49results about How to "Quick dispatch" patented technology

The invention discloses a low-orbit communication satellite load multilink cooperative transmission system, and belongs to the technical field of satellite communication. In order to solve the problems of insufficient link reliability, low utilization rate of resources in constellations, weaker emergency response and fault-tolerant capability and higher operation cost, the invention is composed of a plurality of low-orbit communication satellites, realizes global seamless coverage through reasonably deployed constellation configuration, ensures that a user can obtain stable communication service in any area, and improves the user experience. A multi-link cooperative communication mechanism is adopted, through real-time link quality evaluation and dynamic link selection, rapid switching of link faults is achieved, communication reliability is improved, a dynamic path adjustment technology is combined, a forwarding path of data in a constellation is optimized according to an actual link state, data transmission time delay is effectively reduced, and data transmission efficiency is improved. According to the time-space change of the flow demand, communication link resources are scheduled in real time, the utilization efficiency of system resources is optimized, and the communication demand of a high-priority task is guaranteed.

The invention relates to the technical field of material storage management, in particular to a BIM-based construction site material monitoring management method and system. The method comprises the following steps: obtaining a construction project drawing; performing drawing information extraction on the construction project drawing to obtain construction project material information data and construction project structure data; performing construction project three-dimensional modeling on the construction project material information data and the construction project structure data to generate construction project three-dimensional modeling data; obtaining total construction material data; and carrying out material information modeling on the total construction material data by using a BIM technology to generate total construction material modeling data. According to the invention, accurate three-dimensional modeling, intelligent marking, regionalized storage and real-time allocation of the construction site materials are realized through the BIM technology, and the accuracy of construction site material monitoring management and the emergency response real-time performance are improved.

The invention discloses an industrial Internet of Things edge computing unloading method and system based on a distributed deep neural network, and the method comprises the following steps: firstly, introducing a feature matrix of an attention mechanism optimization task, transmitting the optimized task features to a multi-layer deep neural network DNN, and generating an unloading decision set in parallel; allocating resources for each task; after the to-be-unloaded task is preliminarily selected, computing resources of the high-priority task are preferentially guaranteed in the resource allocation stage according to the priority and deadline of the task. For tasks with relatively large calculation amount or relatively high priorities, decision storage is performed by using a cache strategy to optimize unloading and resource allocation processes of subsequent similar tasks, so that efficient and low-delay task unloading in a large-scale and multi-task environment is realized. Meanwhile, a distributed cache updating mechanism is utilized in each unloading time slot, the unloading decision precision is continuously optimized, and the unloading efficiency and the overall stability of the system are improved.

The invention relates to the technical field of data processing, and discloses a method, device and equipment for constructing a lightweight data warehouse based on an MPP architecture, and the method comprises the steps: collecting data in a plurality of mainstream databases through a DataX collection assembly, and writing the collected data into a Dores data lake to obtain offline data; the method comprises the following steps: acquiring data of a plurality of data sources through a RoutingLoad component and a Kafka component, and writing the data into a Dores data lake to obtain real-time data; establishing a data hierarchical structure; performing calculation and analysis processing to generate a data calculation result; constructing a data asset catalog based on a metadata system of a Dores data lake to perform classified management of libraries, tables and fields; the data service interface is constructed based on the data asset directory, the BI report tool is connected with the data service interface to generate the data analysis report, and the data calculation result and the data analysis report are output to the outside, so that the construction and maintenance cost of an enterprise is reduced, and the requirements in a big data environment can be better met.

The invention provides a network computing power energy sensing network, a resource measurement method, a resource measurement device and a program product. The method comprises the following steps: determining a current available resource corresponding to an infrastructure through a resource sensing unit; before the calculation task is executed, resources needed for executing the calculation task are measured through a measurement device based on the task type, the task scene and the task load corresponding to the calculation task, target resources are obtained, and resource configuration is carried out according to the target resources and resources corresponding to the infrastructure; in the execution process of the calculation task, generating predicted available resources corresponding to the infrastructure in the target period through a measurement device based on the current time feature and the task feature corresponding to the calculation task; performing resource configuration according to the predicted available resource, the current available resource and the target resource; the problem that a single resource measurement index is difficult to meet the requirements of task types and task scene complexity can be solved; and the requirements of task type and task scene complication can be comprehensively and accurately met.

