62results about How to "Improve real-time response performance" patented technology

The invention provides a multi-agent cooperation system, which comprises a multi-agent cooperation engine module, a task decomposition and distribution module and a tool calling normal form module, and is characterized in that the task decomposition and distribution module is used for decomposing tasks and distributing decomposed sub-tasks to agents; the multi-agent cooperation engine module is used for managing cooperation and communication between agents; and the tool calling module enables the intelligent agent to dynamically call different tools. According to the multi-agent collaboration system, the collaboration efficiency among the agents, the flexibility of task decomposition, the adaptivity of tool calling and the intelligent level of user interaction are remarkably improved, and remarkable technical advantages and effects are shown in complex task processing and dynamic environment processing.

The invention discloses a network security threat monitoring method and system based on artificial intelligence, and relates to the technical field of digital information transmission, and the method comprises the steps: obtaining data of a plurality of data sources in a network environment, carrying out the multi-level data fusion of the data through an artificial intelligence model, and forming unified data representation; the artificial intelligence model comprises at least one selective fusion layer, and features are extracted from different data sources and are jointly expressed; based on a data fusion result, performing anomaly detection by adopting an unsupervised learning method; and modeling the network flow data into a graph structure according to the detected abnormal behavior, and analyzing the graph structure by adopting a graph neural network GNN. According to the method, the technical problems of difficulty in multi-dimensional data fusion, delay in threat detection, insufficient response capability and the like in the existing network security protection technology are solved.

The invention provides an abnormal street lamp detection system and method based on a YOLOv8 model, the system comprises an image acquisition module, a target detection module and an abnormal street lamp identification module, the image acquisition module is used for acquiring a monitoring image on a road in real time, the target detection module adopts the YOLOv8 model to carry out target detection on image data, and the abnormal street lamp identification module is used for identifying the abnormal street lamp. Identifying a street lamp area in the image, positioning a street lamp in the image and marking the position of the street lamp; and the abnormal street lamp identification module analyzes the detected street lamp state by using image features, performs multiple times of abnormal detection on multiple street lamp images collected in the same time period by adopting a multiple-time identification strategy, and judges a final result through a voting mechanism, thereby identifying the abnormal street lamp. According to the invention, automatic detection and state analysis are carried out on the street lamps by using the YOLOv8 model, so that real-time monitoring and identification of abnormal street lamps are realized, and the intelligent management level of an urban road illumination system is improved.

The invention relates to an intelligent fund routing system based on an AI large model and an optimization method thereof, and belongs to the field of finance, and the system comprises a data processing module which is used for automatically collecting financial market data, and carrying out the preprocessing and feature extraction; the decision forming module is used for analyzing the processed data and performing fund routing decision based on an AI model architecture; the fund routing optimization module is used for optimizing a fund routing path according to market and user behavior prediction results; the risk assessment module is used for monitoring transactions and fund flow directions in real time and assessing potential risks; and the risk management integration module is used for carrying out early warning and decision support according to the risk assessment result. The method has the advantages that the efficiency is improved; the safety is enhanced; the precision is improved, and the deep learning model can better predict the market trend and the user behavior.

The invention relates to the technical field of intelligent positioning, in particular to an intelligent positioning system and positioning method applied to a spraying robot, and the positioning system comprises a light field data acquisition module, a particle tracking calculation module, a sound wave precision distance measurement module and a dynamic verification execution module. According to the method, the operation environment of the spraying robot is sensed in an all-around mode through synthesis of a multi-sensing technology, the accurate position of the spraying head is updated through a strategy of capturing light field data in real time and accurately calculating particle dynamics, the spraying precision is ensured, the real-time response capacity to environment changes and the dynamic adjusting capacity of the spraying process can be greatly improved, and the spraying quality is improved. The material waste is reduced, the coating quality and the production efficiency are improved, sound wave precise distance measurement is added, the robustness and reliability of the system in a complex industrial environment are enhanced through sound wave and light field information fusion, precise tracking is combined with real-time position adjustment, and it is ensured that the spraying quality reaches the optimal quality every time.

