50results about How to "Accurate scheduling" patented technology

The invention belongs to the technical field of island integrated energy systems, and particularly discloses a short-time scale low-carbon optimal scheduling method and system for an island integrated energy system, and the method comprises the steps: constructing an electricity-hydrogen-heat multi-energy coupled island integrated energy system model; constructing a real-time stepped carbon transaction model based on the interval to which the carbon emission quota participating in the carbon emission transaction belongs by using an island integrated energy system model; on the basis of a real-time stepped carbon transaction model, deviation penalty of new energy prediction is considered, one day is divided into n scheduling cycles, n is an integer larger than 1, a target function is constructed with the highest total income of a system as an optimization target, the optimization target is solved, and an optimized scheduling result is obtained. According to the invention, wind energy, solar energy, wave energy, stored energy, a photo-thermal power station and other energy sources are co-scheduled with electricity, hydrogen and water loads to form a dynamically balanced energy system; and high consumption and low carbon emission are kept as far as possible.

The invention relates to the technical field of power grid demand response, and discloses a power grid dispatching demand response system and method.The system comprises a state vector generation module, a state sequence generation module, a demand factor extraction module, a factor correlation analysis module, a weighted feature generation module and a resource dispatching module; the method comprises the following steps: generating a state estimation value of a power grid, carrying out vector coding to obtain a state vector, carrying out splicing and dimension reduction to obtain a state sequence, extracting demand factors from demand data, calculating a relationship among the demand factors through correlation analysis, weighting the demand factors according to factor correlation to obtain demand weighting characteristics, and finally, obtaining a state estimation result. And a load management strategy is generated based on the characteristics and the state sequence, so that resource scheduling is performed on the power grid according to the load management strategy, and the accuracy of power grid scheduling demand response is improved.

The invention discloses a thread management method and device, equipment and a storage medium. A target task is determined from a task queue, a target thread is determined from idle threads, and the target thread is scheduled to execute the target task. The execution state of the target task is monitored, and when it is monitored that the execution state is cancelled, execution of the target task is stopped, and a new target task is determined again from the task queue. Thus, by directly packaging the target function into the target task and scheduling the thread to execute the corresponding target task, the process of matching the operation language with the thread pool can be omitted, the thread pool is accurately scheduled, the situation that more memory needs to be occupied when the execution state of the target task is cancelled by adopting a lock mechanism is avoided, and the user experience is improved. And the service execution efficiency is ensured.

The invention discloses a three-dimensional map collecting and updating method and device and electronic equipment, and belongs to the field of map updating. Only the data collected by the unmanned aerial vehicle can update the base map of the current three-dimensional map, so that when the position of the to-be-collected area is not the existing position on the current three-dimensional map, at least the data collected by the unmanned aerial vehicle is needed, and when the position of the to-be-collected area is the existing position on the current three-dimensional map, the base map does not need to be updated. Therefore, the unmanned aerial vehicle and the collection vehicle can be used as execution equipment. According to the scheme, after the position of the to-be-collected area is obtained, the execution equipment is automatically determined according to the area data of the to-be-collected area, the collection task is generated, the three-dimensional map is automatically updated based on the collected data, manual participation is not needed, cost is low, efficiency is high, rapid changes of the terrain and texture of a working site can be reflected in time, and working efficiency is improved. Reasonable planning and accurate scheduling of operators are effectively supported.

The invention relates to the technical field of copper foil production, and provides an intelligent scheduling method and device for copper foil production, computer equipment and a storage medium. An initial intelligent scheduling strategy is simulated and generated based on production data of each piece of copper foil production equipment on a copper foil production line, and primary simulation optimization is performed by using a pre-constructed optimization model; calculating production data and product images before and after optimization to obtain an optimization stopping factor value; when the optimization stopping factor value is greater than a threshold value, performing simulation optimization again by using a pre-constructed optimization model; when the optimization stopping factor value is smaller than a threshold value, iteration simulation optimization is stopped, and a target intelligent scheduling strategy is obtained; and generating an intelligent scheduling instruction based on the target intelligent scheduling strategy and sending the intelligent scheduling instruction to the corresponding copper foil production equipment in real time so as to realize intelligent scheduling of copper foil production. According to the invention, the operation sequence and the operation time of each production device can be automatically adjusted, and intelligent and automatic scheduling of copper foil production is realized.