The invention relates to computer task processing, in particular to an efficient tagging check task processing system and method, a task decomposition and distribution module is used for decomposing a complex service request into a plurality of sub-tasks and intelligently distributing the sub-tasks; the concurrent execution engine is used for selecting a proper concurrent strategy according to task types and requirements, and performing multi-task concurrent execution based on the concurrent strategy through a concurrent execution model; the asynchronous task management module supports creation, scheduling, execution and result callback of asynchronous tasks, and simplifies asynchronous logic processing by introducing an asynchronous programming mode; the task scheduler is used for realizing asynchronous transmission and queue management of tasks by using the message queue and dynamically scheduling the tasks in the queue; according to the technical scheme provided by the invention, the defects of unreasonable resource allocation, poor task scheduling flexibility and low task execution efficiency in the prior art can be effectively overcome.

The embodiment of the invention discloses a picking rechecking task management method and device, equipment and a medium, and the method comprises the steps: obtaining picking task information and picker information corresponding to a picking task in an ongoing state, and the working state information of a rechecking table; performing information prediction according to the acquired information to obtain a residual picking time length, an average transportation time consumption of transporting the goods to each rechecking station, a first estimated time consumption of processing an uncompleted picking rechecking task by each rechecking station and a second estimated time consumption of completing a to-be-allocated picking rechecking task corresponding to the picking task by each rechecking station; and determining a target review station corresponding to each to-be-allocated order picking review task according to the predicted information by taking the shortest review completion estimation time of all the to-be-allocated order picking review tasks as a target task scheduling result so as to perform task scheduling management. According to the technical scheme of the embodiment of the invention, manual scheduling of the picking rechecking task can be replaced, the task scheduling cost is reduced, and the task scheduling efficiency and effect are improved.

The invention discloses a soft load balancing cluster capacity expansion system, method, device, medium and product, which are applied to the field of cloud computing, and the system comprises a soft load cluster management and control module which is used for obtaining the cluster busy degree of a soft load balancing cluster, obtaining a capacity expansion condition and a capacity expansion strategy, and when the cluster busy degree reaches the capacity expansion condition, sending the capacity expansion strategy to the soft load balancing cluster; generating a capacity expansion instruction according to the capacity expansion strategy, and sending the capacity expansion instruction to a temporary resource pool scheduling module; and the temporary resource pool scheduling module is used for generating a cluster capacity expansion task list based on the capacity expansion instruction, and starting the soft load balancer corresponding to the temporary resource pool as the soft load balancer to be expanded. The running state of the soft load balancing cluster can be monitored in real time, the capacity expansion instruction is automatically generated according to the preset capacity expansion condition and strategy, and the accuracy and timeliness of capacity expansion decision making are improved. And the soft load balancer is scheduled from the temporary resource pool for capacity expansion, so that the resource utilization efficiency and the emergency efficiency are improved, and the service loss caused by the resource bottleneck of the server is reduced.

The invention relates to an application release management system and an application release management method based on a credential environment, and the system comprises an infrastructure layer which is used for constructing the credential environment according to hardware resources; the publishing system platform layer is used for deploying at least one publishing platform, and the publishing platform is used for publishing an application; the presentation layer is used for providing a user interaction interface and acquiring configuration information of a user; the third-party tool layer is used for providing a release mirror image; the application layer is used for executing an application publishing task according to the publishing platform, the configuration information and the publishing mirror image, and the application layer comprises one or any combination of a login verification module, a publishing window management module, an application module management module, a publishing peripheral resource management module, an application service management module and a publishing configuration management module; and the logic layer is used for carrying out logic abstract packaging on the business of each module in the application layer. According to the invention, applications can be published and managed efficiently and safely in a unified manner.

