38results about How to "Implement dynamic allocation" patented technology

The invention provides an OracIeRAC-based CDC synchronization method and system, and relates to the technical field of OracleRAC, and the method comprises the steps: deploying an incremental log analyzer, a session state collector and a resource monitor, and respectively collecting atomic operation, concurrent transaction information and node performance indexes; and identifying data stream features by using an intelligent classification model, constructing a priority matrix, and performing fine-grained acquisition on high-priority data based on an adaptive sampling strategy. According to the method, multi-dimensional evaluation indexes are further utilized, a time sequence prediction model is constructed to predict node loads, data synchronization tasks are distributed to low-load nodes based on a load balancing matrix, and a two-stage submission protocol is adopted to ensure data consistency. By monitoring the synchronization state in real time and dynamically adjusting the allocation strategy, the CDC synchronization efficiency and stability in the Oracle RAC environment are effectively improved, and the synchronization delay is reduced.

The invention relates to the technical field of data processing, in particular to an intelligent logistics platform management system and method based on multi-source data. The method comprises the following steps: acquiring cold-chain logistics order data; performing multi-type cargo temperature control demand processing on the cold-chain logistics order data to generate cargo temperature control demand data; performing multi-node temperature control task decomposition on the cold-chain logistics order data through the cargo temperature control demand data to generate multi-node fine temperature control task data; performing cold chain abnormal feature analysis according to the multi-node fine temperature control task data to generate abnormal temperature control processing scheme data; and carrying out transportation-junction point temperature control correction according to the abnormal temperature control processing scheme data, and carrying out cold chain quality weighted scoring to generate logistics quality scoring data. According to the invention, through cold chain task decomposition and cooperation of multiple transportation nodes, intelligent cold chain logistics management is realized, and the temperature control management efficiency and cargo quality guarantee of cold chain logistics are improved.

The invention provides an MBB multi-channel local aggregation superposition transmission method and an MBB multi-channel local aggregation superposition transmission system. Belongs to the technical field of communication. The method comprises the following steps that: a plurality of physical links are established in a wireless communication system, and the system selects the plurality of optimal physical links for aggregation according to a current network environment, a current equipment state and a current user demand; dividing data to be transmitted into a plurality of data packets, packaging each data packet according to the characteristics of the selected physical link, and transmitting the packaged data packets in parallel through the selected physical link; in the transmission process, the system monitors the transmission state of each link in real time, and dynamically adjusts the transmission rate and power distribution of each link according to the current network load and equipment state. By transmitting a plurality of physical links in parallel, the network bandwidth can be fully utilized, the data transmission rate is improved, and the transmission delay is reduced.

The invention provides a low-altitude industry chain information intelligent cooperation and airspace management platform based on federal learning. Through cluster ad hoc network and decentralized federated learning, the method is divided into three stages of data acquisition, data preprocessing and analysis application, low-altitude scene data communication of dynamic topology and static topology is realized, and the efficient communication requirement in a low-altitude operation scene is met. According to the system, differential data transmission strategies are adopted, optimization design is carried out on a single machine, a co-task cluster, a cooperative cluster and a non-cooperative cluster, and the communication efficiency and the resource utilization rate are improved. In the data preprocessing stage, federated learning aggregation of multi-source data fusion, data anonymization and decentralization is combined, and data privacy protection and safe sharing of three parties of industry, university and research are ensured. In the analysis and application stage, low-altitude aircraft task scheduling, airspace flow control and environmental condition evaluation are realized through aircraft analysis, airspace analysis, environmental analysis and digital twinborn technologies.

The invention discloses a road right sharing configuration method and a traffic control system, and relates to the technical field of special vehicle road right sharing, and the method comprises the steps: obtaining the real-time position and speed information of a common vehicle and a special vehicle at an intersection; determining the traffic flow condition of the current intersection by using a traffic flow prediction model; according to the real-time position and speed of the special vehicle and the traffic flow condition of the current intersection, the period and phase duration of the signal lamp are dynamically adjusted through a bidirectional dynamic green wave algorithm, a signal lamp control strategy is obtained, and it is ensured that the special vehicle can pass through the intersection without stopping; configuring intersection signal lamps according to the signal lamp control strategy; according to the invention, through combination of prediction of the traffic flow condition of the intersection and the real-time position of the special vehicle, the period duration and the phase duration of the signal lamp at the intersection are automatically adjusted, the influence on common vehicles at other phases is reduced as much as possible while the special vehicle is ensured to pass through the intersection without stopping, thereby realizing dynamic distribution and sharing of the road right of the special vehicle, and improving the traffic safety. And the utilization rate of special lane resources is furthest improved.

