1161 results about "Dynamic management" patented technology

The invention relates to the technical field of intelligent power grids, in particular to a power distribution network battery digital dynamic management system based on digital twinning. Comprising a data acquisition unit; the digital twinborn modeling unit is used for constructing a battery-power grid-environment multi-dimensional dynamic twinborn body and realizing virtual-real bidirectional mapping and adaptive updating by combining a multi-physics field coupling model and a long-short-term memory network time sequence prediction algorithm; a dynamic optimization unit; and executing the feedback unit. Through a distributed heterogeneous sensing network of a data acquisition unit, multi-dimensional operation data of a battery pack and a key node of a power distribution network are acquired, and a high-fidelity data set containing four-dimensional labels of a battery state, a power grid parameter, time and a position is generated in combination with a spatial-temporal feature extraction technology; the deep fusion of the full life cycle state of the battery and the global operation data of the power distribution network is realized, and the comprehensive data support covering the global is provided for the optimization decision.

An AI orchestration system dynamically manages multiple artificial intelligence (AI) agents within a cloud computing environment to efficiently process user requests. A model orchestration subsystem determines whether a request is handled locally using a domain-specific database or by invoking one or more AI agents. The system maintains AI agents in active and inactive states, provisioning computing resources for inactive agents as needed. Real-time model metrics guide the selection of target AI agents, and if a degrading performance trend is detected, the system preemptively spins up additional AI instances. The system provisions processor cycles, memory, and network bandwidth through a cloud-based resource manager, instantiates containerized execution environments or virtual machines, and performs automated load balancing among AI instances.

The invention relates to a steel logistics full-process real-time dynamic management method and device, and belongs to the technical field of steel logistics control methods and devices. According to the technical scheme of the invention, data acquisition and monitoring are carried out, and transport vehicle and cargo states are tracked; demand prediction and inventory dynamic adjustment are carried out, and high-frequency cargo response emergency orders are allocated according to shipment frequency; visual management of the supply chain is carried out, shared data of all links of the supply chain is established, a 3D logistics map is constructed, and inventory, transportation states and bottleneck nodes are displayed in real time; and risk control management: quickly starting the alternative scheme when the early warning is triggered. The method has the advantages that efficiency is optimized, limitation of a traditional single transportation mode is reduced, rolling updating and emergency response of demand prediction are achieved, data transparency and credibility are improved, rapid risk response is achieved, and logistics full-life-cycle management is achieved.

The invention discloses a battery full life cycle intelligent management method and system based on a large model, and the method comprises the following steps: S1, collecting the operation data of a battery, and carrying out the preprocessing; s2, inputting the pre-processed sample into a pre-trained Transform encoder model, and extracting a time sequence and cross-stage characteristics; s3, executing model reasoning, outputting a state index, and generating a battery state vector; s4, identifying an abnormal category and a position in combination with the working condition information; s5, generating a dynamically optimized battery management strategy based on the battery state index and the abnormity identification result; s6, deploying a lightweight model at the edge device, executing local reasoning and uploading data; s7, the cloud updates the model through self-supervised training and issues the model; and S8, repeatedly executing the steps S1 to S7, and carrying out optimized closed-loop management. According to the invention, large model modeling and an edge cloud cooperation mechanism are fused, and intelligent sensing and dynamic management of the whole life cycle of the battery are realized.

The invention discloses an intelligent land engineering carbon sink regulation and control system and method based on dynamic management, and belongs to the technical field of land engineering carbon sink regulation and control. The multi-source spatio-temporal data comprises vegetation indexes, soil parameters, meteorological data and carbon dioxide flux data; the data processing and analyzing module is used for performing fusion processing on the multi-source spatio-temporal data, inverting and calculating the carbon sink or carbon source state of the target area in real time based on a built-in carbon sink accounting model, and generating a carbon sink spatio-temporal distribution diagram; the intelligent decision-making module is used for diagnosing a carbon sink capacity limiting factor based on the carbon sink space-time distribution diagram and generating land engineering regulation and control strategies for different sub-regions; and the execution and feedback module is used for issuing the regulation and control strategy to an execution terminal or a management platform. The method improves the carbon sequestration capacity and regulation and control efficiency of land engineering.