The invention discloses a spacecraft task scheduling method and system, electronic equipment and a storage medium, and relates to the technical field of spacecraft task scheduling, and the method comprises the steps: calculating and obtaining a total score of a preset to-be-scheduled spacecraft task according to a criterion layer weight vector and a factor layer score vector corresponding to the preset to-be-scheduled spacecraft task, and performing priority ranking on all the to-be-scheduled spacecraft tasks according to the size of the total score of each to-be-scheduled spacecraft task, and scheduling and executing all the to-be-scheduled spacecraft tasks according to a priority ranking sequence. Based on the fuzzy hierarchical comprehensive analysis, the accuracy and interpretability of the priority evaluation of the spacecraft tasks can be improved, the priority ranking sequence is more accurate and reliable, and accurate scheduling and execution of the spacecraft tasks can be realized.

The invention relates to the technical field of network communication management, and discloses a system and a method for establishing a VPN (Virtual Private Network) data flow acceleration model, and the method comprises the following steps: distributing an IP (Internet Protocol) address for access equipment through a DHCP (Dynamic Host Configuration Protocol), and obtaining the IP address of a message queue telemetry transport protocol (MQTT) server; and the access device registers identity information through the MQTT and stores the identity information. And performing batch management on the access equipment according to the subscription mechanism of the MQTT server, wherein the management content comprises equipment configuration, operation state, terminal access and batch upgrading. Meanwhile, VPN data features and historical data features of the access device are obtained and stored, a VPN data flow classification model is established based on the features, and the VPN features of the device are substituted into the model to obtain a classification result. And finally, obtaining real-time performance data of a network link, determining an effective link according to a demand relationship between the real-time data and a classification result, and selecting an optimal path transmission mechanism based on the effective link so as to optimize the transmission performance of the VPN data stream.

The present invention provides a virtual-reality combined simulation system and method supporting large-scale unmanned aerial vehicle cluster flight tests, belonging to the field of unmanned aerial vehicle cluster simulation. To solve the problems of low fidelity of large-scale unmanned aerial vehicle clusters and multiple limitations of virtual-reality combined simulation in existing software simulation systems. Combining virtual unmanned aerial vehicle clusters with real real-time unmanned aerial vehicle clusters, simulation support for the underlying environment is provided, covering cluster scheduling algorithms, task allocation algorithms, formation control algorithms, dynamic control algorithms, and three-dimensional visualization frameworks, to achieve task requirement data analysis, task allocation and optimization scheduling, cluster command and control formation flight, cluster measurement and control and status monitoring, and intelligent collaboration of human-machine terminals. The present invention realizes effective verification of large-scale unmanned aerial vehicle clusters in performing tasks through a parallel simulation method that combines virtual unmanned aerial vehicle flight nodes with real unmanned aerial vehicle flight nodes, which has important theoretical significance and application value for promoting the verification of key technologies of unmanned aerial vehicle clusters and the practical application of unmanned aerial vehicle clusters.

The invention provides an intelligent building method for a parameterized three-dimensional power grid frame, and relates to the technical field of electric power, and the method comprises the steps of first collection, second collection, third collection, model construction, demand prediction, power grid division, first setting, architecture construction and the like. The charging demand fluctuation condition of the electric vehicle can be dynamically monitored, the power grid is divided by adopting the clustering algorithm according to the charging demands and regional characteristics of different regions, the load center is set based on the power grid division result, and the power grid architecture is constructed. The constructed power grid architecture can better cope with the conditions of power load fluctuation and power load regional difference caused by popularization of electric vehicles, the dynamic response capability of the power grid is enhanced, and the stability of the power grid is improved.

