61results about How to "Efficient scheduling" patented technology

The invention discloses a multi-underwater-robot cooperative control system and method based on predictive control, and relates to the technical field of cooperative control. During operation of the system, underwater environment data are collected through sensor equipment, an underwater three-dimensional dynamic environment model is generated by using a data fusion technology, and the underwater three-dimensional dynamic environment model is established based on task requirements; tasks are decomposed and distributed to all the robots, through an optimization algorithm, optimal paths of the robots and the mechanical arms are planned, the motion trails of the underwater robot mechanical arms are dynamically optimized based on model predictive control MPC, a real-time control strategy is provided for task division among the multiple mechanical arms, and the real-time control strategy of the underwater robot mechanical arms is provided based on environment modeling and the real-time state. Future motion states of the robot and the mechanical arm of the robot are predicted, an optimization objective function including task completion time, energy consumption and mechanical arm operation precision is constructed, a rolling optimization method is utilized, a control instruction is updated in real time, and real-time data sharing among multiple underwater robots is supported based on an acoustic communication technology.

The invention provides an HIVE grouping operation performance optimization and scheduling method based on key column partitioning, which relates to the technical field of data processing, and comprises the following steps: preprocessing data by constructing a key column distribution histogram and determining a key column partitioning strategy; optimizing data partitions based on resource evaluation and a dynamic programming algorithm; and calculating an optimal data transmission path by adopting a minimum spanning tree algorithm, and dynamically adjusting an allocation scheme. According to the method, HIVE grouping operation performance can be improved, dynamic balance of calculation loads is achieved, the problem of data skew is effectively solved, and large-scale data processing efficiency is improved.

The invention belongs to the technical field of data processing, and particularly relates to a container yard digital twinborn model construction and monitoring method based on the Internet of Things, and the method comprises the steps: collecting the related information of a container yard in real time, and constructing a digital twinborn model of the container yard; dynamic data of the container yard is obtained in real time based on a sensor, the dynamic data can represent the operation state of the container yard, and the digital twinborn model is updated in real time based on the dynamic data; obtaining a monitoring result of the container yard based on the digital twinborn model, and generating a stockpiling scheme and a scheduling scheme based on the monitoring result; and simulating the stockpiling scheme and the scheduling scheme in the digital twinborn model to obtain a simulation result, optimizing the stockpiling scheme and the scheduling scheme based on the simulation result, and simulating the optimized schemes in the digital twinborn model again until an optimal stockpiling scheme and an optimal scheduling scheme are obtained. According to the method, the accurate digital twinborn model can be constructed, and the operation efficiency of the container yard can be improved based on the digital twinborn model.

The invention provides a hierarchical federated learning system and method in a wireless mobility scene. The system comprises a central server, a plurality of base stations and a plurality of edge servers, each base station is connected with at least one piece of user equipment, and the user equipment has mobility and can perform data acquisition and model updating at different positions; in each round of training of the hierarchical federated learning system, the user equipment performs local updating by using the local data set, and uploads a local model to the base station after updating; the edge server is configured in the base station and is responsible for receiving a local model uploaded by user equipment and performing partial aggregation, and the partial aggregation is based on a preset aggregation algorithm; after multiple times of aggregation, uploading an aggregation model to a central server; and the central server is used for receiving the aggregation models from the plurality of edge servers and performing global aggregation to complete a federal learning task. According to the method, the user energy overhead can be minimized under federal learning performance constraint and mobility constraint.

The invention discloses an energy regulation and control method and system of a virtual power plant based on a prediction model, and relates to the field of virtual power plant operation control, and the method comprises the following steps: collecting energy data in the virtual power plant; integrating the wind power data and the load data, and performing feature extraction on the integrated data; based on the predicted power generation data of the distributed energy and the predicted demand data of the load side resources, constructing a preliminary energy dynamic balance prediction model; performing day-ahead load demand and distributed energy prediction by using the preliminary energy dynamic balance prediction model; according to the preliminary scheduling strategy, using a niche grey wolf optimization algorithm to adjust the operation state of each distributed energy and load side resource in real time; dynamically adjusting and optimizing the energy dynamic balance prediction model; and carrying out load demand and distributed energy prediction again by using the optimized energy dynamic balance prediction model. According to the method, the change of the power system can be responded in advance, and more efficient energy scheduling is realized.