The invention is suitable for the field of GPU management, and provides an intelligent dynamic management method for GPU computing power and a cloud platform, and the method comprises the following steps: collecting task data and GPU state data, and generating a task queue and a resource allocation strategy in combination with a scheduling plug-in; based on the task queue and the GPU real-time load, dynamically adjusting a resource allocation proportion through reinforcement learning to analyze a task dependency relationship and generate a migration plan; optimizing a communication path and adjusting asynchronous transmission delay according to the task dependency relationship and the GPU communication topology, and outputting a synchronous state mark; and monitoring abnormity in combination with the synchronization state and the GPU hardware state, executing thermal migration according to the migration plan, performing video memory recovery, and updating the resource idle list. According to the invention, through algorithm innovation and hardware collaborative optimization, intelligent, dynamic and efficient resource scheduling in the multi-GPU system is realized.

The invention discloses a multi-source data fusion type intelligent data management system, which comprises a data preprocessing module used for accessing a heterogeneous data source and generating a standardized data frame; the cognitive sub-graph construction module is used for generating cognitive sub-graphs and forming a cross-source evolutionary multi-cognitive hypergraph; the event aggregation module is used for aggregating entities and relationships according to event fingerprints and outputting a multi-source observation chain; the causal checking module is used for performing causal comparison and conflict detection and outputting a checking result, a positioning report and a treatment suggestion; the fusion updating module is used for distributing weights and performing weighted fusion, outputting fusion representation and confidence score, recording conflicts and updating the hypergraph; and the memory pool module is used for storing the hypergraph, the check result and the fusion representation, executing weight adjustment, forgetting and elimination, and outputting a service interface. According to the method, intelligent fusion and dynamic management of multi-source heterogeneous data are realized by constructing a cross-source self-evolution multi-cognitive hypergraph and an active evolution type fusion memory pool.

The invention relates to an LLM-based power distribution network knowledge graph construction and fault intelligent diagnosis method. The method comprises the steps of constructing a knowledge system, constructing a normal operation state model and an anomaly detection threshold value, performing fault diagnosis through an LSTM-BP cascade network, and performing fault classification. The abnormal parameters and the fault classification result are input into an LLM model, the fault type is judged, corresponding diagnosis information is obtained, and the system generates a scheduling instruction and an emergency decision suggestion according to the diagnosis information; and generating a detailed diagnosis report. According to the system, statistical analysis and deep learning algorithms are adopted for operation parameters such as voltage and current after preprocessing, and automatic detection and fault classification of abnormal parameters are realized in combination with a CNN recognition module; a preset rule base in the knowledge system is combined to accurately determine a fault type, generate a scheduling instruction and an emergency decision suggestion, and assist operation and maintenance personnel in rapid response and dynamic management; finally, a detailed diagnosis report is generated, thereby improving the fault handling efficiency and the guarantee capability of safe and stable operation of a power grid.

The invention belongs to the technical field of authority management, and particularly relates to a dynamic authority management system based on an integrated system, which is characterized in that on one hand, dynamic authority portraits of employees are described periodically by integrating multi-system data, and dynamic risk values of real-time operation behaviors of the employees are analyzed based on the latest dynamic authority portraits; on the other hand, through monitoring an organization event queue in real time and analyzing metadata of an event message, an organization event type is identified, a change rule corresponding to the organization event type is matched, an authority synchronization instruction is generated, and transactional operation is started; a behavior risk real-time assessment and event-driven cross-system collaboration mechanism is adopted, automatic and precise dynamic adjustment of the authority is realized, the access control security and management efficiency in an integrated network environment are improved, and in addition, a self-optimization capability based on machine learning is introduced, so that the authority management has the characteristics of continuous learning and evolution.

The invention relates to the technical field of engineering cost control, and discloses an engineering cost control method and system based on big data. The method comprises the steps of collecting engineering project full-cycle cost data streams, and generating a standardized cost data set through data cleaning; constructing a dynamic cost feature library, and extracting multi-dimensional features such as time sequence fluctuation, resource allocation discretization and supplier association; inputting the feature library into a cost anomaly detection model constructed by a pre-training deep learning network, outputting a cost deviation index, and triggering a correction instruction if the cost deviation index exceeds a threshold value; matching historical cases to generate an optimization strategy set containing material replacement, construction period adjustment and supplier replacement; and virtual deduction is carried out on the optimization strategy through an engineering digital twin system, and the strategy with the predicted cost curve closest to the target value is screened as a final execution scheme. The method depends on big data and a deep learning technology, full-cycle dynamic management and control of the engineering cost are achieved, and the precision and feasibility of cost control are improved.