The invention discloses a metro crew scheduling plan compilation optimization method and system based on an algorithm, relates to the technical field of metro scheduling, and is used for solving the problem that a conventional metro crew scheduling system is not timely in peak allocation. In the prior art, traffic roads are directly matched with aircrafts one by one, but the adaptability between the traffic roads and the aircrafts is not fully considered, and optimization is not carried out aiming at special requirements in peak hours. In the peak period, the demand is far greater than that in the low peak period, more aircraft shifts are possibly needed for support, and in the peak period, the important demand is that the route and the aircraft shifts with high matching degree need to be preferentially matched. According to the method, through matching optimization of the route and the locomotive crew and combination of historical passenger flow data, efficient subway team scheduling is achieved, and it is ensured that the shift demand in the peak period is preferentially met.

The invention relates to the technical field of torque calculation, in particular to a torque adaptability regulation and control method and system for an electric power-assisted bicycle, and the method comprises the steps: receiving a torque regulation instruction, starting a system regulation unit based on the torque regulation instruction, collecting a side-sway angle and a side-sway angular velocity, calculating transmission delay, and if the transmission delay is not in a delay range, starting the system regulation unit; if the transmission delay is within the delay range, screening the transmission data packet set to obtain a standard data packet set and an over-limit data packet set, adjusting the over-limit data packet set to obtain an adjusted data packet set, and obtaining an integrated data packet set based on the standard data packet set and the adjusted data packet set; and if not, calculating an external interference estimated value, calculating a side-sway angular acceleration by using the external interference estimated value, calculating a side-sway torque and an offset torque, calculating a regulation and control torque according to the side-sway torque and the offset torque, and completing torque adaptive regulation and control according to the regulation and control torque. According to the invention, the regulation and control speed and accuracy of torque adaptive regulation and control can be improved.

The invention discloses a panoramic monitoring system based on a digital twinning technology, and the system comprises the steps: triggering an abnormal following mechanism when an event driving unit detects a marking event through monitoring equipment; according to an exception following mechanism, the edge collaboration unit calculates a scheduling instruction; and the view angle control unit is dispatched through the dispatching instruction, and the monitoring view angle of the monitoring equipment is adjusted, so that panoramic monitoring is realized. Based on an event driving unit and an abnormity following mechanism, abnormal events are automatically identified and tracked, intelligent following and visual angle dynamic adjustment of a target are realized, and the monitoring efficiency is improved. Through an edge cooperation strategy and a visual angle control unit, seamless connection of the visual field of monitoring equipment is realized, a blind area is eliminated, continuous tracking of a marking event is ensured, and the comprehensiveness and the real-time performance of monitoring are improved. The edge cooperation unit carries out distributed calculation through the edge nodes, reduces the load of the central server, reduces the delay, and improves the real-time response capability of the system.

The invention discloses a dynamic flexible workshop scheduling method based on an event-driven DDQN algorithm. The method is used for solving the problem of flexible order workshop dynamic scheduling under the condition that a new order is inserted. The method comprises the following steps: firstly, considering the condition of random insertion of a new order, establishing a dynamic FJSP mathematical model taking minimization of total tardiness as an optimization target, converting the dynamic FJSP mathematical model into a multi-stage decision process based on event driving, and carrying out Markov decision process modeling of a scheduling problem; then seven key state characteristics such as machine utilization rate are designed, five composite scheduling rules are designed to form an action space, and a reward function is designed according to the variable quantity of part of the state characteristics; in addition, a soft epsilon greedy behavior strategy is designed according to the problem scale, and exploration and utilization are reasonably balanced. Through simulation research on a plurality of production scheduling examples, the result shows that the method can effectively cope with a dynamic event of random insertion of a new order, the total delay time is remarkably shortened, and good performance is shown in the aspects of convergence speed and solving efficiency.

The invention discloses a voltage active and reactive dynamic cooperative control method considering communication quality. The method comprises the following steps: establishing a voltage reactive power dynamic cooperative control model, obtaining reactive power compensation amount of each node photovoltaic inverter in real time under the condition of considering communication network time delay and packet loss, and performing voltage reactive power dynamic cooperative control on a power distribution system; establishing a voltage active power dynamic cooperative control model, when the voltage reactive power dynamic cooperative control does not relieve the overvoltage condition of the power distribution system, obtaining the electric vehicle charging power increment of each node in real time under the condition of considering communication network time delay and packet loss, and performing voltage active power dynamic cooperative control on the power distribution system; and when each node of the power distribution system does not detect the overvoltage in the preset time period, performing cooperative control on the real-time voltage of the power distribution system through an active and reactive backoff mechanism. According to the method, optimal control over the inverter and the electric vehicle can be achieved in the environment with poor communication quality, and the voltage out-of-limit risk caused by high-permeability photovoltaic grid connection is avoided.