The invention relates to the technical field of robot scheduling, in particular to an airport terminal manned robot scheduling method and system, and the method comprises the steps: collecting the state information of a robot in real time, and receiving the real-time demands of a passenger, the real-time demands comprising the position information of the passenger and the target position information; a bipartite graph matching model is constructed, the bipartite graph matching model comprises a passenger demand set and an idle robot set which form two subsets of a bipartite graph respectively, and by constructing an OD matrix, the path length, the passenger waiting time and the robot energy consumption serve as optimization targets. A self-adaptive Hungary order dispatching algorithm is adopted, special environment characteristics of an airport terminal are combined, an airport terminal multi-robot dispatching scene is established, a bipartite graph order dispatching matching model is constructed, the path length, the passenger waiting time and the robot energy consumption serve as optimization targets, an OD matrix of a loading task is calculated, and the loading task is dispatched. And dynamic allocation and intelligent scheduling of passenger demands and robot resources are realized.

The invention discloses a rate division multiple access communication network total rate optimization method and system, and belongs to the technical field of communication. The method comprises the following steps: constructing a downlink rate segmentation multiple access communication system model based on an intelligent reflecting surface; the communication system model comprises a base station, an intelligent reflecting surface and a user side; grouping users in the user side, and constructing a hierarchical rate segmentation multiple access model based on user grouping; the hierarchical rate segmentation multiple access model comprises a corresponding relation between the user group and information flow generated by the base station; and according to the hierarchical rate segmentation multiple access model and the intelligent reflecting surface, assisting downlink communication between the base station and the user side. According to the method and the device, the layered rate division multiple access model is constructed by grouping the users, and the system performance is improved by combining the intelligent reflecting surface passive beam forming and the rate division multiple access active beam forming, so that the problems of spectrum resource shortage and signal interference can be solved, and the spectrum efficiency is greatly improved.

The invention relates to the technical field of computing power cabin cluster scheduling. The invention relates to a cluster scheduling control method based on a computing power cabin. The method comprises the following steps: S1, obtaining performance data of a computing power cabin, and then carrying out resource virtualization to form a resource pool; s2, collecting historical operation data and real-time operation data of the service user, and predicting a resource demand of the service user to obtain a predicted resource demand; s3, combining the predicted resource demand with the real-time operation data to carry out predicted volatility analysis, setting an isolation fluctuation threshold value, then comparing the predicted volatility with the isolation fluctuation threshold value, and when the predicted volatility is smaller than the isolation fluctuation threshold value, judging whether the predicted volatility is smaller than the isolation fluctuation threshold value or not; according to the method, resource demand prediction is carried out by using the historical operation data and the real-time operation data, resources can be allocated to the user more accurately, and when the predicted fluctuation rate is smaller than the isolation fluctuation threshold value, the resource instance is automatically started to carry out node isolation on the user, so that the stability of resource allocation is ensured.

The invention discloses a frequency point distribution method. The method comprises the following steps: a first device sends a first request to a first network element of a first gateway device; wherein the first request comprises ephemeris information of the first equipment, first beam position frequency point information of the first equipment and beam position information of the first terminal; the first network element is used for managing terminals in an overlapping coverage area of the first equipment; the terminal comprises a first terminal; the first network element receives a first request sent by the first device; the first network element determines a first frequency point at least based on ephemeris information, first beam position frequency point information and beam position information; wherein the first terminal accesses the first device based on the first frequency point; the first network element sends the information of the first frequency point to the first device; and the first device receives the information of the first frequency point sent by the first network element. The invention further discloses the first network element of the first network device, the first device and a computer readable storage medium.

The invention provides a task processing method and device based on a network state. The method comprises the following steps: acquiring a target task through an edge end; task attributes are extracted, semantic coding is conducted on the task attributes, and semantic coding features are obtained; obtaining a time queue of network real-time bandwidth values, and extracting network state time sequence characteristics from the queue; performing feature fine-grained pairing interaction based on the semantic coding feature and the network state time sequence feature to obtain an alignment fusion feature; and distributing the target task to an edge end or a cloud end according to the alignment fusion feature, so that a distributed end processes the target task. According to the invention, dynamic allocation between the edge end and the cloud end can be realized according to different attributes and requirements of tasks and current network conditions; compared with a traditional technical scheme based on static indexes, the method fully considers the characteristics of the task and the real-time network state, enables the target task to be processed more efficiently, and improves the overall response speed and task processing efficiency of the system.