According to the permanent basic farmland quality intelligent monitoring system and method provided by the invention, accurate monitoring and dynamic management are realized through multi-module cooperation, the terrain gradient and canopy height are calculated based on LiDAR point cloud, the complexity index is generated in combination with meteorological data, and the A * algorithm is improved to optimize the unmanned aerial vehicle inspection path. The method comprises the following steps: extracting hyperspectral data to analyze soil and crop states, calibrating an electrode response curve, calculating a bio-availability index in combination with temperature and humidity, dynamically adjusting an early warning threshold value, identifying abnormal data by adopting an isolated forest algorithm and carrying out grading processing, and constructing a space-time cube by adopting space-time Kriging interpolation and CNMF algorithm and fusing multi-source data. According to the method, indexes such as ecological protection grades and economic values are integrated to generate a graded soil quality index model, a disease thermodynamic diagram is generated, key data are stored in a chaining mode, and farmland quality real-time monitoring, risk early warning and ecological economic balance decision making are achieved through multi-source heterogeneous data fusion, dynamic weight optimization and block chain technologies.

The invention belongs to the technical field of information interaction, and relates to a device information interaction method, a slave device gateway and a master device. An active frame transmission mechanism is realized through the slave device gateway, so that the slave device actively reports information to the master device when the state changes or the trigger condition is met, and the master device can analyze and issue a configuration instruction in real time to complete dynamic management of the slave device. The method supports centralized monitoring and configuration of slave devices in the parallel operation energy storage system, ensures the consistency of device identifiers, addresses, groups and states, realizes real-time, accurate and extensible management, does not interfere with the original Modbus master-slave communication process, and effectively solves the problems of poor expansibility, state update lagging, communication conflict risk and the like in the traditional one-master one-slave mode.

The invention relates to the technical field of precise motion control, in particular to an XY motion platform positioning error compensation system and method, which extracts spatial-temporal characteristics through multi-modal data fusion and normalization processing in combination with a neural network hybrid model, and dynamically manages time sequence errors by using a forgetting gate, an input gate and an output gate. And a compensation parameter is updated by adopting an online adaptive training mechanism of error source classification. The problems that in the prior art, due to mechanical abrasion and thermal deformation of an encoder, precision is attenuated, nonlinear errors are difficult to process through a PID algorithm, pure vision positioning is prone to interference and complex in calibration, and an online learning mechanism is lacked can be effectively solved, the positioning comprehensive error is reduced to the micron order, the anti-interference robustness and the real-time compensation capacity of a system are improved, and the system reliability is improved. And the positioning precision and the production efficiency are obviously improved.

The invention discloses a park multi-source heterogeneous data analysis method and system based on the industrial Internet of Things, and relates to the technical field of data analysis. The park multi-source heterogeneous data analysis method based on the industrial Internet of Things comprises the following steps: determining a suspected target according to image information of a target area; according to the moving trend of the suspected target, predicting a moving path of the suspected target, and obtaining feature information of the suspected target through supervision equipment on the moving path; according to the feature information and in combination with working data of the suspected target in a past preset time period, predicting an abnormal probability of an abnormal condition of the suspected target, and judging whether the abnormal probability exceeds a preset threshold value or not; and if the abnormal probability exceeds a preset threshold value, tracking the abnormal target. The technical problems that in the prior art, due to data islands and response mechanism lagging, accurate risk identification and dynamic management and control in a complex industrial scene are difficult to achieve, and false alarm or missing alarm is likely to occur are solved.

The invention discloses an RISC-V vector register pressure-oriented dynamic management method and system, and relates to the technical field of computer processor architecture and compiler optimizing.The method comprises the steps that in the program compiling or executing process, the use state of an RISC-V vector register is monitored in real time, and when it is monitored that the vector register pressure exceeds the limit, the RISC-V vector register pressure is monitored; if yes, selecting a target register and triggering a management strategy; identifying a source instruction of a vector value in the target register, executing heavy materialization validity verification, and dividing the vector value into a heavy materialization type and a non-heavy materialization type according to a verification result; according to a division result, dynamically estimating the heavy materialization cost and the register overflow cost; comparing the two types of costs, and if the heavy material cost is higher, deciding to adopt a register overflow strategy and executing the strategy; and if the overflow cost of the register is higher, a decision is made to adopt a heavy matter strategy and is executed. The computing performance of the processor can be improved, and the problem of performance loss caused by high register pressure is solved.