The invention relates to the technical field of power dispatching, and discloses a demand side resource dispatching method and system based on different scene adjustment of a power grid, and the method comprises the steps: obtaining the historical data of a load abnormal quantity and an abnormal change duration index; classifying the power grid scenes according to the obtained historical data to obtain different power grid scenes; carrying out analysis according to the load curve characteristics in different power grid scenes, obtaining adjustment requirements of the power grid in different scenes, and establishing callable resource libraries matched with the power grid in different scenes; the scenes are trained and learned through an MLP model, and different scenes are identified in combination with corresponding evaluation indexes so as to verify the validity of scene identification; scene adjustment is realized by building scheduling models and constraint models of different scenes of a power grid. According to the method, the power grid scenes are effectively classified, the types of the demand side resources in the resource library, the response time period, the response speed and the response cost information are clarified, and rapid adjustment and accurate scheduling of the power grid are realized.

The invention provides an urban infrastructure damage real-time monitoring and response method and system. A plurality of image sensors arranged at a plurality of key parts of urban infrastructure are used for acquiring images of the infrastructure in real time and constructing an image sample library of infrastructure damage through acquired image data; receiving and processing the image data, and extracting key features; and processing and analyzing the real-time monitoring image data, identifying the damage condition of the infrastructure, and evaluating the damage degree. Through infrastructure damage feature memory and a generalization association technology based on diffusion generation, real-time monitoring, accurate identification and rapid response of urban infrastructure damage problems are realized. According to the invention, the efficiency and accuracy of city management and emergency rescue are improved, and powerful data support is provided for intelligence and refinement of city management.

The invention discloses a parallel simulation task delay optimization method and device, equipment and a storage medium, and the method comprises the steps: obtaining delay attribute data of each task node in a target simulation critical path, the target simulation critical path comprising a root node and a plurality of child nodes; calculating the rank of each task node according to the delay attribute data to obtain a node priority; selecting a priority task node corresponding to the maximum node priority, and distributing the priority task node to a target idle processor for task processing based on a preset distribution condition; and carrying out delayed attribute updating operation on the priority task node to obtain an updated task node. The technical problem that the overall calculation efficiency is low due to the fact that efficient scheduling of high-delay tasks cannot be achieved and processing of complex tasks is difficult to adapt in the prior art can be solved.

The UE is configured to receive a set of repetitions of a downlink message from a base station, and attempt to decode a DL message after receiving one or more of the repetitions. If the decoding is successful, the UE transmits an uplink message (e.g., HARQ-ACK) indicating successful decoding. If the decoding is not successful, the UE does not transmit an uplink message indicating that the decoding is not successful. If the set is not complete, the UE receives one or more additional repetitions and attempts again to decode the DL message. If the base station receives a UL message indicating successful decoding before transmitting all repetitions in the set, the base station stops transmitting the repetitions. For half-duplex UEs that disable HARQ feedback processing, upon successful decoding, the UE switches from a downlink mode to an uplink mode to send uplink messages, thereby avoiding processing subsequently received repetitions for the same downlink messages.

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.

This invention discloses a self-service printing device, comprising a housing with an observation window and a temporary storage mechanism and a release mechanism located within the housing. The temporary storage mechanism consists of multiple parallel and inclined support units arranged sequentially along the normal direction of the observation window; the front support unit and its paper obscure the content area of ​​the rear paper, with only the side serial number area exposed. Each support unit has a support plate, a holding member, and a conductive bead. The release mechanism has electrical contacts aligned with the conductive beads. When the contact is activated, it drives the corresponding holding member to switch from holding to releasing, allowing the target paper to slide out along the support plate. This structure achieves physical obscuring of the content area and visibility of the serial number during the temporary storage stage, supporting accurate single-page release; the side serial number is permanently exposed for easy identification and position mapping; the number of contacts is small, the wiring is simple, and the paper is fed by gravity, reducing the risk of missorting and jamming, improving confidentiality, efficiency, and reliability; the structure is modular and easy to maintain.