The invention discloses a scheduling method and system based on a ship traffic flow prediction model, belongs to the technical field of multi-step double-route ships, and is used for solving the problems that in the operation process of an existing multi-step double-line type ship lock, due to the fact that a ship arrangement plan is unreasonable, the utilization efficiency of lock chambers is low, and the cost is low. And the overall operation efficiency and the collaboration of the passing of the fleet are difficult to improve. The method comprises the following steps: carrying out passing analysis on a ship queue of a wait-to-pass water area under a time factor and a queue length factor, and determining a ship queue state; performing dynamic and static data statistics on all ships in the wait-to-pass water area to obtain dynamic attributes and static attributes of each ship; performing interval division of ship flow on the ship queue in the waiting passing area to obtain an initial ship interval; performing target optimization scheduling processing on the ship flow in the ship interval to obtain a final interval ship flow; and a ship flow scheduling planning scheme based on the multi-step double-linear ship lock is generated.

The invention discloses a multi-task PEM unmanned aerial vehicle energy scheduling method and system based on MPC and DDPG, and the method comprises the steps: building a stress model and a power model in each flight mode according to the flight mode of a hydrogen fuel cell unmanned aerial vehicle; establishing a mathematical model, an objective function and operation constraints of the hydrogen fuel cell unmanned aerial vehicle energy system; constructing an MPC model by combining the stress model and the power model of the unmanned aerial vehicle in each flight mode, collecting state parameters of the unmanned aerial vehicle, and obtaining electric power predicted by the MPC model; and constructing a DDPG model based on the mathematical model, the objective function and the operation constraint of the hydrogen fuel cell unmanned aerial vehicle energy system, and taking the predicted electric power as the input of the trained DDPG model to obtain an energy scheduling result. According to the invention, energy utilization can be optimized in a complex task environment, and the task completion efficiency and cruising ability of the unmanned aerial vehicle are improved.

The invention relates to the technical field of virtual power plant management systems, in particular to a multi-virtual power plant comparative analysis and evaluation method and system, and aims to realize multi-dimensional comparative analysis by establishing a basic principle of a comprehensive performance evaluation index system and performing performance evaluation on virtual power plants by adopting an analytic hierarchy process. Based on the principles of purposiveness, completeness, operability, independence and the like, a comprehensive performance evaluation system including aggregation response performance, optimization scheduling performance and reliability performance is constructed, and the comprehensive performance of the virtual power plant can be comprehensively and accurately reflected. Through evaluation, the system can discover the advantages and deficiencies of different virtual power plants, provides a reference basis and targeted improvement suggestions for decision makers, and improves the market competitiveness of the virtual power plants. The system also screens out benchmark virtual power plants with excellent performance for demonstration application, promotes technical innovation and industry progress of the virtual power plants, verifies feasibility and advantages, and lays a foundation for popularization and application of the virtual power plants.

The invention discloses an MAC unit supporting input activation and weight double-end sparsity, and relates to the technical field of neural network accelerator hardware design. Aiming at the technical defects existing in a sparse matrix acceleration scheme, the scheme is adopted, an activation value and non-zero elements of a weight matrix are stored through a special compressed data register, corresponding zero value distribution is recorded through a matched sparse bitmap register, and a joint sparse bitmap marking a double-non-zero effective calculation position is generated through dual-port joint operation; and the control and address generation subunit scans the joint sparse bitmap and outputs an address and an enable signal, the MAC calculation subunit is driven to read non-zero data to complete multiply-accumulate operation, and finally, an operation result is compressed and coded through an output end sparse encoder, so that efficient transmission of interlayer sparse data streams is realized. According to the method, input activation and weight double-end sparsity can be utilized at the same time, end-to-end sparse data flow is supported, zero value calculation can be dynamically skipped, and the energy efficiency ratio and the calculation throughput of neural network reasoning are improved.

