vehicle satellite positioning data, and generating a regional alarm when a vehicle crosses the boundary or violates speed limits; executing a verification and processing procedure for various alarms generated by the monitoring platform, including platform alarms and proactive safety alarms, supporting enterprise users to appeal the verification results and subsequent review; marking the status of vehicles in special states such as being out of service, under maintenance, scrapped, or suspended from monitoring, and providing abnormal movement records and offline duration statistics queries; pushing announcement documents to subordinate enterprises or initiating safety inspection tasks, and requiring enterprises to submit reading receipts or inspection responses; generating statistical reports on daily, weekly, monthly, and yearly cycles, and supporting scheduled automatic or instant push to designated email addresses.

A multifunctional boxed tobacco strip detection trolley comprises a trolley body, a box holding mechanism, an electric mechanical arm, a weighing mechanism, a control system and a flat plate. A box body is arranged above a chassis of the vehicle body, and a control system is arranged in the box body; the electric mechanical arm is arranged above the box body, the bottom of the electric mechanical arm is connected with the control system, and the other end extends out of the box body and is selectively connected with the sampling device, the punching insertion rod or the temperature measuring rod; the box holding mechanism is arranged on one side edge, close to the electric mechanical arm, of the box body; the weighing mechanism comprises a wireless separated platform scale and an independent panel, the platform scale is placed in the box body, and the independent panel is arranged above the box body and used for displaying weighing data; the panel is arranged at the top of the box; and the control system controls the electric mechanical arm to a position required by temperature measurement punching or sampling, and guides the punching and sampling device to punch at a central temperature measurement point or sample at quartering points. The invention provides a multifunctional boxed tobacco strip detection trolley which is small in occupied area, flexible to move and capable of realizing multi-item detection.

The application provides a seven-day period factory cyclic Megalobrama amblycephala fry behavior domestication method and system, relates to the Megalobrama amblycephala breeding technical field, and includes: domesticating the fry into a domestication pond on the first day; starting vertical water flow impact before feeding fresh bait fish according to a preset first feeding frequency on the second day; feeding electric shock disabled live bait according to a preset second feeding frequency on the third day; feeding mixed live bait according to a preset third feeding frequency on the fourth day; feeding mosaic bait according to a preset fourth feeding frequency on the fifth day; feeding pure artificial compound feed using a composite feeding mode and starting water flow impact on the sixth day; feeding pure artificial compound feed on the seventh day, and screening domestication successful individuals based on behavior indexes after the period ends, so that the Megalobrama amblycephala is rapidly domesticated from feeding live bait to feeding artificial compound feed.

The application discloses a high-temperature fractured rock mass permeability simulation method under multi-field coupling, and relates to the technical field of geotechnical engineering, which comprises the following steps: building an initial fracture network according to structured data sets, assembling an HTMC variable parameter operator library and establishing operator selection and weighting rules to form a multi-field coupling model package; in the multi-field coupling model package, calling the HTMC variable parameter operator library according to a multi-field state quantity vector to obtain a multi-field solution, calculating a fracture connectivity criterion and a threshold, forming an event trigger quantity, and summarizing the multi-field solution and the event trigger quantity into a field solution trigger quantity; determining an event trigger state in the fracture network according to the field solution trigger quantity, executing local reconstruction, updating the fracture network, generating a new fracture network and local parameter change information, and obtaining a network parameter change package; and the application realizes real-time perception and adaptive update of dynamic changes of fracture network connectivity, and enhances simulation timeliness and prediction reliability.