The invention discloses a production scheduling intelligent optimization method for a flow industry enterprise production process, and relates to the technical field of production scheduling intelligent optimization, and the method comprises order data analysis, production data collection, production quantity analysis, employee production scheduling, raw material use data collection, use data analysis, and raw material use blending. The method comprises the following steps: analyzing production data of each workshop section, dividing each production workshop section into a transfer-away production workshop section, a transfer-in production workshop section and a non-scheduling production workshop section, scheduling employees according to the production data of the employees of each production workshop section, and dividing each workshop section into a transfer-away processing workshop section, a transfer-in processing workshop section and a non-scheduling processing workshop section according to the production data of each workshop section; through production scheduling, the production efficiency of the whole production process can be improved, and the loss caused by local problems in the production process is reduced.

The embodiment of the invention discloses a task scheduling method and device based on an electronic map, electronic equipment and a storage medium. The method comprises the steps that a frame selection area on the electronic map is acquired, and intelligent inspection equipment in the frame selection area is acquired; if a plurality of intelligent inspection devices are included in the frame selection area, selecting and acquiring a scheduling function supported by each intelligent inspection device in the plurality of intelligent inspection devices; according to the scheduling function supported by each intelligent inspection device in the plurality of intelligent inspection devices, displaying a to-be-called function, the to-be-called function including but not limited to cluster voice, video passing and message issuing; obtaining a selection instruction for the to-be-called function and input target information; and based on the selection instruction of the to-be-called function, sending the target information to the plurality of intelligent inspection devices, so that the information of the intelligent inspection devices can be displayed in real time by integrating an electronic map, and the intelligent inspection devices can be quickly scheduled on the electronic map.

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 application relates to the technical field of power optimization and dispatching, and in particular to a flexible control method, system, and power router for a power router. The method includes: when the power router is in operation, real-time acquisition of operating status data; calculation based on the operating status data using a preset flexible dispatching algorithm to obtain a dispatching decision result; adjustment of the power allocation and exchange boundaries between the power router's energy ports based on the dispatching decision result to obtain a flexible operating range; determination of the current operating mode based on the flexible operating range; and control of the power router to execute energy management actions corresponding to the current operating mode based on the current operating mode and operating status data. By constructing a flexible operating range, the system's adaptability and operational stability under varying operating conditions are improved, achieving rapid response in the time dimension and multi-port coordination in the spatial dimension for energy dispatching, comprehensively enhancing the operating efficiency and control accuracy of the power router.

The application relates to the technical field of construction safety management, and discloses a power engineering construction safety management system, which comprises a real-time risk assessment scheduling unit, a forward-looking human factor risk perception unit and a risk simulation mapping unit. The real-time risk assessment scheduling unit is used for generating a safety state characteristic map based on heterogeneous safety data of a construction site, identifying a risk event of the construction site through the safety state characteristic map, and generating an intervention instruction and a resource scheduling scheme to optimize the construction site. The application can comprehensively capture multi-dimensional information of the construction site by collecting personnel biological characteristics, equipment operation logs, environmental indexes and work video streams and other heterogeneous safety data through a multi-modal perception unit, breaks the limitation of single and one-sided data collection in the traditional management mode, and enables management personnel to obtain more rich and comprehensive on-site safety information, so that the overall safety condition of the construction site can be more clearly understood.

The utility model belongs to the field of hoisting devices, and provides an adjustable suspended ceiling hoisting device which comprises an I-shaped steel beam, a reinforcing assembly is arranged on the upper side of the I-shaped steel beam, a hoisting assembly is arranged at the lower end of the I-shaped steel beam, and an operator sends an instruction through a wireless remote controller and drives a servo motor to drive a walking vehicle to move along a track until materials are stacked. In the moving process, an embedding plate arranged at the upper end of the walking vehicle is embedded in an embedding groove, under the limiting effect that a limiting plate is embedded in a limiting groove, through double protection of an infrared obstacle avoidance sensor and an anti-falling net, the high-altitude operation risk is reduced, the requirements of different building spaces are met, the flexibility is adjusted, the requirements of diversified scenes are met, and it is guaranteed that the problem of tall and large spaces is solved; and compared with traditional single-point fixing, adjustment incapability and the like, the adjustable ceiling fixing device has the advantages of being convenient to install and high in adaptability.