The invention relates to the technical field of waste gas treatment, and particularly discloses a dynamic management method and system for industrial waste gas treatment, and the system comprises a region division module which is used for dividing an adsorption bed layer in adsorption equipment into a plurality of monitoring regions with similar sizes in a waste gas treatment process, by combining waste gas data at a waste gas outlet for coupling analysis, high-quality real-time waste gas concentration data can be obtained after coupling treatment on the basis of diversified data, and then the concentration of the waste gas is determined based on the data and state data of adsorption equipment in the waste gas treatment process. The real-time adsorption saturation of the adsorption equipment can be accurately analyzed, and the data reflects the adsorption saturation of the current activated carbon adsorption bed layer, so that the waste gas collection air volume can be optimized by dynamically adjusting the waste gas collection air volume through the air speed adjusting module subsequently based on the data, and the desorption of attachments is accelerated; the waste gas treatment effect is improved.

The invention relates to the technical field of new energy automobile charging management, in particular to a new energy automobile charging pile orderly management system and method based on a WeChat applet, and the system comprises a multi-dimensional data collection module which is used for collecting the state of a charging pile, parking space occupation and power grid load data; the Internet of Things sensor group is deployed at the charging pile and is used for acquiring electrical parameters such as the state (during charging, idle charging and fault), charging power and voltage of the charging pile in real time; provided is a parking space visual monitoring device. Through combination of an interval tree data structure and a multi-target optimization scheduling model, space-time dimension dynamic management of charging pile resources is realized, the problems of reservation conflicts, resource idleness and the like in a traditional system are effectively solved, the utilization rate of the charging piles is remarkably improved, and an intelligent time period recommendation algorithm is based on user habits and a power grid load state. Users are guided to carry out peak shifting charging, balanced allocation of charging resources and power grid loads is promoted, and optimization of energy utilization efficiency is achieved.

The invention provides a real-time data acquisition buffer throughput management method and device and electronic equipment, and relates to the field of data processing. Receiving a data object containing a sampling value, a timestamp, a measuring point number and a state mark through an input memory queue, and constructing a logic mapping identifier by a mapping agent unit to generate a logic write-in state; the logic write-in state is stored in a delay sensing buffer area, and a transaction confirmation delay sequence returned by a target database is monitored in combination with a distributed delay monitoring unit; establishing a time regression model based on the delay sequence, and generating a prediction projection window of transaction confirmation time; when the window meets a confidence threshold condition, releasing the logic write-in state to an output memory queue; and finally, writing into a database through an output thread, generating a completion mark table, and feeding back for delay buffer dynamic management. By implementing the technical scheme provided by the invention, the buffer data release rhythm and the database processing capability are conveniently coordinated, so that the overall throughput efficiency is improved.

Systems and methods for managing resources across a global and / or cloud network. In particular, systems and methods for mitigating issues related to providing services while resources are offline (or may potentially go offline). For example, the systems and methods may mitigate issues related to providing services while resources are offline (or may potentially go offline) by monitoring network services at an aggregate level.

The invention discloses a love and marriage matching system based on hierarchical AI expert decision, relates to the technical field of hierarchical matching, and is used for solving the problems that hierarchical management and a refined hierarchical pushing mechanism are lacked, various recommendation targets are difficult to consider, and recommendation accuracy is reduced. Extracting a user pair feature vector, calling a plurality of field expert agents to generate a multi-dimensional score vector, performing similarity comparison on the feature vector and a success mode vector in the dynamic matching mode knowledge base, calculating a matching degree score, and synthesizing the matching degree score and the multi-dimensional score vector to obtain a matching recommendation level. And dividing the user pairs into corresponding recommendation pools according to the matching recommendation levels, and outputting a recommendation list according to a display strategy, so that multi-stage, layered and dynamic management of love and marriage matching is realized, the matching success rate and the interaction satisfaction degree are improved, and a layered recommendation decision-making mechanism based on multi-source expert knowledge driving is realized.