According to the FPGA dynamic allocation device and method based on the server cluster, the field programmable characteristic of an FPGA can be greatly utilized, FPGA hardware is rewritten in real time, and the FPGA resource utilization rate and the operation efficiency of a server are greatly improved. The system comprises a data acquisition module, a controller, a first memory, a second memory and an FPGA device, the data acquisition module collects information, wherein the information comprises current time, user access habits, current server resource consumption conditions and to-be-executed task contents; the first memory stores FPGA engineering files in a binary code stream form, and each engineering file is a solution for accelerating a demand scene of a server cluster; the second memory stores an instruction program, and the instruction program directs the controller to download a specified FPGA project file into a specified FPGA device; and the controller downloads the FPGA project file to a specified FPGA device.

The present invention is applicable to the computer field, and provides a container-based industrial Internet of Things edge computing resource allocation method and system. When there is a resource container whose operating load exceeds a threshold, the resource container whose operating load exceeds the threshold is calculated to meet the resources to be supplemented required for task operation, and the resource container whose operating load is less than the threshold is obtained. The remaining allocatable resources of each resource container whose operating load is less than the threshold are calculated, and the resources to be supplemented are compared with each of the remaining allocatable resources. A resource container to be divided is determined according to the comparison result; the remaining allocatable resources of the resource container to be divided are mounted to the resource container whose operating load exceeds the threshold, and the task is continued to be executed in the mounted resource container, so that the dynamic allocation of resources of each resource container when executing the task can be realized, and the problem of unreasonable resource allocation affecting the resource utilization rate and task processing efficiency is solved.

The application relates to a resource scheduling method and device, computer equipment, a storage medium and a computer program product. The method comprises the following steps: determining a target virtual machine from a plurality of virtual machines to be created, and taking an initial physical machine cluster as a candidate physical machine cluster corresponding to the target virtual machine; determining a candidate allocation physical machine corresponding to the target virtual machine from the candidate physical machine cluster; determining a reference allocation physical machine from the candidate allocation physical machine based on the physical machine cluster fragmentation quantity and the remaining virtual machine quantity generated by allocating the target virtual machine to the candidate allocation physical machine; updating the idle resources of the reference allocation physical machine in the candidate physical machine cluster to obtain an intermediate physical machine cluster corresponding to the target virtual machine; and continuously allocating a next virtual machine on the basis of the intermediate physical machine cluster until a candidate physical machine cluster and a candidate allocation physical machine corresponding to a last virtual machine are obtained, and then determining a target scheduling scheme. The method can improve the resource utilization rate.

The present invention discloses an intelligent load balancing method based on a zero-sample hybrid expert model, comprising the steps of: creating a task spectrum mapping relationship through zero-sample learning, generating virtual labels, refining the requirements of new tasks into resource requirement feature spectra through multi-dimensional feature cross-projection, and predicting the multi-dimensional resource requirements of new load balancing tasks; establishing a multi-perspective hybrid expert dynamic integration mechanism, configuring multi-perspective hybrid collaborative experts for tasks, applying a combination of several expert models to different demand dimensions, creating virtual image samples of new tasks, simulating resource requirements and their load effects in a virtual environment, and generating an initial resource allocation plan; in the face of dynamic load fluctuations, distributing task cells to nodes with sufficient resources; the method improves the robustness and efficiency of the system, simplifies the implementation process, and has broad application prospects and practical value.

The application provides an AI computing power allocation method, system, device, storage medium and program product, and relates to the technical field of data processing. The AI computing power allocation method determines the corresponding target AI algorithm model based on the service demand of the target reasoning service in real time, and then dynamically matches the target computing power resource used to load the target AI algorithm model by combining the processing demand of multiple AI algorithm models, the preset adaptability rules of various heterogeneous computing power resources, and the current use state of the various heterogeneous computing power resources, so as to realize dynamic allocation of AI computing power resources, avoid computing power resource overload or idling, improve computing power resource utilization, reduce task reasoning delay, and thus improve data processing capability.