The utility model discloses an auxiliary device for AGV intersection dispatching, which comprises a storage ground, a cross-shaped intersection is arranged on the upper surface of the storage ground, a first AGV is arranged on the upper surface of the left end of the storage ground, and a second AGV is arranged on the upper surface of the rear end of the storage ground; scheduling assemblies are arranged on the two sides of the crossing and used for detecting and controlling starting and stopping of the first AGV and the second AGV; according to the dust removal device, the protection component is arranged, firstly, the sucking pump is controlled to be started, the dust removal pipe can be driven to convey scraped dust into the sucking pump when the sucking pump is started, then the dust removal pipe conveys the collected dust into the collection box, and the filter screen arranged on the collection box can isolate and collect the collected dust; according to the AGV scheduling device, the secondary pollution of dust is avoided, the working environment of the AGV is improved to a great extent, and meanwhile, the accuracy of the AGV driving route can be improved through dust cleaning, so that the scheduling device can be well assisted.

The invention discloses a mixed request-oriented large language model adaptive scheduling algorithm. The algorithm comprises the following steps: S1, initializing queues Q1, Q2 and Q3 and a set CB to be empty; s2, when a new request arrives, calculating the priority of the new request, adding Q1 or Q2 according to the type of the new request, and then entering S3; when no new request arrives, entering S3; s3, judging whether the request is true or not, if so, entering S4, otherwise, terminating the algorithm, and starting when a new request exists; s4, updating the priorities of the requests in the queues Q1, Q2 and Q3; s5, the updated Q1, Q2 and Q3 are traversed in sequence, and the request is selected to be added into the CB; s6, inputting the CB into the large language model for reasoning for one time, removing the completed request from the CB, and recording the completion time; s7, when the CB is empty, entering the step S2; when the CB is not empty, k is made to be equal to k + 1, and when k is smaller than Y-1, the step S6 is executed, and otherwise, the step S8 is executed; and S8, for uncompleted requests in the CB, the request from the Q1 is put back to the Q1, the requests from the Q2 and the Q3 are both put back to the Q3, and then the step S2 is returned.

The invention discloses a saline-alkali soil precision desalination device, which relates to the field of soil technology. The upper front side of the desalination box is fixedly connected to the lower end of the pH detection box, and a quantity control chute is provided on the upper front side of the desalination box. The inner wall of the quantity control chute is slidably connected to the outer wall of one end of the quantity control frame, and the right side of the desalination box is fixedly connected to the lower end of the desalination box. The advantages of the invention are: for different soil conditions, the pH value of the saline-alkali soil can be quickly detected by the pH detection box, and the weight information support of the desalination block placed by the user is provided by using the quantity scale according to the corresponding relationship between the soil pH value and the soil salinity and alkali content, and the position of the quantity control plate and the quantity limit plate is controlled by the quantity control frame to adjust the weight of the placed desalination block, so that the device can be placed according to the actual demand. The corresponding number of desalination blocks is placed for precise desalination. Compared with the existing desalination equipment on the market, it can reduce the waste of desalination blocks and improve the utilization rate of desalination blocks.

The application discloses a routing and scheduling based time sensitive network topology design method, and relates to the field of industrial networks.The application carries out mathematical modeling on a TSN topology-routing-scheduling joint problem, designs an optimization target, and solves the optimization target of the TSN topology-routing-scheduling joint problem based on schedulability analysis.The application can not only effectively reduce the number of switches and cables, but also significantly reduce deployment cost and maintenance cost;by simplifying the modeling of the scheduling part and converting complex nonlinear constraints into linear / quadratic modeling, the TSN routing and scheduling problem can be directly input into a commercial solver for efficient solving;the TSN network can be quickly deployed, real-time requirements of an industrial site are met, and the TSN network is adapted to rapid changes of a flexible production environment.