The invention provides a cast-in-place box girder pre-camber automatic regulation and control method and device. The device comprises a first-stage jacking system, a second-stage jacking system, a third-stage jacking system and a transverse moving system. After the pouring maintenance of the current span box girder is completed, the hydraulic oil cylinders of the first-stage jacking systems of the front and rear main supporting legs retract, the whole machine falls down, and the formwork is demoulded; the hanging outer rib is disconnected, a three-stage jacking system oil cylinder at the top of the cross beam retracts, and a transverse moving system is started to achieve mold opening; the whole machine moves forwards by one span, and the jacking amount is adjusted according to the longitudinal slope of a main beam through a front and rear main supporting leg first-stage jacking system; correcting the section position of the template through a three-stage jacking system at the top of the cross beam, and controlling the bottom die to be positioned at the same elevation; a transverse moving system is started to complete outer mold bottom plate connection, and the actual position line of the mold plate is determined; calculating to obtain the elevation adjustment amount of the outer mold of each block based on an influence matrix method, and performing synchronous and automatic regulation and control by utilizing a secondary jacking system, so that a template system reaches a designed pre-camber line position; the problems that the pre-camber regulation and control efficiency of a traditional cast-in-place box girder movable formwork is low, errors are uncontrollable and the like are solved.

The application discloses a motor temperature control method based on environment monitoring and belongs to the technical field of motor temperature control, which comprises the following steps: S1, multi-source data synchronous acquisition: the working temperature T1 of a motor body, the environment temperature T2 of an environment where the motor is located, the running current I of the motor and the heat dissipation state signal S representing the state of a heat dissipation system are synchronously acquired in real time, the heat dissipation state signal S is the temperature of a radiator, the flow of cooling liquid or the rotating speed of a heat dissipation fan, S2, multi-source temperature coupling analysis and feature extraction: based on the real-time data collected in step S1, coupling calculation is performed to generate an environment normalized temperature rise index and a heat balance deviation index for representing the abnormal state of the system heat, S3, fault root cause discrimination and classification: the environment normalized temperature rise index and the heat balance deviation index calculated in step S2 are used for fault root cause discrimination and classification. The application realizes the motor temperature control based on environment monitoring, realizes the transition from fuzzy perception, extensive control to accurate diagnosis and can realize intelligent intervention.

A video forwarding system based on ROS2 and WebRTC comprises a data acquisition and publishing module used for acquiring image data and publishing the image data to a corresponding ROS2 topic; the multi-process streaming pushing module is used for creating an independent streaming pushing sub-process for each path of video stream needing to be forwarded outwards and sending the video stream to the streaming media forwarding module; the streaming media forwarding module is used for receiving the independent video stream from the multi-process streaming pushing module and forwarding the video stream to a user terminal according to a user subscription relationship; the signaling and process management module is used for receiving an external instruction from a user side and dynamically creating or destroying the corresponding streaming pushing sub-process according to the instruction; and the user terminal module is used for sending an instruction to the signaling and process management module and subscribing and receiving the video stream from the streaming media forwarding module through the WebRTC technology. The method has the advantages of extremely low end-to-end delay, extremely low remote equipment resource occupation, strong expandability and flexibility and the like.

The invention provides a match management method and system and a storage medium. The method comprises the steps of receiving a match creation request, obtaining a match data set of a to-be-created match type, and classifying the match data set to obtain a match scale data set and a resource demand data set; inputting the match scale data set into a match schedule management model, processing match scale parameters by using a first feature extraction layer in the match schedule management model, and generating match schedule structure data; inputting the resource demand data set into a resource management model, processing the resource demand parameters by using a second feature extraction layer in the resource management model to obtain a resource type, and processing the resource type through a feature reconstruction layer to generate a resource configuration scheme; and creating a match management scheme according to the match schedule structure data and the resource configuration scheme, and managing the match according to the match management scheme, thereby realizing refined and intelligent management of the match.

The present application relates to the technical field of video monitoring, and particularly relates to a multi-scene-oriented monitoring management method and system, comprising: acquiring basic feature data of a scene monitoring area, performing scene configuration based on the basic feature data, constructing a multi-dimensional error dynamic compensation calibration strategy in combination with error data, performing precision calibration on the scene configuration to obtain a configuration scheme; constructing a hierarchical permission management and control strategy according to the configuration scheme, anchoring the right of ownership of monitoring full-quantity data and generating a unique identifier, completing dynamic right establishment in combination with operation subject attributes and operation requirements, and establishing permission flow and verification rules; collecting scene multi-source monitoring data, establishing a unified data storage structure in association with the unique identifier, and generating multi-source fusion data; and based on the multi-source fusion data, constructing an abnormal dynamic correlation domain, and completing abnormal disposal in combination with the hierarchical permission management and control strategy. The present scheme eliminates multi-dimensional errors through multi-dimensional error dynamic compensation calibration, and improves the collection accuracy and scene adaptability.

