22results about How to "Realize dynamic analysis" patented technology

The invention discloses an intelligent safety management method and system for a highway service area, and the method comprises the steps: recognizing the number of vehicles in the service area, and obtaining historical flow data and analysis data corresponding to the historical flow data; identifying the types of vehicles entering the service area, obtaining parking space data of parking areas corresponding to different types of vehicles, and guiding the vehicles to parking spots; safety monitoring is carried out on the vehicles of the focus type in the recognized vehicle types; and pushing the data to a manager. Through accurate identification of the number and types of vehicles entering a service area and combination of historical vehicle conditions of the service area, dynamic analysis of vehicle flow data can be realized, optimal distribution of parking resources in advance is realized, congestion caused by too many vehicles is avoided, and meanwhile, real-time monitoring and early warning of key vehicle types are realized, so that the service area is more intelligent. Safety accidents can be found in time at the beginning, and expansion of the accidents is avoided.

The invention provides an intelligent power grid safety early warning system and a monitoring method in the technical field of intelligent power grids, which are used for solving the problem of safety early warning and monitoring function defects of the existing imperfect intelligent power grids, and comprise an information acquisition unit, a data management unit, an abnormity analysis unit and a safety early warning unit, the method comprises the steps of collecting power grid real-time data and line equipment data; constructing an adjacent matrix and a target matrix, calculating and analyzing to obtain a node weight and a target correlation degree, and analyzing by using a discrete model to obtain a dispersion index; a data evaluation value is obtained, and a data abnormal value is obtained through analysis; and generating intelligent power grid safety early warning information and a disaster recovery strategy according to the data abnormal value and the line equipment data. By constructing an intelligent power grid monitoring and early warning system, power grid equipment with potential safety problems is predicted in real time, the operation and maintenance efficiency is improved, the method can be suitable for power grid systems of different scales, the influence of faults on power grid operation is reduced, and large-area power failure events are effectively prevented.

The invention discloses a hospital safety production operation management ecological platform, and relates to the technical field of hospital safety production management and control. According to the hospital safety production operation management ecological platform, the risk checking module is utilized to call the industry standard risk library to comprehensively identify all potential risk points in a target hospital and carry out preliminary risk rating, and the risk factor identification module analyzes and identifies events influencing risks, so that the risk factor identification module carries out risk assessment on the events. The risk factor identification module identifies risks, the risk control measure module adopts corresponding control measures according to the identified risks, the risk factor identification module and the risk control measure module output risk change indexes through the event analysis decision module, and finally, the corresponding risk control measures are dynamically adjusted according to updated risk levels. Therefore, continuous optimization of hospital safety production and effective risk control are ensured. The core of the system is that dynamic monitoring of hospital safety production and adjustment of control measures are realized through standardized and systematized risk management.

The invention relates to the technical field of global war game deduction, in particular to a global hexagonal war game map deformation analysis method and system based on a dynamic comprehensive deformation index, and the global hexagonal war game map area deformation analysis is carried out based on a lattice area standard deviation. Performing global hexagonal war chess map shape deformation analysis based on the adjacent distance standard deviation; introducing a cell area average value and a cell adjacent distance average value, and proposing a grid area deformation index and a grid shape deformation index; and constructing a dynamic comprehensive deformation index by using the grid area deformation index and the grid shape deformation index, and carrying out overall deformation analysis on the area deformation and the shape deformation of the HGWM. According to the method, the dynamic comprehensive deformation index is put forward to carry out overall measurement on the deformation of the HGWM, and the limitation that deformation analysis is carried out only through area difference and perimeter difference is made up; by dynamically adjusting the weight variable, the dynamic analysis of the overall deformation degree of the grid is realized, and a more suitable global hexagonal war chess map is selected for different types of global war chess deduction.