The invention belongs to the technical field of underwater acoustic communication reconnaissance and artificial intelligence edge computing, and discloses a sea area signal reconnaissance method and device based on deep learning. According to the method, a constructed lightweight LeNet-5 hierarchical convolutional neural network model is embedded and deployed into an STM32H743 microcontroller through an X-Cube-AI tool to process underwater acoustic signals, automatic identification and classified modulation are performed on underwater signals of active sonar signals and non-cooperative communication signals in real time, and the underwater signals are used for analysis of recovered sea area information. According to the method, deep-level features can be automatically learned from the time-frequency graph, better robustness is achieved for noise and a complex marine environment, and the recognition accuracy is higher.

This invention relates to the field of equipment training technology, and discloses an electro-dynamic feedback device and design method for virtual training, including the following steps: Designing an arm-worn force feedback device based on a DC servo motor; establishing a mapping relationship between virtual environment interaction information and physical feedback force by deriving a mathematical model of feedback force and servo motor rotation angle; designing a phase displacement-torque dual closed-loop control system, controlling the servo motor rotation angle through a phase displacement closed loop and controlling the servo motor output torque through a torque closed loop to achieve precise control of the feedback force amplitude; using the mathematical model and the dual closed-loop control system, driving the arm-worn force feedback device to generate feedback force matching the virtual training scene, achieving rapid response to virtual collisions, and keeping the feedback force and rotation angle error within a preset threshold to enhance the realism and immersion of virtual training. Establishing a mapping relationship between virtual interaction and physical feedback enables precise control of the servo motor rotation angle and output torque.

The application belongs to the technical field of artificial intelligence driven system design optimization, and discloses a training course planning service method and system. A quantum principal component analysis module is used to extract a correlation feature matrix of scene fluctuation parameters and resource demand, a quantum Fourier transform is used to analyze system health degree attenuation signals, and dynamic scene features are generated. A parameter tuning instruction set is constructed based on a quantum annealing algorithm to drive a genetic algorithm to optimize the topology. A quantum superposition state mapping is used to distribute micro-optimization units to a digital twin platform, and a variation quantum algorithm is used by a collaborative verification module to solve resource multiplexing strategies to form a data closed-loop feedback link. The application solves the problem of static data and dynamic demand mismatch, and improves real-time responsiveness and resource optimization efficiency in complex scenarios.

The invention relates to a real-time intelligent operation and maintenance system framework for a large-scale terminal, and belongs to the field of operation and maintenance systems. A terminal equipment layer; the data acquisition layer is responsible for real-time acquisition and transmission of underlying data and is used for data input of a large-scale terminal system; the edge computing layer is an adjusting and deploying layer of the system, provides a bridge function between a terminal and a cloud end, and is used for enhancing real-time performance and expandability; the cloud platform layer is responsible for calculation processing of the system and is responsible for global analysis, optimization and coordination, the cloud platform layer is a core for realizing intelligent operation and maintenance, elastic expansion is realized through a micro-service architecture, dynamic access of terminal equipment and rapid allocation of tasks are supported, the risk of a single point of failure is avoided through a cooperative processing mode of edge calculation and a cloud platform, and the operation and maintenance efficiency is improved. And the overall reliability and stability of the system are improved.

The application provides a multi-layer satellite network distributed routing method and system, the method comprising: dividing a low-orbit satellite set into multiple low-orbit satellite regions, each low-orbit satellite region corresponding to at least one medium-high-orbit satellite as a regional control node; multiple medium-high-orbit satellites cooperatively generating an exit selection strategy for each low-orbit satellite region and issuing the exit selection strategy to the corresponding low-orbit satellite region; low-orbit satellites in a low-orbit satellite region taking the corresponding exit selection strategy as an inter-regional forwarding constraint and performing hop-by-hop autonomous forwarding in the low-orbit satellite region; and multiple medium-high-orbit satellites updating the exit selection strategy for each low-orbit satellite region based on updated regional network state. The multi-layer satellite network distributed routing method and system of the application can reduce the frequency of cross-region path reconfiguration while retaining the real-time response capability of hop-by-hop routing, thereby enhancing the overall stability and scalability of the system.