The invention discloses a joint beam hopping and precoding scheduling method based on an RSMA multicast satellite system, and relates to the technical field of satellite communication, and the method comprises the steps: building a multicast multi-beam satellite communication system model based on simulation parameters of a satellite communication system; the model comprises a plurality of antenna feed sources and clusters; determining the total provided capacity of different clusters in each time slot through time slot allocation and a beam hopping mode; determining the optimization problem of the model according to the total provided capacity of different clusters; the optimization variables of the optimization problem are the optimal solutions of the precoding vector, the common rate allocation and the CBH strategy vector, which are solved based on a weighted minimum mean square error method. And solving the optimal solution of the CBH strategy vector based on an integer programming method. And determining an optimized multicast multi-beam satellite communication system model by integrating the optimal precoding vector, the common rate allocation and the CBH strategy vector. According to the invention, the interference between beams in the cluster is reduced, and the communication reliability is improved.

This utility model discloses an intelligent three-dimensional storage rack that is easy to schedule, including a support frame and multi-layer placement plates arranged between the support frames. Side frames are respectively arranged on the front sides of the support frame, and a top plate is arranged between the tops of the side frames. A lifting screw is arranged inside the side frame, and a lifting gear is arranged at the top of the lifting screw. A belt is arranged between the two lifting gears. A mounting plate is arranged on the top of the side frame, and a lifting motor is arranged on the mounting plate. A pair of slide rail grooves are arranged on the moving base. The traverse motor is powered by an external power supply. A moving gear and a fixed gear are arranged inside the moving base. A support plate is arranged above the moving base. This storage rack achieves efficient positioning and scheduling of goods through precise mechanical linkage design. This layered positioning mechanism significantly improves the accuracy and efficiency of goods scheduling, facilitates subsequent goods picking operations, and reduces the risk of manual goods handling.

The invention discloses a marketing content generation method based on multi-agent cooperation and related equipment, and the method comprises the steps: determining a target business scene according to content generation demand information and content generation reference information, and obtaining a corresponding target scene data package from a marketing scene library; determining a target agent list and a task list according to the target scene data packet, generating a task directed acyclic graph in combination with the material information and the constraint information, and further generating an arrangement plan; and calling a target agent plug-in to execute a generation task according to the target agent list and the arrangement plan, obtaining a stage content generation result, and performing acceptance check to obtain a final content generation result. According to the embodiment of the invention, full-process automation from scene recognition, task disassembly, task arrangement, multi-agent task generation execution to content acceptance can be realized, and the marketing content generation efficiency, quality and stability can be effectively improved. The method can be widely applied to the technical field of generative artificial intelligence.

The present application belongs to the technical field of intelligent manufacturing and logistics automation, and specifically relates to a multi-task scheduling optimization method and system for RGV shuttle vehicles, which comprises the following steps: firstly, the system is digitally modeled by constructing a time-space resource network and a task association graph; then, a joint prediction model is trained to predict congestion risk and energy consumption cost; further, the prediction results are fused with task value and power state into dynamic heuristic information to guide the self-adaptive ant colony algorithm; finally, online correction and closed-loop self-learning of the model are realized by analyzing the execution deviation vector. The present application continuously improves the actual execution efficiency, robustness and economy of the scheduling scheme by calculating the deviation between the actual execution result and the prediction, correcting the prediction model online, and forming a closed-loop self-learning mechanism.

The invention relates to the field of oil field energy supply, and discloses an oil field united station energy supply system and method based on carbon dioxide energy storage and waste water hydrogen production. The carbon dioxide energy storage device is configured to selectively store or release electric energy by using carbon dioxide generated by the oil field united station; the production load comprises a hydrogen production device, and the hydrogen production device is configured to produce hydrogen by using the production wastewater of the oil field united station; the power distribution device is electrically connected with the clean energy power generation device, the carbon dioxide energy storage device and the hydrogen production device; and the energy management device monitors the power generation power of the clean energy power generation device and the electricity utilization power of the production load, and controls the operation of the carbon dioxide energy storage device according to the power generation power and the electricity utilization power. The safe, efficient and stable energy supply system can be provided, the discharge amount of carbon dioxide and waste water can be reduced, and the utilization rate of clean energy is increased.

The application discloses a lossless and efficient data processing method and network interface card based on RMDA, and belongs to the field of data communication of a data center. When a large-scale QP is concurrent in the RMDA, the efficient scheduling processing problem of different QP requests is solved, the lossless request signal, the out-of-order QP request and the waste-free scheduling period are ensured, the scheduling fairness problem of different QPs is effectively solved in combination with congestion control, the blocking of other QP processing by a large message and the excessive number of requests needing to be processed in a single scheduling are avoided, and the head blocking problem is solved.