The application discloses a temperature compensation method based on thermal imaging of a machine tool ram, and relates to the technical field of machine tool thermal error compensation; the method comprises the following steps: installing a temperature measurement thermal imager and establishing a thermal distribution model, calculating thermal deformation amounts in three directions, obtaining a deformation correction error sequence, constructing a compensation error prediction model, determining an error compensation opportunity, and executing a progressive compensation strategy; two-dimensional temperature distribution data is obtained by the thermal imager, high-precision temperature distribution fields are generated by combining three-dimensional mapping technology, the theoretical deformation amounts in each direction are quantified based on an integral method, and dynamic analysis of multidimensional thermal deformation amounts is realized; meanwhile, an error correction amount is predicted in advance based on a time sequence prediction model of an LSTM network, combined with working condition parameters such as an environmental temperature and a spindle speed, active compensation is realized, a multi-condition triggering mechanism and a priority are set at the same time, and compensation at a suitable opportunity is ensured; a progressive compensation strategy avoids overcompensation or undercompensation, and a threshold alarm mechanism is combined to improve the robustness of the system.

The present invention discloses a management method for electrolytic copper additive production equipment. The electrolytic cell and electrolyte data are collected through a monitoring module, and a prediction model based on random forest is constructed in combination with product detection defect information. The model integrates the linear change characteristics of the electrolytic cell and electrolyte monitoring data, uses the CART algorithm to independently train decision trees, and predicts production defects through a voting mechanism. In real-time production, the pre-processed monitoring data is imported into the model to predict defects, and the defect categories are analyzed through the prediction results and the additive ratio is dynamically adjusted to achieve real-time optimization and adjustment of electrolytic copper production. Through the present invention, multi-dimensional real-time monitoring and analysis of electrolytic copper production and precise quality prediction can be achieved, dynamic analysis and regulation of additive schemes can be achieved, and production efficiency can be improved.

The invention discloses a road network analysis system related to intelligent traffic, and relates to the technical field of intelligent traffic, and the system comprises a traffic road network range determination module, a road network analysis module, a control personnel processing end, a driving personnel client and a driving recommendation module. Comprehensive acquisition, dynamic analysis and accurate early warning of traffic data are realized; the system can calculate a congestion risk coefficient and an accident risk coefficient of a road in real time, identifies and manages a high-risk road based on a traffic safety index, and quickly sends early warning information to control personnel and driving personnel to guarantee the smoothness and safety of the road; particularly, the driving recommendation module provides a safe and efficient driving path for the user through a path optimization technology in combination with real-time road condition data, so that the driving experience and the operation efficiency of the traffic system are greatly improved.

The invention discloses a fish in-situ video processing method and device, and the method comprises the steps: carrying out the image quality evaluation of a collected video, and screening out an effective video frame; identifying the category, bounding box and mask information of each fish individual in the video through an instance segmentation technology; calculating the instantaneous swimming speed of the fish instance by using a monocular relative depth estimation technology and combining reference object information and a computational photography principle; and the extracted fish instance information is edited and corrected through an interactive labeling function. The device comprises an in-situ video acquisition and preprocessing module, a multimedia resource management module, a video frame granularity multi-sensor data structured binding module, an instance granularity biological feature association module and an interactive labeling module, and the functions of video frame capture, screening, multi-modal data binding, biological feature association and interactive labeling are achieved. According to the method, the problems of low effective frame density and single data dimension in traditional video analysis are effectively solved, and comprehensive and accurate technical support is provided for fish ecological research.

The application relates to the technical field of emergency management, and discloses a multi-information fusion disaster accident emergency knowledge pushing method, which comprises the following steps: collecting multiple types of disaster related data and preprocessing, and constructing a unified emergency information dataset; inputting the dataset into a pre-constructed time-space-cause three-in-one state transition model to obtain disaster accident scenario evolution data; generating a unified scenario feature vector through a three-level fusion architecture; generating a candidate knowledge set through a thinking chain reasoning combined with an emergency knowledge graph and a pre-trained emergency large model; sorting the candidate knowledge in combination with a disaster scenario, a rescue task and a user role; and performing multi-terminal directional pushing. The application improves the scenario adaptability, multi-source information fusion efficiency and reasoning accuracy of emergency knowledge, realizes personalized pushing of the emergency knowledge, and provides scientific and efficient support for emergency rescue decision-making.

