13results about How to "Improve resource allocation efficiency" patented technology

The invention discloses a dynamic clustering and role adjustment networking method and device, equipment, a medium and a product, and relates to the technical field of computers.The method comprises the steps that equipment information of multiple terminal equipment is obtained, and an information model is constructed according to the equipment information of the multiple terminal equipment, the equipment information comprises hardware characteristics, position information and state information of the terminal equipment; clustering the plurality of terminal devices based on the position matrix to obtain at least one cluster, and determining a device role of each terminal device in each cluster according to the state matrix, the device roles including a core device and an auxiliary device; and if it is detected that the information model is updated, dynamically adjusting the device role of each terminal device in the cluster according to the updated information model. According to the invention, the resource allocation efficiency among multiple devices is improved.

The invention discloses a consultation joint review system and method, belongs to the technical field of government affair service systems, and aims to solve the technical problem of how to improve the handling efficiency of consultation joint review. Comprising an institution declaration management module which is used for supporting a declaration institution to submit a declaration application online and supporting a user to edit and manage submitted declaration information; the consultation management module is used for supporting auditor of each supervision department to approve the declaration information submitted by the user according to a predetermined process; the feedback information management module is used for recording the approval process of the declaration information through the constructed approval result information table, feeding back the feedback process of the declaration information to the declaration mechanism and supporting the approval process of the declaration mechanism for querying the declaration information; and the industry and commerce registration management module is used for supporting a declaration mechanism to submit an industry and commerce registration application on line, supporting a user to edit and manage submitted industry and commerce registration information, and supporting the user to inquire an industry and commerce registration state on line.

The present disclosure relates to a resource allocation method, device and system for a cluster. The cluster includes multiple nodes, the multiple nodes are divided into multiple node sets that are the same as the total number of multiple asynchronous scheduling threads, and one asynchronous scheduling thread corresponds to one node set. The resource allocation method includes: receiving a resource allocation request, the resource allocation request includes the number of resources to be allocated; according to the resource allocation request, scheduling each asynchronous scheduling thread in the multiple asynchronous scheduling threads to perform the following steps: judging whether each asynchronous scheduling thread meets a first resource allocation condition, and if each asynchronous scheduling thread meets the first resource allocation condition, judging in turn whether each node in the node set corresponding to each asynchronous scheduling thread meets a second resource allocation condition, and for each node in the node set corresponding to each asynchronous scheduling thread, if the node meets the second resource allocation condition, allocating the resources to be allocated to the node.

The invention discloses an energy management balance scheduling optimization method and system based on deep learning, and the method comprises the steps: collecting multi-source feature data, carrying out the standardization and preprocessing, and obtaining structured multi-dimensional time series data; constructing a node relation graph by using an improved dynamic graph attention model, and generating a global attention matrix; node features are updated according to the global attention matrix, optimized features are formed, and a scheduling strategy is generated; optimizing the scheduling strategy by adopting an improved Harlisia eagle algorithm to obtain an optimized scheduling scheme; a node operation strategy is adjusted according to the optimization scheme, and power and load distribution is completed; and a final operation scheme is generated and dynamically corrected. According to the method, the improved dynamic graph attention model is constructed, and the Harris eagle optimization algorithm combining a boundary escape mechanism and a dynamic energy regulation and control mechanism is combined, so that intelligent modeling of multi-source data of an energy network, multi-target optimization of a scheduling strategy and dynamic balance scheduling of energy operation are realized.

The invention discloses a maritime emergency search and rescue resource assessment and responsibility allocation method. The method comprises the following steps: constructing a maritime emergency resource allocation risk assessment model, and constructing a maritime emergency search and rescue difficulty analysis and assessment model; constructing a responsibility subject allocation index system based on a maritime emergency search and rescue resource allocation risk assessment result and a search and rescue difficulty assessment result; establishing a multi-objective optimization model by minimizing the response time, maximizing the resource utilization rate and optimizing the load balancing and responsibility subject allocation index system; an NSGA-III algorithm is adopted to solve the multi-objective optimization model, and a Pareto optimal solution set is obtained; and performing cooperative game screening on an optimal solution in a Pareto optimal solution set based on responsibility allocation calculation of a dynamic Shapley value and a contract network protocol mechanism, generating a final task-rescue station responsibility allocation matrix, and realizing dynamic cooperative decision-making of a responsibility subject.

The invention discloses a multi-level agent collaborative decision-making method and system, and the method comprises the steps: carrying out the semantic analysis of an energy-saving standard document, extracting a standard knowledge unit, carrying out the semantic matching of an urban energy consumption target and the standard knowledge unit, and generating a correlation graph; a high-competition target group is identified through target competition degree analysis, collaborative agent pairs are screened through resource complementation degree calculation, and a building-level decision network is constructed; identifying low-load high-potential equipment and performing capability activation through equipment capability scanning and load potential evaluation; conflict intention double-layer features are extracted in combination with conflict detection, a conflict root is traced through a causal chain, and a mediation rule is established; improving the consensus degree of weak consensus nodes by adopting a consensus obstacle traceability and enhancement strategy; and finally, a hierarchical decision scheduling graph is formed through decision dependency analysis, multi-level collaborative decision scheduling is performed to generate a collaborative decision instruction, and comprehensive and intelligent multi-agent collaborative decision support is provided for a city-level energy-saving and carbon-reducing system.