This invention relates to the field of concurrent data processing technology in embedded operating systems, and particularly to a hierarchical fair spinlock control method based on queue distance awareness. The method includes the following steps: the processor initiates a mutual exclusion access request for shared resources; reads the idle / available flag stored in the lock; if the flag is valid, the processor directly acquires the lock through an atomic comparison and exchange operation; if the flag is invalid, the processor atomically increments the pending ticket number stored in the lock to generate a ticket number held by the processor; reads the current service ticket number stored in the lock, and calculates the difference between the processor-held ticket number and the current service ticket number to obtain the queue offset. This invention, while maintaining the fairness and determinism of spinlocks, enables safe execution in various modes including tasks, interrupts, and exceptions, while reducing cache consistency overhead in multi-core concurrent scenarios, improving lock scalability, and providing lock state detection capabilities.

The application provides a communication method, an electronic device, a storage medium, a power supply, a lamp and a lighting system. The communication method is applied to a host computer, the host computer is connected with a plurality of slave computers, and the method comprises the following steps: a broadcast packet is sent to all the slave computers, the broadcast packet is used to indicate that the host computer is ready to extract information; after the broadcast packet is sent, a plurality of first cycles are performed; the plurality of first cycles are ended, and a plurality of information packets are accepted, the information packets are from the slave computers which have a message sending intention; wherein the first cycle comprises the following steps: a plurality of reporting identifiers are received, the plurality of reporting identifiers are from a subset of all the slave computers which have a message sending intention; an identification is formed according to the plurality of reporting identifiers, and the identification is sent to the slave computers in the subset. When the number of slave computer devices is large, the real-time response capability of the host computer is improved, and the experience of the master-slave system is optimized.

The invention discloses a multi-modal heterogeneous data increment embedding fusion method, equipment and a medium, mainly relates to the technical field of multi-modal heterogeneous data, and aims to solve the problems of difficult neighborhood structure maintenance, insufficient cross-modal information fusion, single and fixed index structure and the like in the existing scheme. Comprising the following steps: converting modal data in a multi-modal heterogeneous data set into hidden space representation, and fusing the hidden space representation by utilizing a cross-modal attention mechanism to obtain historical embedding representation of a preset d dimension; when the newly-added multi-mode heterogeneous data set appears, calculating a newly-added embedding representation of a preset d dimension; according to the newly-added multi-modal heterogeneous data set, the newly-added embedding representation, the historical multi-modal heterogeneous data set and the historical embedding representation, constructing an adjacency relation graph of the newly-added multi-modal heterogeneous data set; and inputting the adjacency relation graph into a pre-trained incremental graph neural network to obtain an embedded representation fusing the adjacency relation.

The application discloses a kind of multi-modal event primitive extraction, coding and collaborative generation method and system for smart engineering construction scene, the system includes multi-modal data acquisition module, edge preprocessing module, event candidate extraction module, time-space alignment module, subject association module, event primitive coding module, multi-source fusion generation module and primitive output module. Through edge pre-processing, candidate event extraction, time alignment, space mapping, subject association, unified coding and multi-source fusion to video, environmental parameters, device status, positioning information, wearable terminal data and job log data and other multi-modal raw data, generate standardized event primitives, and output to risk identification, knowledge graph and early warning module. The present application can reduce the transmission pressure of raw data, improve the unified semantic expression ability of multi-source heterogeneous data, the fusion accuracy and the subsequent risk analysis efficiency, suitable for hoisting, high altitude, closed space and warehousing logistics and other smart engineering construction scenes.