The present invention discloses an intelligent medical service integrated management system and method, which relates to the field of integrated management technology, including: the intelligent medical service integrated management system and method, by implementing the generation of a drug dispatching plan for drugs to be called with sufficient inventory, can achieve mixed treatment of multiple drugs for one disease under the premise of ensuring the side effects of drugs, can reduce the loss of a single type of drugs while ensuring the therapeutic effect of drugs, and avoid a sudden reduction in the number of drugs due to frequent use of the same drug. At the same time, by implementing the generation of a drug dispatching plan for drugs to be called with insufficient inventory, can achieve treatment of multiple diseases with one drug under the premise of ensuring the side effects of drugs, can avoid the situation where there is no medicine to treat in an emergency situation while ensuring the therapeutic effect of drugs, and can ensure the normal medication treatment of patients in an emergency situation.

The invention relates to the technical field of computers, and discloses a personnel scheduling information generation method and device, equipment, a medium and a program product, and the personnel scheduling information generation method comprises the steps: receiving first target region description information, first population description information and second target region description information; generating target region area information and first proportion information by using the first target region description information and the first population description information; generating second proportion information by using the second target area description information; generating first personnel placement information according to the second target region description information and the target region area information; processing the first proportion information and the second proportion information to obtain a personnel placement coefficient; judging whether the personnel placement coefficient is greater than a preset value; and if yes, updating the first personnel placement information as personnel scheduling information through a personnel placement coefficient. According to the method, the area proportion of the garden plot collected by the target area is considered, and the obtained personnel scheduling information is more accurate.

This invention discloses a method and system for verifying the functionality of a vector processor. The method unifies matrix, vector, and scalar data formats into a matrix type using a reference model. Multi-input interface data is stored in corresponding data queues in the form of address plus data. The required computational data is extracted according to the current instruction, and unused data is stored back to the original queue. Expected output data at the clock cycle level is generated and compared with the actual output data of the vector processor to determine functional correctness. The system includes an instruction generator module, a controller module, a data generation module, a reference model module, a data collection module, and a data comparator module. This invention can improve the accuracy of vector processor fault location, simplify verification logic, and improve overall verification efficiency.

The present application provides a method and device for optimizing a CPU energy efficiency model, the method comprising: recalculating the static power consumption of each CPU frequency point at the current temperature after the CPU temperature changes; and updating the energy efficiency model according to the static power consumption. The present application scheme can accurately predict the CPU power consumption and ensure the accuracy of the energy efficiency model.

The application discloses to the elevator dispatching technical field, specifically is based on edge computing building elevator group intelligent dispatching control system, including edge computing gateway module, group control collaborative scheduling module, local real-time decision module, elevator direct connection interaction module, cloud closed loop iteration module, multi-source perception fusion module, stop optimization scheduling module, network outage autonomous operation module, the application has the beneficial effect: according to total floor and elevator quantity average stop floor is calculated, and minimum mobile journey priority algorithm is adopted adaptive scheduling, completely solve the traditional elevator random stop or only return to the first floor, the distance is too far when calling elevator, the problem of long waiting time, significantly shorten the waiting time, improve user experience, effectively avoid repeated response, bunch up and stop and idle running, improve the overall transport efficiency of elevator group, reduce equipment wear and tear and operating energy consumption.

The invention belongs to the technical field of cloud computing, and particularly relates to a server equipment load real-time prediction method. The method comprises the following steps: collecting an equipment parameter sequence of a server in a past period of time, and dividing the equipment parameter sequence into a sample sequence and a label sequence; the sample sequence and the tag sequence are preprocessed; for the preprocessed sample sequence, clustering each coverage according to the service information, so that the similar coverage is clustered into one class, and introducing a timestamp to obtain a final sample sequence; establishing a random forest regression prediction model by adopting a random forest regression algorithm; inputting the final sample sequence and the tag sequence into the random forest regression prediction model for training to obtain a trained real-time prediction model; and inputting the equipment parameter sequence of the server in the current time period into the trained real-time prediction model to obtain the current load parameter of the server. According to the method, the load prediction accuracy is effectively improved.