The present application relates to the field of data processing, specifically to an aviation bus data processing method based on time pyramid, which comprises the following steps: S1, cleaning and checking the data; S2, dividing the complex table structure according to columns; S3, constructing data combination of time column and data column; S4, constructing the bottom layer basic tile data of time pyramid data; S5, extracting the basic data to be processed in the form of frequency reduction by half each time to form multi-level frequency-decreasing extracted data, and the data forms multi-level LOD data; S6, processing the data in each level of LOD data according to the time block processing method of each level of tile construction; S7, serializing the tile data to the database to form hierarchical tile pyramid data. The present application realizes the tile segmentation of the aircraft bus data, and then processes the huge and complex bus data tiles, which can achieve the purpose of on-demand calling and on-demand taking in use.

The utility model discloses a management and control network platform for a threshing and redrying production line. The management and control network platform comprises a production control unit, a production information unit, an engineer station, a workshop core unit, a server group, an operation and maintenance management unit and a video display management and control system, the production control unit comprises a first field access layer and a first central control room convergence layer, and the first field access layer is in communication connection with the first central control room convergence layer; the production information unit comprises a second field access layer and a second central control room convergence layer; the second field access layer is in communication connection with the second central control room convergence layer; the engineer station is in communication connection with the first central control room convergence layer and the second central control room convergence layer; the operation and maintenance management unit is in communication connection with the second central control room convergence layer; the workshop core unit comprises a first core switch, and the first core switch is in communication connection with the first central control room convergence layer, the second central control room convergence layer, the server group and the video display management and control system. And comprehensive presentation and rapid scheduling of production operation and operation data are realized.

The application provides a vehicle rescue management method and system based on a cloud platform and edge computing, and relates to the field of data processing.The method comprises the following steps: determining a vehicle rescue service station setting scheme and an edge computing configuration scheme of a target area according to historical vehicle rescue data of the target area, setting multiple vehicle rescue service stations in the target area, and setting multiple edge computing stations in the target area; determining a vehicle rescue resource dynamic scheduling scheme and an edge computing dynamic scheduling scheme according to real-time road information of the target area through a cloud platform; scheduling the multiple edge computing stations to determine vehicle rescue demand of the target area according to the real-time road information of the target area based on the edge computing dynamic scheduling scheme; receiving vehicle rescue requests through the multiple edge computing stations; and performing vehicle rescue through the multiple edge computing stations according to the vehicle rescue demand and the vehicle rescue requests of the target area, so that the vehicle rescue efficiency and quality are improved.

The present invention discloses a fire prediction method for fusing multi-source time series data suitable for edge computing, including collecting multi-view RGB images, multi-view infrared images and meteorological data, and preprocessing the data; constructing a Smokey Net prediction model with CNN as the backbone network, inputting the preprocessed data into the prediction model, and performing multi-source data fusion; selecting three attention mechanisms: sparse attention mechanism, strong attention mechanism and multi-head attention mechanism; adding an external register module and a long short-term memory network; and training the Smokey Net prediction model. The present invention solves the problem of insufficient sample data when predicting wild fires, and improves the accuracy of long-term monitoring. Thereby helping to reduce casualties and property losses caused by fires, and improving the efficiency and timeliness of responding to fires.

The invention discloses an improved three-way decision-making-based computing network task scheduling method and a related device, and relates to the technical field of computing power resources and computing network task scheduling, and the method comprises the following steps: obtaining computing network task scheduling data; classifying calculation network indexes according to the calculation network task scheduling data, and constructing a calculation network index system; based on the calculation network index system, dividing each platform and each task by adopting a three-way decision theory to obtain a platform division result and a task division result; and according to the platform division result and the task division result, matching a corresponding task for each platform to obtain a preliminary calculation network task scheduling result, and according to the load factor and the matching degree of each platform, optimizing the preliminary calculation network task scheduling result to obtain a final calculation network task scheduling result. The computing network resource utilization rate and the task scheduling efficiency can be improved.