The application discloses a kind of low-altitude logistics hub facing in and out field connection and supplement energy chain collaborative control method. Build task-unmanned aerial vehicle-take-off and landing position-supplement energy unit-route window heterogeneous association graph and resource linkage constraint state diagram;Using HRG-MambaNet to the heterogeneous association graph executes relationship coding and time sequence state joint modeling, and according to the relationship, the task connection direction, resource release order, supplement energy switching and route window redistribution range are implemented linkage constraint, form candidate control scheme, and delay, power deviation, window mismatch and supplement energy continuous connection deviation are written back to constraint state diagram structure as the input of next control time;Under the disturbance trigger, construct mismatch propagation inhibition boundary according to local subchain reconstruction threshold, only the local subchain of mismatch in boundary is reconstructed, and the in and out field connection, supplement energy chain switching and take-off and landing position release result are output. Compared with prior art, the application can improve the scheduling coordination, control stability and anti-disturbance ability in the operation process of low-altitude logistics hub.

The present disclosure relates to a headlamp system for a moving object and an operating method thereof, and more particularly, a headlamp system for a moving object can be provided, which includes a controller configured to generate light pattern information based on external environment information, and a light output device including a plurality of light sources and outputting a road projection image generated based on the light pattern information, wherein the controller calculates the light pattern information based on the external environment information and provides the light pattern information to the light output device, the light pattern information being data about an image of an update region that has changed compared to a previous road projection image.

The present invention relates to the field of file management technology, and in particular to a Hive small file management method, the method comprising: setting an initial cleaning cycle, regularly cleaning the generated small files to obtain regular cleaning results; real-time monitoring of the generation of small files, and determining whether the small files are abnormal based on the generation; determining the abnormality level of the small files based on the abnormality of the small files; determining a small file management strategy based on the abnormality level, and determining a management score based on running the small file management strategy; calculating an overall performance score based on the regular cleaning results combined with the management score; adjusting the initial cleaning cycle based on the overall performance score, or optimizing the management strategy. The present invention reduces the need for manual intervention, improves efficiency, avoids the accumulation of small files and performance degradation, and ensures the efficient operation of the management process through comprehensive management from regular cleaning to performance scoring to strategy optimization.

This application provides a transformer fault identification method and system based on hydrogen content anomaly characteristics, relating to the field of power equipment condition monitoring and fault diagnosis technology. The method includes: constructing a hydrogen content time series, extracting amplitude features, change rate features, and trend morphology features to achieve multi-dimensional characterization of the hydrogen change process and improve the ability to identify early abnormal signals; simultaneously, constructing a multi-gas discrimination feature set based on abnormal mode types combined with auxiliary feature gas detection data and gas ratio relationships to achieve multi-source gas information fusion analysis and enhance the ability to distinguish different fault types; further, generating early warning information based on fault identification results and health status assessment results to achieve linkage between fault diagnosis and risk early warning, improving the accuracy, stability, and online monitoring capabilities under complex operating conditions.

The present invention belongs to the technical field of optical modules, and relates to an optical module based on an embedded operating system and a working method thereof. An embedded operating system is transplanted into the MCU of the optical module, and the CMIS protocol and / or user-defined functional tasks are executed through the embedded operating system; the architecture of the optical module includes an application layer, a kernel layer, and a hardware abstraction layer; the kernel layer schedules and processes the tasks defined in the application layer to control the hardware abstraction layer; the kernel layer adopts an embedded operating system kernel, specifically: an embedded operating system is transplanted into the MCU of the optical module. By introducing the embedded operating system kernel into the optical module MCU, real-time operating system support for high-speed optical modules is achieved; and based on the task scheduling and priority management capabilities of the embedded operating system, high real-time response capabilities of optical modules at 400G, 800G and higher rates are achieved.

The invention discloses a multi-master-device-oriented global bandwidth scheduling and priority control method and system, and the method comprises the steps: forming a complete end-to-end scheduling system through a software marking mechanism, network-on-chip real-time monitoring, initiating end adaptive adjustment, transmission path adjustment and a master memory controller cooperation strategy; and dynamic management of multi-service flow access behaviors is realized. In the system, a software layer configures initial strategies for different data streams; the main equipment end dynamically adjusts the priority of the sent request based on the real-time load; the network-on-chip carries out secondary adjustment on the priority based on the congestion state of the transmission path; the main memory controller maps the request to different queues for execution according to the final priority; and the system feedback layer collects the overall performance state and feeds back the overall performance state to the software layer so as to dynamically update the strategy. According to the method, software and hardware collaborative and adaptive global bandwidth management is realized, and the overall performance and service quality of the complex system on chip are remarkably improved.