This application provides a control method, apparatus, device, medium, and program product for unmanned aerial vehicle (UAV) swarms, relating to the field of automatic control technology, and aimed at improving overall resource allocation efficiency. The specific technical solution involves: acquiring scene information and state information of the UAV swarm's mission scenario; inputting the scene and state information into a UAV control model; extracting global feature information from the scene and state information through a low-level task controller; assigning at least one sub-task to each UAV in the swarm based on the global feature information through a high-level task switcher; and generating and outputting control strategy information for the UAV swarm for each sub-task through a low-level action controller. This application is applied to scenarios where UAV swarms collaboratively perform disaster awareness and communication support tasks in emergency situations.

The present invention discloses a dual game method and system of multiple virtual power plants and distribution systems, the method comprising: constructing a distribution system operation model and a virtual power plant operation model respectively with the goal of minimizing the operation cost; converting the distribution system operation model and the virtual power plant operation model into corresponding distributed blue-robust optimization models respectively according to the uncertainty of distributed photovoltaics; constructing a first game model between multiple virtual power plants and the distribution system with the electricity price strategy and the grid-connected power as the interactive variables; constructing a second game model between the virtual power plants with the active power transmitted between the virtual power plants as the interactive variables; constructing a dual game model of multiple virtual power plants and the distribution system based on the first game model and the second game model; solving the dual game model to obtain the optimal power generation plan and the optimal energy interaction strategy. The present invention can balance the supply and demand relationship of the power system and improve the resource allocation efficiency of the entire power system.

This invention relates to the field of petrochemical safety production management technology, specifically to an intelligent on-site safety management platform for petrochemical plants. The platform comprises a perception layer, a transmission layer, a data layer, an application layer, and a display layer. These layers work together to achieve full-process coverage of on-site safety management in petrochemical plants. The perception layer is equipped with positioning terminals, health monitoring equipment, behavior recognition equipment, and environmental monitoring equipment to collect personnel location, health data, work behavior, and environmental parameters. The transmission layer utilizes a 5G private network, a WIFI local area network, and a ZigBeePlus wireless communication module to achieve high-speed and stable data transmission between the perception layer and the data layer. This invention, through ZigBeePlus three-dimensional positioning technology, achieves personnel positioning accuracy down to the meter level, accurately pinpointing the specific location of personnel in plant areas and confined spaces. Vital signs are linked in real-time with location data; when personnel exhibit health abnormalities or are in dangerous areas, the system can quickly trigger an early warning and lock their location, reducing rescue response time by more than 50% and significantly reducing the risk of personnel injury or death.

The invention discloses a method for a user equipment (UE) to report the opportunity that a physical uplink shared channel (PUSCH) is not used in a configuration grant (CG) period, and relates to a method for the UE to report the opportunity that the physical uplink shared channel (PUSCH) is not used in the CG period. The UE receives information about the CG, including a number of consecutive slots within the CG period and a size of a bitmap for reporting. Based on the received CG configuration, the UE identifies an unused PUSCH occasion within the CG cycle. In one embodiment, the UE transmits uplink control information (UCI) in a physical uplink shared channel (PUSCH) opportunity, and the UE transmits the uplink control information (UCI) in a physical uplink shared channel (PUSCH) opportunity. The UCI includes a bitmap indicating the identified opportunity of unused PUSCH (Physical Uplink Shared Channel).

The embodiment of the invention discloses a transformer substation starting device and method and a generator response device. The transformer substation starting device comprises an uninterruptible power supply (UPS) power supply module and a remote control system. The UPS power supply module is used for providing an uninterruptible power supply for the remote control system; the remote control system comprises a generator monitoring module, a generator remote starting module and a generator device information reset module. The generator monitoring module is used for transmitting generator state information to the dispatching center in real time; the generator remote starting module is used for sending a starting instruction to the generator starting circuit to start the generator when the generator state is not abnormal; and the generator device information reset module is used for sending a reset signal to the generator when the generator state is abnormal. Through the UPS power supply module and the remote control system, remote quick start and automatic access to the station system of the generator can be realized, and the time from power failure to power supply recovery is greatly shortened.

This invention discloses a cloud-based method for the integrated supervision of cross-border e-commerce, comprising the following steps: S1, real-time collection of cross-border e-commerce transaction data, logistics and distribution data, warehousing data, and customs supervision data, and standardization processing using a distributed cleaning method; S2, construction of a multi-source heterogeneous graph based on the standardized data; S3, annotation of node and edge types, relationship types, and timestamps in the graph, and extraction of high-dimensional features using a relation-enhanced graph Transformer; S4, local and global aggregation using a multi-layer attention mechanism to generate an aggregated view; S5, construction of a multi-objective supervision task model and generation of a resource scheduling scheme; S6, identification of transaction, logistics, and supervision anomalies, and generation of risk warning and intervention strategies; S7, dynamic optimization of the relationship structure and Transformer parameters based on execution feedback. This invention, based on high-dimensional graph representation and optimized scheduling mechanism, achieves integrated supervision and risk warning of cross-domain multi-source data in cross-border e-commerce.

The present application relates to the technical field of multi-agent system cooperation, and particularly relates to a multi-agent overlapping alliance optimization method based on a capability center drive, which comprises the following steps: collecting a plurality of agents around a given task agent to obtain a total available capability pool in a region; if it is determined that the total available capability pool in the region meets the demand, constructing an alliance for the given task agent and the plurality of agents around the given task agent; screening an alliance that meets the task demand and has the optimal system efficiency; implementing dynamic resource allocation on the optimal alliance, and updating the resource state of the agent in real time; when a new task arrives, the remaining resources of the agents in the constructed alliance are deducted, and a new round of alliance construction is performed. The present application focuses on dynamic task allocation and cooperation optimization of multi-agents, and is particularly suitable for collaborative work and resource management of heterogeneous agents in a complex and topologically time-varying environment.