The invention discloses a petroleum drilling machine space safety analysis system which comprises a processing unit, and the input end of the processing unit is connected with an image recognition unit, a storage unit and an operation and display unit. The output end of the processing unit is connected with an alarm unit and a third-party device, and the processing unit can detect and track a specific object in the image recognition unit, collect spatial information, model a spatial relationship and create a physical world charting expression; according to the security analysis method, the specific object feature model needing to be analyzed is input into the processing unit, the distance threshold parameter is set in the operation unit and the display unit, and the content of the storage unit is checked if the content needs to be played back, so that the three-dimensional space security of a certain area can be dynamically analyzed without human intervention; when the distance between specific objects is smaller than a set value, early warning is carried out, measures are automatically taken, and meanwhile high adaptability to different background environments is achieved.

The application provides a kind of factory multi-device beat coordination control method and system, applied to data processing field, specifically specially applicable to the data processing of supervisory purpose;The application constructs beat sequence by real-time operating parameter of processing equipment, and further establishes multi-device beat coupling topological network, realizes the dynamic analysis of beat correlation and disturbance propagation process between multi-devices, compared with the local speed regulation mode of traditional single-device beat, can identify the propagation path and propagation trend of beat disturbance between multi-devices through beat fluctuation frequency, phase difference and buffer oscillation frequency etc. Beat oscillation characteristics, and accurately locate the source device of beat disturbance in combination with preset phase lead relationship, to avoid periodic amplification of beat fluctuation in production line.

This application discloses a method, apparatus, device, and storage medium for adapting the UI layout of an in-vehicle device, relating to the field of vehicle engineering and applied to a target in-vehicle device. The method includes: launching a target application to be adapted on the target in-vehicle device; using the target application to read a target configuration file locally on the target in-vehicle device and parsing the target configuration file to obtain the corresponding parsing results; the target configuration file is a JSON configuration file; adjusting the UI components of the target application based on the parsing results, and adapting the business logic corresponding to the adjusted layout based on the logical rules in the target configuration file to obtain the corresponding target layout; initiating a display request for the adapted layout using the target application; restarting the target application based on the request result to display the main activity interface of the target application based on the target layout. This application achieves efficient and flexible dynamic adaptation of UI and business logic across multiple platforms using a single codebase.

The invention discloses a method and system for predicting shale oil reservoir crustal stress and formation pressure, and the method comprises the steps: analyzing the geologic structure characteristics of a target region according to logging data and seismic data, thereby constructing a three-dimensional geologic structure model, then obtaining a stress field, formation pressure, rock mechanics parameters and reservoir physical property parameters of each single well in the target area, and forming a three-dimensional rock mechanics and physical property parameter attribute body in combination with the three-dimensional geologic structure model so as to construct a three-dimensional geomechanical model; constructing a finite element geologic structure model based on the three-dimensional geomechanical model, further constructing an attribute parameter field in combination with the parameter attribute body, and forming a coupling seepage physical field based on the attribute parameter field in combination with a preset boundary condition so as to establish a four-dimensional ground stress and formation pressure model; and performing seepage-stress coupling iterative calculation on the four-dimensional ground stress and formation pressure model to obtain a corresponding prediction result. The shale oil reservoir ground stress and formation pressure can be accurately predicted.