This invention proposes a method, apparatus, equipment, and storage medium for simulation training of ship section construction. It achieves the construction of a high-performance virtual reality simulation environment, supporting collaborative interaction across multiple terminals such as VR, PC, and CAVE, significantly improving the system's adaptability and interactive immersion. Through a multi-user network synchronization architecture and workstation-level dynamic simulation scene construction, it realizes the realistic restoration of section construction process logic and operational synchronization, improving collaboration and training realism. Employing a multi-level detail model and dynamic mesh optimization technology based on view distance and bounding box overlap rate effectively reduces the rendering load of complex scenes and improves the system's real-time response performance. By establishing a multi-projection plane world coordinate system and real-time viewpoint matrix calculation, it achieves consistent rendering across multiple terminals. Combined with workstation cycle data synchronization and an operation scoring mechanism, it forms a quantifiable training evaluation system, thereby comprehensively improving the efficiency, safety, and scientific rigor of ship section construction training.

The invention discloses a fault detection method based on a fusion network, and relates to the technical field of fault detection of industrial equipment. The convolutional neural network model carries out local feature extraction and sliding window operation on time series data of equipment through a convolutional layer to capture a local mode and a change trend, and the Transform module helps the CNN model to capture global dependency relationship features in the time series data through a self-attention mechanism; the bidirectional gating recursion module considers forward and backward information of time series data at the same time and captures front and back dependency relationship characteristics, introduces the cross attention mechanism module to carry out characteristic fusion, and compresses the characteristics into fixed-length characteristics through adaptive average pooling mapping. The processed features are classified through a full connection layer, and prediction results of fault categories are output; according to the fault detection method based on the fusion network, the feature information of the industrial equipment can be automatically extracted, and the intelligence and the accuracy of the equipment are improved.

The present application relates to a kind of method and device for the distributed scene engine of vehicle, the method includes: obtaining the context information of vehicle;Current scene where vehicle is located is judged to be comprehensive scene or pure in-vehicle scene based on context information and predetermined rule set;When current scene is judged to be comprehensive scene, in-vehicle scene signal is generated for in-vehicle scene in comprehensive scene based on context information;And in-vehicle scene signal is sent to cloud server.

The invention discloses a network intrusion tracing method and system based on behavior analysis, and relates to the technical field of network security. The method comprises the following steps: S1, constructing an attack activity propagation graph and calculating an attack propagation coefficient between nodes; s2, according to behavior data and attack propagation coefficients of each node in the attack activity propagation graph, calculating behavior pulse factors of the nodes, and determining attack participation nodes; s3, calculating a time propagation coefficient of an attack path and constructing an attack time trajectory according to interaction time difference characteristics and behavior pulse factors among the nodes; s4, according to the flow rate, the attack propagation coefficient and the time propagation coefficient between the nodes, calculating a traceability flow overflow index, and generating a potential attack source set; and S5, calculating an attack intensity adjustment coefficient according to the traceability flow overflow index and the flow rate, and triggering a defense strategy response mechanism based on the attack intensity adjustment coefficient. Precise traceability and real-time defense are realized through multi-dimensional behavior analysis, and the network intrusion response efficiency is improved.

Embodiments of the present application provide a fluid flow field analysis method, an analyzer and an analysis system. The method is applied to a fluid flow field analyzer, which includes a plurality of ultrasonic transducers for mounting outside a measuring pipeline, and the plurality of ultrasonic transducers are distributed along a circumference. The method comprises: controlling each ultrasonic transducer and at least one of the other ultrasonic transducers to form at least one ultrasonic transducer pair according to a scanning mode; acquiring propagation time and distance information between the ultrasonic transducer pairs corresponding to N ultrasonic transducer pairs; determining a fluid flow rate of a path where the ultrasonic transducer pair is located according to the propagation time and the distance information corresponding to the ultrasonic transducer pair for any one of the plurality of ultrasonic transducer pairs; and determining a cross-sectional flow rate trend according to the fluid flow rates of the paths where the N ultrasonic transducer pairs are located. The method can directly capture transient flow field changes so as to enable an operator to measure and analyze the flow field online.