The utility model provides a waste heat recovery device for a steam pipeline, belongs to the technical field of waste heat recovery, and aims to solve the problems that high-temperature and high-pressure steam is transmitted for a long time in a conveying pipeline with too many bends, the consumption is high, the efficiency of converting the high-temperature steam into electric energy is not high, a pipeline system is complicated, and the conveying process needs to be detected. The heat utilization mechanism is mounted in the steam conveying pipeline; one end of the conveying mechanism is fixedly communicated with the heat utilization mechanism; the liquid control mechanism is communicated with the conveying mechanism; the steam conveying pipeline is arranged in the steam boiler and is resistant to high temperature and corrosion, the heat preservation performance is high, and a steam pipe network is monitored in real time; the heat utilization mechanism is inserted into the steam conveying pipeline to improve the steam utilization rate; high-temperature and low-temperature liquid flows in or out in a one-way mode, and auxiliary absorption of waste heat is rapidly completed.

The invention discloses a computing power resource dynamic slicing and isolation method for an artificial intelligence target range, and the method comprises the following modules: S1, business feature perception and dynamic resource slicing: carrying out the analysis and modeling of an artificial intelligence attack and defense task through a mechanism, and mapping a task demand into a corresponding computing power slicing specification; s2, a driving-level video memory firewall, which monitors the video memory usage behavior of the virtual instance in real time on a driving layer of an execution node, and prevents attack behaviors such as abnormal occupation of the video memory; and S3, carrying out atomized rollback based on the model state of the shared memory. According to the mechanism, rapid recovery of the environment is realized through page table resetting. The method is oriented to an artificial intelligence target range, and the problems of static low efficiency, insufficient safety and isolation, lack of a quick recovery mechanism and the like of resource scheduling are solved through the mechanisms.

The invention discloses a regional multi-microgrid cluster-oriented collaborative operation system, which relates to the technical field of power system dispatching and control, and comprises an asynchronous sensing fusion module, an asynchronous receiving and time axis reconstruction module, a time axis reconstruction module and a time axis reconstruction module, which are used for carrying out asynchronous receiving and time axis reconstruction on operation state data reported by a plurality of microgrid nodes; the credibility level is determined based on the communication link state and the data integrity, and weighted merging is carried out in the same time window according to the credibility level to form a unified state view; and the prediction difference modeling module is used for extracting state change characteristics among micro-grid nodes based on the state view, determining state offset information and a historical change boundary thereof, and taking the state offset information and the historical change boundary as numerical constraints of scheduling calculation. According to the system provided by the invention, through the asynchronous sensing fusion module, time axis reconstruction is realized on the basis of asynchronous data receiving, the credibility level of each piece of data is dynamically evaluated in combination with a communication link state and data integrity, and then weighted fusion is carried out in a unified time window.

The application relates to a dynamic distributed short-term scheduling method and system for short-term precipitation prediction, which comprises the following steps: inquiring whether new radar echo data is received in a preset storage folder; if the new radar echo data is received in the storage folder, the new radar echo data is segmented, and a plurality of calculation units are obtained after the segmentation; the segmented calculation units are stored, and the stored calculation units are dynamically allocated to each precipitation prediction processing machine; precipitation prediction is performed on the calculation units based on a preset space-time prediction model, and precipitation prediction results of the calculation units are respectively generated; the precipitation prediction results are combined and precipitation prediction data is generated. The application realizes efficient scheduling of multiple machines for dynamic distributed short-term scheduling.

The utility model provides a bank outlet delivery machine control system. The bank outlet delivery machine control system comprises a client, a delivery total device, a dispatching center and an outlet terminal. Data communication connection is established between the client and the delivery total device; and data communication connection is established between the delivery total device and the dispatching center and the network terminal. Wherein the delivery total device comprises a delivery middleware and a delivery transaction cloud, and the delivery middleware adopts an intelligent picking-up cabinet.