This application provides a signal communication method for a multi-dimensional domain of a data link, comprising: performing cross-domain correlation deconstruction on the data link's spatiotemporal-frequency multi-dimensional signal and error feature data under an electromagnetic environment to obtain the original spatiotemporal-frequency domain feature set; simultaneously integrating signal propagation characteristic data and error source attribute data to generate a multi-source correlation data cluster to generate a spatiotemporal-frequency multi-dimensional fused feature topology; constructing a multi-dimensional domain collaborative error-resistant model based on the spatiotemporal-frequency multi-dimensional fused feature topology; and performing dynamic weight allocation and error suppression strategy iterative optimization on the spatiotemporal-frequency domain error-resistant weight parameters and error suppression strategy parameters in conjunction with spatiotemporal-frequency domain resource adaptation rules to generate a multi-dimensional domain error-resistant control command; performing spatiotemporal-frequency collaborative optimization processing on the data link transmission signal according to the multi-dimensional domain error-resistant control command to obtain an error-resistant optimized signal; simultaneously collecting transmission quality data of the link feedback signal; and fine-tuning the multi-dimensional domain error-resistant control command parameters in reverse by the deviation between the transmission quality data and a preset quality threshold.

The application provides a digital twin and cloud edge collaborative deep-sea mining system fault diagnosis method and system, and relates to the technical field of deep-sea mining system fault diagnosis. The method comprises the following steps: constructing a digital twin model and performing mechanism monitoring; edge side signal processing and component level intelligent diagnosis; cloud data aggregation; double-engine information fusion and decision making are performed in the cloud diagnosis center; uncertainty quantification and visual output are performed. The application constructs an intelligent diagnosis architecture based on digital twin and cloud edge collaboration, deeply integrates mechanism models and artificial intelligence, realizes early warning of system level chain faults, robust diagnosis of weak component faults in a strong noise environment, and provides high credibility diagnosis conclusions with quantitative confidence and decision support information, thereby significantly improving the safety, reliability and operation intelligent level of deep-sea mining operations.

The application belongs to the technical field of civil aviation airport flight management, and discloses a flight resource dynamic allocation method and system based on data analysis. A resource data set based on resource characteristics is constructed, and a flight history database based on flight characteristics is constructed; a resource allocation scheme sample library containing both flight characteristics and resource characteristics is constructed; an initial resource allocation scheme is established by data analysis using the resource allocation scheme sample library, and the initial resource allocation scheme is further adjusted to form an allocation scheme of allocation resources; flight information is marked with flight characteristics to complete the allocation of flights; meanwhile, corresponding resource characteristic values in the resource data set are matched with resource characteristics in the allocation scheme of allocation resources to complete the allocation of resources. The application realizes dynamic allocation of flight resources, reduces the cost of manual allocation, and improves the efficiency of flight resource allocation.

The invention discloses a two-phase cold plate spraying cooperative battery thermal runaway intelligent hierarchical control method and system, and relates to the technical field of battery thermal control. The two-phase cold plate spraying collaborative battery thermal runaway intelligent hierarchical control method comprises the following steps: S1, collecting and preprocessing thermal state working condition data, component operation data and environment auxiliary data, and constructing a standardized thermal state data set; s2, top evaluation is conducted on the top sudden heat source intensity, and the starting behavior of a spraying device is regulated and controlled; s3, bottom analysis is conducted on the bottom steady-state cooling bearing condition, and the opening degree of a cold plate runner is dynamically adjusted; and S4, performing vertical evaluation on the vertical heat flux coupling characteristics in combination with the local thermal disturbance trend, and performing linkage control on the top spraying frequency and the operation state of the condensation path. The problems that in battery thermal management, a traditional single cooling mechanism is difficult to consider distributed temperature control requirements of bottom steady-state heat absorption and top sudden refrigeration, so that heat flux coupling is uneven, and the local overheating risk is prominent are solved.