The invention discloses a multi-layer automatic seedbed system which comprises a rack main body and is characterized in that a motor assembly seat is fixedly mounted on the lower side of the rack main body, a servo motor is fixedly mounted on the motor assembly seat, a driving gear is arranged at the driving end of the servo motor, and the driving gear is in meshed connection with a first transmission chain; the invention relates to the technical field of automatic seedbeds, and has the beneficial effects that a multi-layer metal frame forms a framework of a system, provides stable support and realizes intensive utilization of a vertical space, and a chain and chain wheel conveying system is a key for realizing automation. The system can drive the seedling raising plates to horizontally move or vertically ascend and descend among all the layers, the space efficiency is extremely high, the most prominent advantage is that through three-dimensional stacking, the production capacity of the unit occupied area is multiplied, and the system is very suitable for intensive production in environments such as greenhouses and plants with high space cost.

The invention relates to power dispatching, in particular to a power dispatching method, which comprises the following steps of: constructing a power system historical dispatching knowledge graph containing historical dispatching data and historical dispatching knowledge data; matching the scheduling data of the scheduling day with historical scheduling data to obtain a first similarity data set of the scheduling data; matching the scheduling text data of the scheduling day with historical scheduling knowledge data to obtain a second similarity data set of the scheduling text data; fusing the first similarity data set and the second similarity data set by taking a preset time length as a unit to obtain a fused similarity data set; matching data in the fusion similarity data set with historical scheduling knowledge data, fitting to obtain a power generation curve of a scheduling day, and regulating and controlling the power system according to the power generation curve; acquiring a voltage signal and a current signal of the transformer substation in real time, and calculating to obtain a power factor; according to the technical scheme provided by the invention, the defect that the power system is difficult to accurately and timely dispatch can be effectively overcome.

The application relates to the technical field of intelligent communication evaluation, and discloses a Chinese traditional culture intelligent communication effect evaluation method and system. The method comprises the following steps: analyzing original culture communication content, extracting element features such as cultural connotation, emotional color and historical background; collecting direct interaction records and indirect behavior tracks of audiences; performing grid-by-grid matching and superposition of the element features and audience feedback in a preset space-time grid; quantitatively scoring the superposition data according to preset weights and rules; introducing initial scores into a simulator based on a culture communication law model to perform dynamic evolution calculation; performing multi-round iteration optimization on the evolution result by using incremental feedback data to generate an evaluation value; and mapping the evaluation value into a correction instruction for content form, communication channel and presentation rhythm. The method realizes fine evaluation and dynamic trend prediction of communication effect in the space-time dimension, and supports accurate optimization and adaptive adjustment of a communication strategy.

The application relates to a data processing method and device, computer equipment and a storage medium. The method comprises the following steps: obtaining a multi-dimensional feature of a data unit in to-be-processed data; obtaining a feature weight of the multi-dimensional feature according to a preset business target; obtaining a priority of each data unit according to the feature weight and the multi-dimensional feature; generating a non-uniform splitting scheme for splitting the to-be-processed data into multiple data unit combinations according to the priority of the data unit and real-time state information of each business processing node in a distributed cluster; splitting and performing parallel computing operation on the allocated data unit combinations based on each business processing node to generate a lightweight intermediate result; aggregating the intermediate results generated by each business processing node to obtain an initial result; and performing consistency checking on the initial result based on a hash function, and taking the initial result as a data processing result if the consistency checking is passed. The method can improve resource utilization.

The invention relates to the technical field of law enforcement boat dispatching, in particular to a law enforcement boat dispatching system and method.The method comprises the following steps that a standard law enforcement signal information sending range is set, law enforcement boats with law enforcement signals within the standard law enforcement signal information sending range are determined, and distance analysis is conducted on the law enforcement boats and the law enforcement signals; obtaining a total advancing coefficient; and performing state analysis on all the law enforcement boats with the law enforcement signals within the standard law enforcement signal information sending range to obtain state coefficients of the law enforcement boats. By comprehensively considering factors of law enforcement boats, law enforcement signal distances, boat states and law enforcement officer capabilities, boats more suitable for task execution in hardware conditions and personnel allocation are screened out, the efficiency of law enforcement task completion is improved, selection is performed from a descending set according to the number of boats required by law enforcement signals, resource waste is avoided, and the efficiency of law enforcement task execution is improved. It is ensured that the number of the invested law enforcement boats can meet the law enforcement task requirement, and precise scheduling is achieved.