The present invention discloses a fast connection adaptive dispatching system based on the response of heterogeneous transfer demand based on travel characteristics, which relates to the technical field of traffic dispatching. The system includes a historical data processing unit, a prediction and analysis unit, a real-time monitoring unit and a response dispatching unit; the historical data processing unit is used to obtain historical transfer passenger flow data and extract the corresponding travel feature set; the prediction and analysis unit is used to train the demand prediction and analysis model using the travel feature set, and predict the transfer demand using the trained model; the real-time monitoring unit is used to collect the location, speed and passenger capacity information of public transportation in real time and monitor the passenger flow of transfer stations; the response dispatching unit is used to use genetic algorithms to perform dispatching simulation based on transfer demand and collected real-time data, and perform multi-mode traffic dispatching according to the optimal dispatching strategy. The present invention improves the efficiency and quality of traffic services and enhances the travel experience of passengers.

The invention relates to the technical field of power load monitoring, and particularly discloses an intelligent power grid energy storage distribution and scheduling system, which is characterized in that a power grid management area is divided into sub-management areas in order to realize efficient energy storage distribution and scheduling, and then the number of industrial power users and the number of residential power users in each sub-management area are sequentially acquired; calculating an electric energy distribution coefficient of each sub-management area according to the user number data of each sub-management area, then, distributing the electric energy of each sub-management area according to the electric energy distribution coefficient of each sub-management area, and meanwhile, distributing the electric energy of each sub-management area according to the electric energy distribution coefficient of each sub-management area; according to the invention, the electricity consumption change condition of each sub-management area in the peak electricity consumption period and the valley electricity consumption period is monitored in real time, and the electric energy scheduling coefficient of each sub-management area is calculated according to the electricity consumption change condition of each sub-management area; and judging whether the current sub-management area needs electric energy scheduling according to the electric energy scheduling coefficient of each sub-management area.

This application relates to the technical field of resource scheduling, and in particular to a task scheduling method, apparatus, and computer device. The method is applied to a scheduler and includes: in response to a task acquisition request reported by a computing container, determining a target task instruction from an instruction queue; wherein the instruction queue contains task flows of received tasks to be executed, and each task flow includes at least one task instruction; the computing container includes multiple threads, and the task acquisition request is generated by the computing container in response to the determination of an idle thread, where the idle thread is a thread in an idle state; generating an allocation instruction containing the target task instruction, and feeding the allocation instruction back to the computing container; the allocation instruction is used to instruct the computing container to call an idle thread to execute the target task instruction. The solution of this application can improve hardware utilization.

The application discloses a transmission line, wherein the transmission line comprises a first outer linear stator, a first bifurcated stator, a first inner linear stator, a cross stator and a first power line; the first outer linear stator transmits a mover in a first direction; the first bifurcated stator comprises a first confluence end, a first and a second bifurcation end, the first confluence end is spliced with the first outer linear stator; the first inner linear stator is spliced with the first bifurcation end and transmits a mover in a second direction perpendicular to the first direction; the cross stator comprises a first splicing end, a second splicing end, a third splicing end and a fourth splicing end arranged in sequence and perpendicularly, the first splicing end is spliced with the first inner linear stator; the first power line connects the first outer linear stator, the first bifurcated stator, the first inner linear stator and the cross stator in sequence. The technical scheme of the application can simplify the wiring mode of the transmission line.

The invention provides a real-time collaborative Web test capturing method and system based on multi-feature scoring, and relates to the technical field of Web automatic testing. According to the method, the interactive coordinates clicked by the user are obtained, cyclic penetration detection is carried out, and a candidate element sequence is output; then five-dimensional feature quantitative scoring is executed, a scoring result is output to select a target element, a corresponding unique identifier is generated, and a capture event is packaged; a change observer interface is used for monitoring change, and an anti-shake mechanism is combined to perceive the page steady state of the browser, so that when the page is structurally changed or redrawn, a related monitor is awakened, computing power is distributed, a target element is reselected, and a capture event is packaged, and when the page is stable, the capture event is sent to a back-end server. And broadcasting to other cooperation terminals in the same room is facilitated. According to the method, the problems of misalignment of element positioning and low cooperation efficiency can be effectively solved, and efficient real-time cooperation and financial-level data security protection of distributed crowdsourcing testing are realized while system resource loss is reduced.