The present application relates to dilution refrigerator temperature calibration technical field, and disclose a kind of dilution refrigerator thermometer in situ calibration system based on natural cooling dynamics, comprising: according to the dynamics equation of cooling power and temperature Curvature is calculated, according to the temperature corresponding to thermometer resistance value, the temperature is substituted into temperature curvature, and the calibration function of resistance value and temperature is obtained;Identify the multivalued region of temperature, and evolve multiple branch functions in multivalued region in calibration function, calculate the deviation measure of each branch function and calibration function;In multivalued region, the support degree of each branch function to calibration function is calculated, and real-time data is obtained by adjusting calculation load, to minimize the number of experiments to verify calibration function;According to the branch verification result of multivalued region, dynamically adjust the verification strategy of non-multivalued region, under the premise of not relaxing calibration accuracy, through dynamics branch and load guide, significantly reduce the repeated experiment cost of dilution refrigerator cryogenic calibration.

The invention discloses a data file storage system based on combination of distributed storage and blue-ray storage, relates to the technical field of data file storage, and not only ensures quick access of high-frequency data, but also realizes long-term reliable storage of low-frequency and important data through combination of distributed storage nodes and blue-ray storage equipment. The distributed storage nodes provide efficient writing and reading performance and are suitable for the data requirement of frequent access, and blue light storage has low storage cost and excellent durability and is particularly suitable for storing low-frequency and long-term reserved data; besides, the data management software layer intelligently classifies the importance and access frequency of data files, so that dynamic allocation and optimal management of resources are realized, and reasonable storage of different data is ensured; according to the whole system, the data access efficiency is improved, the dual requirements of real-time performance and safety are met, and the storage cost is reduced.

The application relates to a DUT test method, a digital board card and a test machine. An ALPG generates a first test data group of all channels according to test vector data and delivers the first test data group to an FC. The FC determines effective channels and ineffective channels according to the delivered channel mode, encodes or shields each channel, obtains a second test data group of all channels, and sends the second test data group to a TC. The TC calculates data pushing time or data sampling time of each effective channel according to timing parameters, and at each data pushing time, updates a historical test data group locked at a previous data pushing time based on the second test data group to obtain a third test data group. A TG receives the third test data group and sends the third test data group to a device under test to perform a data driving operation, or extracts response data of the device under test at a data sampling time to perform a data sampling operation. The application improves the compatibility of DUT test under a multi-channel mode.

The application discloses a kind of distributed control network deployment systems based on industrial PON, it includes industrial network link deployment unit, builds industrial network link and equipment, collects power production control signal and power production related data;Wireless communication unit, the power production control signal of real-time acquisition is encrypted transmission, and non-real-time power production related data is transmitted through LoRa module;Intention drive management unit includes semantic analysis module, and the natural language command of power production control signal and power production related data is parsed using BERT model, and dynamic scheduling module is calculated and distributed to link load by dynamic load balancing algorithm;Block chain storage unit, the natural language command storage of power production control signal and power production related data is realized using alliance chain;Security isolation unit, firewall is based on SM4 algorithm of national secret ALC strategy is deployed, and one-way net gate isolates control area and management information area of industrial network link.

The invention relates to the technical field of wireless communication, and discloses a spectrum collaborative management and control method adaptive to an air-sea cross-domain communication gateway. Aiming at the problem of low spectrum resource management efficiency in an air-sea cross-domain communication scene, the method comprehensively considers overwater and underwater complex environments, and realizes pre-allocation of spectrum resources and dynamic adjustment according to environmental changes through underwater sound spectrum management and control, an efficient adaptive time slot allocation method and overwater electromagnetic spectrum management and control. The spectrum collaborative management and control method adaptive to the air-sea cross-domain communication gateway is based on a maximum-minimum fair channel allocation scheme, and is combined with task priority analysis and environment dynamic perception to perform channel pre-allocation and dynamically adjust a frequency point allocation strategy, so that resource waste is avoided, and the communication stability and the anti-interference capability are improved. The spectrum collaborative management and control method adaptive to the air-sea cross-domain communication gateway provided by the invention significantly improves the spectrum utilization efficiency and system performance of the cross-domain communication network, and is suitable for application scenarios such as ocean resource development and detection.

The application relates to the field of intelligent analysis, and discloses a LIBS multi-component quantitative analysis method based on spectrum mechanism constraint and feature decoupling. Target spectrum data is acquired and pretreated. Spectrum mechanism perception features are extracted according to the pretreated target spectrum data. Component-specific feature decoupling is performed according to the spectrum mechanism perception features. Adaptive error regulation is performed. Finally, multi-component quantitative analysis results are output. The output multi-component quantitative analysis results are based on concentration range constraint and multi-component consistency constraint. The application realizes spectrum feature decoupling, avoids the problem of insufficient attention to low-content components, and improves the accuracy and stability of analysis.