In a method for scheduling jobs in a storage device, a first job is executed. While the first job is being executed, a first timestamp for the first job is pre-updated based on a predefined operation schedule representing a relationship between an operation of the storage device and an operation time. While the first job is being executed, a scheduling request associated with a second job to be executed after the first job is received. While the first job is being executed, a scheduling operation for selecting the second job is pre-executed based on the scheduling request and the timestamp.

The invention discloses a field operation energy scheduling system based on a Markov chain structure, and relates to the technical field of battlefield energy scheduling, and the field operation energy scheduling system comprises an intelligent prediction module, an energy aggregation module, an energy routing module, a control module, a communication and monitoring module and an energy management module. The system has the advantages that the energy demand, the weather condition and the equipment state on the battlefield are monitored and predicted in real time through the intelligent prediction module, accurate prediction is performed by using the Markov chain model, dynamic networking and rapid scheduling of power resources are realized, the flexibility of a battlefield power system is improved, and the power utilization rate of the battlefield power system is improved. The system can quickly adjust power output according to real-time conditions, meets complex and changeable battlefield requirements, realizes quick transmission and distribution of electric energy through flexible configuration of the energy routing module, and further improves the response speed of the system.

This disclosure relates to a method, apparatus, electronic device, and storage medium for determining a production calendar. The method for determining a production calendar includes: acquiring target resources required to produce a target product during a target time period; determining a target production line corresponding to the target resources and determining a first working duration, the first working duration representing the time required for the target production line to produce the target resources within the target time period; determining a production calendar matching the first working duration as an initial production calendar; determining time-influencing factors corresponding to the production of the target resources by the target production line within the first working duration, and determining the capacity loss duration corresponding to the target production line based on the time-influencing factors; adjusting the daily working durations recorded in the initial production calendar so that a second working duration obtained after adjusting the daily working duration becomes the first working duration, thereby obtaining a target production calendar, where the second working duration is the difference between the total working duration and the capacity loss duration of the initial production calendar. This disclosure improves the accuracy of the production calendar.

The embodiment of the invention discloses an omnidirectional distributed machine learning cooperation method, system and device, and the method comprises the steps: monitoring the resource information corresponding to a computing power resource party and a data resource party in real time, and transmitting and storing the latest resource information in a relay chain; when the relay link receives a training task of a model training party, selecting a target computing power resource party and a target data resource party according to related parameters of the training task, and generating a training scheme; distributing a distributed training task to a target computing power resource party and a target data resource party according to the training scheme; and the target computing power resource party executes the distributed training task and sends state information in the training process and result information after training is completed to a relay chain. Cooperative training of data and computing power is realized in a multi-chain environment, so that the efficiency, safety and traceability of distributed model training are improved.

The invention discloses a high-gain dual-polarized directional antenna, which comprises an antenna body and an antenna mounting bracket used for rolling the antenna body and adjusting the pitch angle of the antenna body, the antenna body comprises a feed network board, and a first antenna array and a second antenna array which are arranged in parallel are mounted on the feed network board; each of the first antenna array and the second antenna array comprises three rows of longitudinal arrays which are parallel to each other, and radiation units in two adjacent rows of longitudinal arrays are arranged in a staggered manner so as to be spaced by a first wavelength distance in a vertical plane direction; it can be understood that the antenna provided by the invention can effectively reduce the sidelobe level of the horizontal plane through the staggered arrangement of the radiation units in the double-antenna array so as to reduce the cross-zone interference, so that the trains running in opposite directions at high speed can receive the main beam signal coverage more accurately, and the accurate scheduling is realized.