The invention provides a DAG arrangement and execution method and system based on operator dynamic management, and the method comprises the steps: constructing an initial directed acyclic graph DAG, dynamically loading operator plug-ins registered in the initial DAG, obtaining context information during operation, and storing the context information to a context container; dynamically selecting a next execution path based on the real-time data in the context container, generating an executable operator queue according to the updated DAG structure, and monitoring the execution state of the operator node in real time; and dynamically modifying the DAG structure according to a trigger condition in the execution process, and outputting a final result after the DAG is executed. According to the DAG arrangement and execution method and system based on operator dynamic management, flexible configuration of the task process, dynamic scheduling of the operator level and intelligent decision making during operation are achieved, and therefore the universality, adaptability and execution efficiency of the system are remarkably improved.

The invention relates to the technical field of artificial intelligence and natural language processing, in particular to a KV cache compression and eviction lexical element recovery method and system for large language model reasoning, and the method comprises the steps: for a query vector of an ith lexical element calculated by a current Transform layer, calculating attention scores of the query vector and all key vectors; executing a V cache dynamic updating operation based on the attention score; and for the ith lexical element, after the V cache dynamic updating operation is completely completed, performing attention calculation by using the updated value vector set in the V cache storage pool and the pre-calculated attention score partial product P. According to the technical scheme, the technical problem that in the prior art, collaborative optimization of video memory occupancy and calculation efficiency is difficult is solved, and the method has the advantages that KV cache video memory occupancy is dynamically managed, the model reasoning quality is kept, and the calculation efficiency is improved.

The invention belongs to the technical field of network security, and relates to a terminal security access control method and device, computer equipment and a storage medium, the method comprises the following steps: deploying an infrastructure for terminal security access, the infrastructure comprising a client, a security system and a server component; the method comprises the following steps: performing initial registration on terminal equipment, and realizing unique binding of a terminal identity and loading of a basic security policy by acquiring an equipment fingerprint, issuing a certificate and configuring a policy; the user identity and the equipment credibility are verified in real time through a multi-factor dynamic authentication mechanism; through signature verification and encrypted transmission, application and network communication authentication is carried out, and application legality, communication channel security and operation environment credibility are ensured; and after the authentication is passed, trusted connection is established, fine-grained authorization is implemented, and security isolation of a service layer is realized through dynamic token and API management and control. The problems that in existing terminal access control, the authentication dimension is single, the authorization granularity is rough, and dynamic management and control are lacked are effectively solved.

The invention discloses a multi-platform-based advertisement creativity and putting strategy intelligent generation system, equipment and medium, multi-source data are integrated through a cross-platform creativity intelligent generation module to generate creativity materials adaptive to different platforms, and a cross-platform collaborative strategy optimization module is used for quantifying a platform collaborative effect and dynamically allocating budget. An advertisement creative life cycle is managed by means of a real-time dynamic optimization module, a strategy is adjusted based on multi-dimensional feedback, and finally, output of each module is fused through a unified decision engine to form a unified decision. The system realizes full-process intelligentization of advertisement originality and putting strategies, quantifies a cross-platform synergistic effect to improve budget distribution efficiency, constructs an advertisement originality life cycle dynamic management mechanism, realizes strategy real-time evolution through multi-dimensional feedback, and visualizes full-link data in combination with a unified decision engine, so that the advertisement putting return on investment is remarkably improved, and the advertisement putting efficiency is improved. The creative manufacturing cost is reduced, the strategy adjustment efficiency is improved, and an efficient and accurate multi-platform putting solution is provided for advertisers.

The invention provides a resource control method, device and equipment, and relates to the technical field of terminal communication. The method comprises the steps that the electronic equipment can obtain load information, the load information is used for representing resource usage amounts corresponding to tasks in a first task group and a second task group, and the first task group comprises a real-time task corresponding to an application interacting with a user at present; a first resource threshold value corresponding to the first task group is greater than a second resource threshold value corresponding to the second task group. And when the load information meets a first condition, adjusting a first resource threshold value corresponding to the first task group to a third resource threshold value, and adjusting a second resource threshold value corresponding to the second task group to a fourth resource threshold value. By grouping the tasks differently and dynamically adjusting the resource thresholds corresponding to the groups, resource allocation corresponding to the important real-time tasks can be ensured, conditions such as lagging are avoided, and dynamic management of resources is realized. Therefore, the stability and performance of the system and the use experience of the user are improved.