The application discloses a double-drive privacy budget and decentralized incentive method and system based on a blockchain, relates to the technical field of the blockchain, and comprises the following steps: receiving user privacy demand data and task side drive data, generating a user side privacy demand baseline based on the user privacy demand data, generating a task side drive value based on the task side drive data, weighting and coupling the user side privacy demand baseline and the task side drive value to obtain a privacy budget baseline; dynamically distributing and cutting the privacy budget baseline under a preset global risk constraint and a unified scaling factor to obtain a distributed final round privacy budget, obtaining the data contribution degree of the user, inputting the data contribution degree of the user and the distributed final round privacy budget into a preset incentive function to output a user final reward value, and inputting the user final reward value into the blockchain.

The invention discloses a marine energy storage box battery pack liquid cooling heat dissipation device and method suitable for a sea wave impact working condition. According to the marine energy storage box battery pack liquid cooling heat dissipation device, the total output flow is adjusted through a cooling liquid pump, and the flow of each branch is adjusted through a multi-channel proportional valve; in the strategy adjusting aspect, whether a compensation mechanism is triggered or not is determined according to the calculated comprehensive impact index and the flow channel impact included angle, and the output total flow and the branch flow are adjusted; and when the temperature difference between the adjacent battery packs is greater than a first set value, triggering an overcooling protection mechanism, otherwise, updating the output total flow and the branch flow through a circulation mechanism. Ship movement is sensed in real time through the sensor, active cooling liquid flow compensation adjustment is conducted on impact disturbance, and the problems that heat dissipation of a battery pack is uneven, efficiency is reduced and system reliability is reduced due to sea wave impact of a ship under the complex sea condition can be solved.

This application discloses a method, apparatus, and electronic device for fine-tuning a large model based on hybrid experts, belonging to the field of artificial intelligence technology. It addresses the problem that current large model technologies struggle to meet the application needs of multi-task scenarios in network management. The method includes: initializing a hybrid expert network for a pre-trained large model, the hybrid expert network comprising a task-level gating network and multiple task-level expert groups (each group containing a character-level gating network and multiple character-level experts), the hybrid expert network being embedded in specific layers of the pre-trained large model; inputting training data and a first prompt word into the pre-trained large model, guiding the pre-trained large model to output sample prediction results through the first prompt word; determining the loss result of the pre-trained large model based on the true label results corresponding to the training data, the sample prediction results, and the target loss function; and fine-tuning the network parameters of specific layers of the pre-trained large model based on the loss result to obtain a network management model for multi-task scenarios.

The invention discloses a public network access authority management method and a related device, and the method comprises the steps: firstly obtaining a routing rule corresponding to a target Pod, then configuring the corresponding routing rule for the target Pod through an initialization container when the target Pod is started, enabling the target Pod to have a public network access authority, and enabling the target Pod to have the public network access authority based on the routing rule when the target Pod sends a public network access request. The message corresponding to the target Pod is sent to the server corresponding to the next hop address, the message is forwarded to the public network server after being subjected to SNAT, when the target Pod is deleted, the public network access permission of the target Pod is recycled, resource leakage caused by residual permission is avoided, and therefore the public network access permission is bound with the life cycle of the target Pod, and the service life of the target Pod is prolonged. According to the invention, the dynamic distribution and recovery of the public network access authority are realized, and the security of the public network access authority management of the Kubernetes cluster is effectively improved through the fine-grained management of the Pod level of the public network access authority.

The invention relates to a parking reservation and dynamic allocation method for large-scale high-concurrency users, and the method comprises the following steps: S1, collecting the state information of all parking facilities in a region in real time, and parking request information and user state information from a network-connected automatic driving user vehicle or a manual driving user vehicle; s2, according to the distribution moment information obtained in the S1, determining a feasible parking resource set which accords with user preferences and a total user expected cost; s3, describing a parking reservation and distribution system into a dynamic resource distribution problem by using mixed integer linear programming, and setting an objective function and constraint conditions according to parking demands and supply information; and S4, solving the dynamic resource allocation problem in the S3 through an improved Monte Carlo tree search and heuristic rule combined algorithm, and allocating the most suitable parking resources for each user. According to the invention, while the total parking fee of the system user is minimized, the utilization of parking resources can be optimized, and cruise vehicles are reduced.