This invention discloses a lossless compression transmission method and system for narrowband channel data based on power protocols, belonging to the field of communication technology. The method includes: acquiring the original message from the power terminal; identifying the IEC 60870-5-101 / 104 protocol, stripping application layer protocol data units and extracting the core payload; constructing a dynamic mapping dictionary to map high-frequency protocol control information as short-byte indices; performing adaptive differential prediction based on recursive least squares on telemetry data to generate a differential residual sequence; performing adaptive arithmetic coding on the residual sequence to generate a compressed data stream; monitoring the length of the compressed data, and if it exceeds the narrowband channel payload limit, performing secondary fragmentation and adding a header containing sequence numbers and priority markers. This invention achieves high-rate lossless compression of power protocol data, effectively adapts to narrowband satellite channels, and significantly improves the reliability and situational awareness capabilities of power emergency communication in extreme environments.

The application relates to a planetary gearbox fault diagnosis algorithm automatic generation system and method based on a large language model, which comprises the following modules: a large language model generation module, which is used for receiving prompt words, selecting parent planetary gearbox fault diagnosis algorithm and architecture component knowledge, and combining with the characteristics of the planetary gearbox fault diagnosis task to call the large language model to generate new planetary gearbox fault diagnosis algorithm code; a dynamic code execution and verification module, which is used for code execution and verification; an architecture evaluator module, which is used for training and performance evaluation; an intelligent evolution strategy module, which is used for analyzing the training history and obtaining an analysis result; a program database module, which is used for storing and managing the population of the planetary gearbox fault diagnosis algorithm and constructing prompt words; and an evolution control engine, which is used for coordinating and controlling the work processes of the modules and controlling the number of iterative evolutions to realize evolution circulation. Compared with the prior art, the application has the advantages of automatic generation, iterative evolution and the like.

The invention provides an intelligent forest tree breeding method based on multi-modal data and a large model, and relates to the technical field of forest tree genetic breeding. The method comprises the steps of obtaining and integrating genotype data, phenotype data, multi-omics data and environment time sequence data of a target tree species, and performing preprocessing and feature fusion to form a multi-modal data set for analysis; on the basis of the multi-modal data set, key genes or gene modules for regulating and controlling target characters are mined by adopting a genotype-environment interaction algorithm and multi-omics coupling analysis; constructing a dynamic model fusing genotypes, environmental factors and time dimensions, and predicting breeding values of individuals or combinations on a whole genome level based on mined key genes or gene module information; and based on a prediction result, performing multi-objective optimization and intelligent screening at three levels of parents, combinations and offspring, and outputting a breeding decision scheme. According to the method, a complete, efficient and accurate forest tree intelligent breeding solution is formed.

The invention provides a refining production process management and control system, method and equipment and a storage medium, and belongs to the field of refining process management. The system comprises a data acquisition module used for acquiring index data of a refining process; the key index data monitoring module is used for analyzing and managing the process index data to obtain a process analysis result; the alarm evaluation optimization module is used for evaluating and managing the alarm index data to obtain an alarm evaluation result; the control loop evaluation and diagnosis module is used for evaluating and optimizing the control loop index data to obtain a control loop evaluation result; and the evaluation module is used for determining the stability of the refining process based on the process analysis result, the alarm evaluation result and the control loop evaluation result. According to the invention, real-time monitoring, dynamic analysis and comprehensive research and judgment on the production process of the refinery enterprise device can be realized, and the method has a very positive effect on improving the stable operation level and automation, digitization and intelligence levels of the enterprise process.

The invention discloses an IT informatization double-model operation and maintenance management method based on a multi-layer data lake, and the method comprises the following steps: collecting IT operation and maintenance related data from a plurality of data sources in real time, and carrying out the correlation processing, and forming a multi-layer operation and maintenance data network; the multi-layer operation and maintenance data network is embedded into a data lake through a layering technology to form a multi-layer operation and maintenance data lake, and rapid access and calling of large-scale operation and maintenance data are carried out through a multi-layer interface; performing big data analysis on the called data, completing accurate filtering of the data, extraction of key features and deep combination, and obtaining a plurality of key performance evaluation state quantity sets; inputting the state quantity set into an operation and maintenance identification model to identify potential factors which may cause system problems and performance bottlenecks; automatically adjusting IT resource configuration through an operation and maintenance adjustment model based on the potential factors so as to optimize the system performance and improve the resource utilization rate; and dynamically displaying the identification result and the adjustment result. The operation and maintenance efficiency and the system stability are remarkably improved.