This invention relates to the field of medical supplies technology, specifically to an intelligent transfer cabinet for body fluid specimens. The cabinet comprises a cabinet body, a partitioned storage system, a control unit (i.e., an industrial-grade main controller), and a communication and control execution module. The cabinet body is integrally formed from 304 stainless steel and includes multiple physically isolated specimen storage areas and a low-temperature storage area. The main controller, based on an ARM Cortex-A series processor and equipped with an embedded system, serves as the core for managing all modules. The communication module enables data interaction with the hospital information system, and the control execution module, controlled by the main controller, centrally manages the electromagnetic locks and status indicators of each storage compartment door. This invention achieves standardized and intelligent temporary storage and transfer of body fluid specimens, improving management automation and reliability, and ensuring storage hygiene and safety as well as the integrity of information management.

This invention discloses a method and system for constructing emotional curves for children's autism risk assessment, relating to the field of image and video processing technology. The method includes the following steps: acquiring a sequence of facial video images of the test subject watching an emotionally stimulating video; extracting facial action unit (AU) feature values ​​and macroscopic behavioral features from the facial video image sequence; calculating the dynamic weight coefficients of each feature in the multimodal feature set based on predefined effect sizes and significance levels; calculating the emotional intensity score at each time point based on the dynamic weight coefficients and real-time AU feature values, and generating an emotional curve through temporal smoothing; extracting feature indicators from the emotional curve to characterize abnormal emotional responses in autism, conducting autism risk assessment based on these feature indicators, and outputting the results. This achieves refined and dynamic modeling of the test subject's emotional responses, providing quantifiable and interpretable auxiliary diagnostic evidence for early autism screening.

The utility model discloses a horn installation structure and an electronic device, the horn installation structure comprises a housing, the housing is provided with an installation groove, the groove bottom of the installation groove is provided with a sound outlet hole and a waterproof strip, the sound outlet hole penetrates through the groove bottom of the installation groove, the waterproof strip is arranged along the outer side of the sound outlet hole for a circle, and the waterproof strip is arranged on the outer side of the installation groove. The waterproof strip and the shell are integrally formed; and the loudspeaker is adaptively arranged in the mounting groove, the loudspeaker is provided with a clamping piece, a clamping part is arranged at a corresponding position of the shell, and when the clamping piece is adaptively clamped with the clamping part, the loudspeaker extrudes the waterproof strip, so that the loudspeaker is hermetically connected with the groove bottom of the mounting groove. According to the utility model, the required space is small, the waterproof effect is good, the assembly is simple, and the first pass yield of the production process is improved.

The invention provides a ship lock operation scheduling system and method based on big data analysis, and relates to the technical field of ship lock operation scheduling. By integrating big data analysis of historical operation data, ship priority evaluation, real-time navigation state monitoring and intelligent prediction, refinement, dynamics and intelligence of ship lock scheduling are achieved, the overall traffic efficiency is remarkably improved, and congestion of a lock area is effectively relieved. Low-efficiency links are identified through clustering analysis, congestion points are captured in real time in combination with a space thermodynamic diagram, and a declaration time period and interval time are dynamically adjusted, so that the adaptive capacity of the system to abnormal conditions such as load change, severe weather and equipment faults is enhanced; differentiated services and green channel support of high-priority ships are realized, and key transportation requirements are guaranteed; and upstream and downstream ship lock linkage scheduling is realized through a network cloud platform, and a neural network model is utilized to generate an optimization scheme containing a lockage sequence, suggested arrival time and a coordination instruction to improve watershed navigation collaboration.