The invention provides a mining digital program control scheduling communication method and system, the system comprises a scheduling host at the bottom of a main roadway and static communication positioning base stations in auxiliary roadways, firstly, an underground three-dimensional environment map is created, and secondly, a carry-on communicator of a miner transmits voice information to a nearby communication base station; the latter identifies the speaker identity and the content as requesting communication or non-requesting communication. If the communication is request communication, the system converts the content into digital information and transmits the digital information to the digital stored program control exchange through the ring network exchange to realize effective communication above and below the well; and if the communication is not requested, activating the adjacent positioning base station, measuring the distance and transmitting the information to the scheduling host. And the dispatching host positions the accurate position of the speaker on the three-dimensional map according to the distance information of the two base stations, and outputs a result to the main control center. The system not only effectively improves the intelligent management and scheduling capability, but also enhances the safety and emergency response capability of a mine, and provides a solid foundation for the modern development of coal mine operation.

The invention relates to the technical field of network transmission optimization, and provides a data transmission method and device. The method comprises the steps of receiving credit authorization information sent by a receiving end, wherein the credit authorization information is used for authorizing a sending end to transmit to-be-transmitted data based on a credit authorization amount; determining a transmission performance index of each data transmission path; determining a credit allocation weight of each data transmission path according to the transmission performance index; determining the target credit of each data transmission path according to the credit authorization amount and the credit allocation weight of each data transmission path; and based on the target credit of each data transmission path, distributing the to-be-transmitted data to the corresponding data transmission path for transmission. According to the data transmission method provided by the invention, multi-path data transmission under active control is realized, and the robustness of data transmission and the resource utilization rate are improved.

Embodiments of the present disclosure disclose a data processing method based on reinforcement learning, an electronic device and a readable medium. The method is applied to an execution node, a policy node and a training node included in a reinforcement learning system, and a specific implementation of the method comprises: performing environment simulation by the execution node to obtain an observation result; performing policy updating by the training node according to a training sample and a model to be trained, wherein the training sample is transmitted from the execution node to the training node through a sample transmission stream; the policy node performs policy inference according to the observation result and updated policy information, wherein in a non-in-line inference mode, the execution node and the policy node perform data transmission on the observation result and an action to be executed through an inference transmission stream; and the execution node executes the action to be executed to generate an updated observation result. The implementation realizes effective scheduling of large-scale computer hardware resources, meets the training requirements for complex reinforcement learning tasks, and improves the training speed.

The invention belongs to the field of multi-energy power system dispatching, and relates to a water-wind-light power source base power generation dispatching method considering alternating current and direct current peak regulation requirements. The method comprises the following steps: firstly, constructing an optimal scheduling model containing time and space double dimensions; in the aspect of time, a differentiated objective function is adopted in a dry period, the dry period minimizes the sum of squares of residual loads of an alternating current receiving end to smooth the loads, and the flood period minimizes the system abandoned electric quantity to guarantee clean energy consumption. In space, the model overall plans multiple types of actual constraints such as cascade hydraulic connection, upstream and downstream collaboration, water and electricity distribution proportion, direct-current stepped power and standby, and differential peak regulation driving is implemented on alternating-current and direct-current receiving ends. And through model solution, optimal distribution of base output among multiple receiving ends and cascade power station cooperative scheduling are realized. According to the method, the resource utilization efficiency and the power grid operation safety are remarkably improved, and a reliable method is provided for efficient scheduling of the alternating-current and direct-current hybrid delivery clean energy base.

The present invention discloses a method for monitoring and managing engineering construction based on Internet of Things simulation, including determining the construction planning scheme of the current engineering project; screening the abnormal construction links of cost deviation through simulation simulation, when it is determined that the simulation construction cost is greater than the planning cost, obtaining the planned construction period and resource allocation scheme of the abnormal construction link, using LSTM model to predict the weather change trend and resource price fluctuation trend within the planned construction period, and performing cost sensitivity analysis on the abnormal construction link; if the sensitivity is greater than the second preset threshold, judging whether there is a schedulable construction link that has no dependency on the abnormal construction link; if so, calculating the resource matching degree between the resource allocation scheme of the abnormal construction link and the schedulable construction link, screening out the one with the highest matching degree as the target scheduling link to update the abnormal construction link. The present invention can schedule the order of abnormal construction links according to the simulation cost deviation, thereby optimizing the construction plan and reducing construction costs.