The present invention discloses a method for evaluating the results of microplastic pollution control, which belongs to the technical field of pollution assessment, and specifically comprises: using unmanned aerial vehicles to automatically collect ground images of rural areas, identifying cultivated land areas in combination with cultivated land planning maps, and detecting plastic pollutants in cultivated areas and non-cultivated areas respectively, so as to count the total plastic pollution amount N and the total amount of plastic pollution in cultivated areas m; through multiple data collections, a line graph of N and m changing with time is drawn, and then the cultivated land pollution status and the trend of pollution diffusion are analyzed; at the same time, the system can identify the types of crops in the cultivated land, and calculate the pollution amount Pi per unit area of ​​each type, and construct the pollution index Q of the cultivated land in combination with the pollution weight ω and the slope k; when the Q value exceeds a preset threshold, the system will automatically issue a warning; the present invention helps to prevent the pollution problem from worsening and realize active intervention and effective control of microplastic pollution.

The present invention relates to the technical field of water conservancy project inspection and scheduling, specifically to a detection robot inspection and scheduling management system and method based on the Internet of Things, in which a risk inspection monitoring point analysis module in the system combines the positions between different monitoring points in the corresponding water conservancy project and the collaborative relationship between the various monitoring points involved in the historical control process of the corresponding water conservancy project to generate indirect associated monitoring points corresponding to each element in the direct associated monitoring point set, and construct a risk inspection monitoring point set for the corresponding water conservancy project. In the inspection and scheduling process, the present invention not only realizes the dynamic construction of the risk inspection monitoring point set through the operating status data of the monitoring points, the impact of rainfall changes on the water level of the water conservancy project, and the collaborative relationship between the various monitoring points involved in the historical control process; it also takes into account the location of the detection robot to realize dynamic analysis and accurate screening of the inspection scheduling plan, and realizes effective management of the inspection and scheduling of the detection robot.

This invention discloses a remote smart meter reading method and system, specifically relating to the field of smart meter reading. It addresses the problem that existing remote smart meter reading methods rely solely on address fields and frame verification for response confirmation, making it difficult to identify abnormal responses, equipment aging, and coupling loop drift in complex power line environments. By extracting the synchronization convergence fingerprint vector during carrier synchronization establishment and the current transient feature vector during response frame transmission, a dynamic correspondence between communication synchronization behavior and electrical transient behavior is constructed. Topology preservation comparison is performed on the current response pulse, and the trajectory is predicted based on the inferred current transient feature vector from historical meter reading records. A homogeneity determination result is generated by combining the trajectory deviation and transient topology preservation degree. Simultaneously, a dynamic coupling stability sequence is constructed to achieve stable uploading of remote smart meter reading results and anomaly identification, improving the automation level of meter reading management and user service experience.

The present invention provides a multi-task scene understanding method based on a graph attention network. The method includes the following steps: collecting data and annotating and recording to obtain a multimodal data set; obtaining the category information of all objects based on the multimodal data set; then finding the relative position information of each object and converting it into global position information, while adding the current time environmental information to generate a comprehensive data representation; designing preset rules to generate a scene model; using the loss function and the graph attention neural network to iteratively train the scene model, obtain a trained scene model and perform a variety of scene analysis tasks, and infer the overall situation of the scene through the scene analysis results. The present invention can improve the efficiency of multimodal data fusion, simplify the data alignment and synchronization processing process, fully integrate and analyze environmental information, enhance the global scene understanding ability, and perform a variety of scene understanding tasks at the same time, so as to achieve comprehensive perception and intelligent reasoning of complex scenes.