The embodiments of the present application provide a node scheduling method, device, and storage medium based on a content distribution network, and the node scheduling method includes: after obtaining a request from a terminal, obtaining the IP address of the terminal from the request to obtain a target IP address; finding the area corresponding to the target IP address from the mapping relationship between the area and the IP address pool, and using the found area as the target area; wherein the mapping relationship between the area and the IP address pool is obtained from the backbone router based on the connection with the backbone router; determining the target CDN node whose deployment location corresponds to the target area from the multiple CDN nodes included in the content distribution network; and scheduling the target CDN node to the terminal. The technical solution of the embodiments of the present application can determine a new target area from the backbone router when the target area of ​​the terminal changes, and schedule the CDN node according to the new target area, thereby improving accuracy.

The present application relates to a carbon quota scheduling method, device, equipment, storage medium and program product. The method includes: obtaining the historical carbon emission data and historical electricity-clearing power data of the target electricity user, and obtaining the historical power generation-clearing power data of the target power generation subject; wherein the target power generation subject includes the renewable energy power generation subject and the non-renewable energy power generation subject; determining the equivalent carbon emissions of the target power user based on the historical power generation-clearing power data and historical electricity-clearing power data of the renewable energy power generation subject, determining the carbon quota transfer data when scheduling the target carbon quota based on the equivalent carbon emissions; scheduling the target carbon quota based on the carbon quota transfer data. The use of this method can improve the reliability of carbon quota scheduling and make energy-saving and emission reduction measures more accurate and effective.

The present invention discloses a networked traffic signal light controller and an intelligent control method for traffic signal lights with priority for emergency vehicles. The networked traffic signal light controller is used to execute an intelligent control method for traffic signal lights with priority for emergency vehicles. The method makes full use of traffic density information of ordinary vehicles and networked emergency vehicle information to realize ordinary vehicle scheduling and multi-priority emergency vehicle scheduling, and solves the task of vehicle scheduling at traffic intersections. In the traffic scenario where emergency vehicles of multiple priorities appear on the road and emergency vehicles enter at the same time in multiple phases, the present invention realizes the timing scheduling and control of the signal lights of networked emergency vehicles and ordinary vehicles, can accurately handle the problem of priority passage of emergency vehicles, and enable emergency vehicles to quickly pass through the intersection while ensuring safety. At the same time, the efficiency of vehicles passing through the intersection is improved, proving the practicality of a networked traffic signal light controller and an intelligent control method for traffic signal lights with priority for emergency vehicles.

The invention relates to a rail station shared bicycle classification scheduling method based on parking position perception, and the method comprises the steps: monitoring a shared bicycle parking region around a rail station, and obtaining the number, states and operator types of shared bicycles around the rail station in real time through a pre-trained parking position perception model; determining a corresponding operation strategy according to the number and the state of the shared bicycles and the types of operators to which the shared bicycles belong and in combination with the station types of the rail stations; according to the operation strategy, scheduling demands of shared bicycles around the rail station are predicted in real time, and scheduling suggestions are generated; and according to the generated scheduling suggestion, carrying out classified scheduling on the shared bicycles around the rail station. According to the method, efficient classified management and balanced distribution of the shared bicycles are realized through accurate perception and intelligent scheduling, the resource utilization efficiency and the user experience are remarkably improved, the operation cost is reduced, and the urban traffic resource allocation is optimized.

The present invention proposes a method, device, equipment and storage medium for regulating resources in a virtual power plant in seconds. By extracting key information features from the operating data of various adjustable resources of edge nodes and uploading them to the cloud. The cloud predicts the optimal regulation strategy and then feeds back the strategy to the edge node through low-latency communication technology. Before local execution, if there is no identical strategy in the cache, the received strategy will be decomposed into sub-strategies and stored. During execution, resource regulation is performed according to the sub-strategy queue in the cache. In addition, sub-strategies suitable for the current situation can be retrieved from local storage for application. The entire process optimizes the cloud-edge collaboration mechanism, reduces the time cost of data transmission and processing, and enables the powerful computing power of the cloud to be fully utilized for data analysis and intelligent decision-making, while the edge focuses on rapid response and instruction execution, jointly realizing efficient and accurate management and scheduling of virtual power plant resources.