The invention relates to a fully mechanized coal mining face respirable dust concentration management limit value determination method, belongs to the technical field of coal mine dust treatment, and is used for solving the problem of inaccurate respirable dust control caused by the fact that a traditional fixed threshold value cannot adapt to a multi-dust-source coupling working condition. The method comprises the following steps: acquiring dust falling efficiency data of multiple dustproof measures, establishing a mathematical model of dustproof parameters and dust concentration, calculating a dynamic management limit value by combining an industrial standard threshold value, and performing self-adaptive adjustment by monitoring and triggering parameters such as spraying pressure and dust removal air volume in real time. Compared with a traditional method, the dynamic limit value enables the respirable dust concentration to be reduced by 40% or above, the multi-measure cooperative dust falling efficiency is improved to 85%, water is saved by 15%-20%, the equipment energy consumption is reduced by 10%, and intelligent and precise dust treatment is achieved.

The invention provides a digital intelligent base service achievement management method and system, and relates to the technical field of digital intelligent base service management.The method comprises the steps that firstly, a basic feature set containing attributes, sources and process features of service achievements in a digital intelligent base is collected, then associated features of the basic feature set are mined, and a service achievement associated network is formed; then, a multi-level management index containing a transverse attribute dimension and a longitudinal flow node dimension is constructed based on the service achievement association network, and a management strategy covering storage, updating and sharing features is generated in combination with index features and service achievement real-time state features; and finally, performing dynamic management and control on the business achievements in the digital intelligent base according to the management strategy, thereby deeply mining the relationship between the business achievements, realizing multi-dimensional fine management, dynamically adapting to business changes, and improving the management efficiency.

The invention discloses an operation planning optimization method, system and device for resource allocation, a storage medium and a product, and relates to the technical field of resource allocation and optimization decision, and the method comprises the steps: collecting resource related data; through a pre-trained resource allocation large model, based on the constraint condition and the target function, outputting an operation planning optimization formula matched with the current service scene; based on the workflow arrangement mode, performing service logic definition and workflow node visualization processing on the service demand information to obtain a workflow execution model; executing operation planning optimization calculation according to the resource related data and an operation planning optimization formula to obtain an optimal solution set, and fusing a workflow model to generate a decision variable; and calling a decision engine to carry out variable replacement, and generating a resource allocation strategy. According to the scheme, large model modeling and operation planning optimization capabilities are fused, the modeling threshold is reduced, and the intellectualization, data driving and interpretability of a resource allocation decision are improved; and meanwhile, in combination with a workflow dynamic management mechanism, intelligent optimization decision making is realized.

The invention relates to the field of intelligent transportation and urban landscaping management, and discloses an LIM transportation junction landscaping landscape intelligent operation and maintenance method and system and electronic equipment, and the method comprises the following steps: constructing a landscaping landscape information model integrating a three-dimensional space model, physiological attributes and infrastructure topology; deploying a multi-source sensing network based on the model, and collecting environment, vegetation and operation and maintenance data; performing time-space association on the data and the model entity, and establishing a dynamic data management platform; constructing a vegetation digital twinborn prediction engine in combination with the physical information neural network and outputting a result; based on the prediction result, adopting multi-target reinforcement learning to generate a maintenance strategy; and executing an intelligent maintenance task bound with the model space coordinates according to a strategy. According to the method, unified integration and dynamic management of greening landscape data are realized, vegetation state sensing precision and prediction capability are improved, intelligent decision-making of multi-objective optimization is supported, and scientificity, efficiency and resource utilization rate of greening maintenance are effectively improved.

The invention provides an urban traffic ubiquitous perception method based on a federal aided large model, and belongs to the technical field of data processing, and the method specifically comprises the steps: 1, building a space-time diffusion field based on multi-source heterogeneous traffic data of a target city, and dynamically dividing traffic perception subtasks according to the space-time diffusion field, and obtaining a subtask set; 2, scene training is carried out according to each traffic perception sub-task in the sub-task set based on federated learning, and a traffic perception sub-model corresponding to each traffic perception sub-task is obtained; and step 3, performing hierarchical aggregation and splicing on all the traffic perception sub-models to obtain a hierarchical perception large model, and realizing multi-task parallel perception and dynamic management of target urban traffic. Through the scheme of the invention, the generalization ability and accuracy are improved.