81results about How to "Speed up dispatch" patented technology

The invention discloses a public bicycle renting forecasting method based on multi-source data fusion. According to the method, historical data about public bicycle renting / returning records, weather, temperature, holidays, festivals and the like are cleaned and preprocessed, and training datasets are acquired; the datasets are classified with a clustering algorithm, and different renting modes of public bicycles are divided; the classified datasets are used to establish a Bayesian classifier used for forecasting the renting modes according to conditions of holidays, festivals, weather and air temperature of one day in the future; a self-adaptive particle swarm neural network model corresponding to each mode is trained for different modes of datasets respectively; finally, the renting mode of one day is forecasted by the aid of the Bayesian classifier, a corresponding particle swarm neural network model is selected to forecast the renting law of public bicycles. The forecasting accuracy is high, the operation speed is high, reference basis is provided for bicycle renting and returning by a user, the duration time of the unbalanced state of a public bicycle station is shortened, and the users' satisfaction is improved.

The invention discloses a coordination control method and relates to the technical field of control of power systems. The coordination control method comprises the following steps: S1. measuring real-time voltage, current, active power and reactive power of all bus bar nodes, and setting an AGC (automatic gain control) command; S2. performing voltage check according to the AGC command, and outputting voltage predicted value and check result of the selected bus bar node; S3. outputting the AGC command if the AGC command meets the voltage requirement, otherwise, implementing the step S4; S4. performing AVC (automatic voltage control) according to the voltage predicted value of the selected bus bar node, and calculating voltage adjusting value of the selected bus bar node after performing the AVC; S5. performing power check according to the voltage adjusting value of the selected bus bar node, and outputting power predicted value and the check result of a call wire; and S6. outputting anAVC command if the AVC command meets the power requirement, otherwise, resetting the AGC command, and returning to implement the step S2. By adopting the method, active power flow and reactive power flow of the power system can be well controlled, and economy and safety of operation of the power system can be improved.

The invention belongs to the technical field of event injection of a computer system, in particular to a task scheduling method of an event injection engine based on a multilevel feedback queue. The method includes the steps that a scanner scans a target system according to user commands or system control signals, and a scanning result comprising all vulnerability types of the target system is returned; the scanning result is analyzed according to all vulnerabilities or user requirements, and types of batch events needing injecting are determined; the scanner sends information needing injecting of the types of the batch events to an event model library; the event model library receives the information, of the types of the batch events, sent by the scanner, and corresponding events are selected according to the types of the batch events. The method has the advantages that the application range is wide, feedback cost is small, compatibility is good, the utilization rate of the event injection engine is high, and batch event injection is more flexibly, efficiently and reasonably achieved.

The invention provides a uplink resource allocation method, including: user terminal reports sum of data to be transmitted in the logical channel buffer with the same highest priority; base station allocates uplink resource based on sum of received data. Meanwhile, the invention also provides a uplink resource allocation system, including: user terminal, for reporting sum of data to be transmitted in the logical channel buffer with the same highest priority; base station, for allocating uplink resource according to sum of received data. Further, the invention also provides a user terminal. The invention makes uplink resource allocated reasonably between each user terminals, and realizes better load balance between each user terminals, improves user's satisfaction.

The invention discloses a visualized big data workflow configuration method and system based on the WEB. Workflow configuration is achieved through a browser by the drag method and an wizard interface, the development efficiency is improved, and the personnel cost is reduced. Meanwhile, complete MapReduce / Hive / Spark support is provided, the current mainstream big-data processing programs refer toHiveSQL, MapReduce, Spark and SparkSQL, and the method attempts to provide thorough support to the big-data processing programs. Moreover, according to the scheme, the running speed can be improved, an lightweight distributed workflow engine is achieved, the scheduling speed and running speed of the distributed programs are improved, and performance of the system is improved.

The invention discloses a wind power prediction correction method. The method includes the steps that 1, the total capacity of a selected wind power plant is obtained, and wind power prediction data and wind power actual measurement data of the whole field in a recent civil year of the wind power plant are obtained; 2, normalization processing is carried out on the wind power data, obtained from the step1, of the wind power plant by means of the total capacity of the wind power plant; 3, an input and output data set is formed according to the wind power prediction data and the wind power actual measurement data obtained after preprocessing in the step 2; 4, 2 / 3 of the input and output data set obtained in the step 3 is selected randomly to serve as a training set, and the remaining 1 / 3 serves as a testing set; 5, a kernel function and training parameters of the support vector machine are selected, training is carried out by means of the training set obtained from the step 4, and the testing set is used for testing; 6, a grid searching method is utilized to correct the parameters of the support vector machine, and an average absolute percentage error and a root-mean-square relative error of a correction result are utilized to serve as evaluation criteria to obtain a local optimum support vector machine training model, namely a local optimum wind power prediction correction model.

The invention relates to the technical field of power grids, particularly relates to a thunderstorm early warning system and method. The system comprises a thunderstorm short-term and temporary forecasting module, a thunderstorm potential forecasting module, a thunderstorm real-time monitoring module, a user management module and a thunderstorm forecasting and early warning visualization module. Refined forecasting product data are provided based on short-term and temporary forecasting and potential forecasting of power grid thunderstorm forecasting data, and are accessed to a deployed serverthrough an API (Application Program Interface) to transmit a forecasting result in real time, and the forecasting result is displayed through a forecasting and early warning visualization system platform based on a Web GIS (Geographic Information System) technology. The thunderstorm forecasting and early warning project system can be divided into a data source layer, an original data layer, a datastorage layer, a calculation layer and an application service layer as a whole. According to the method, the influence of lightning activity on the power transmission line can be effectively discovered in advance, the scheduling and emergency plan making management level is improved, a good foundation is laid for safe, stable, high-quality and economic operation of a power grid, and the safety and benefit society is remarkable.

The invention discloses a vehicle-mounted monitoring system comprising an RF (Radio Frequency) data acquisition terminal, a vehicle-mounted information controller and a background monitoring center, wherein the RF data acquisition terminal acquires vehicle-mounted temperature and humidity and the vehicle-mounted information of a mechanical and electronic lock through a sensor and then carries out communication through a first RF module and a second RF module; a GPS (Global Position System) module is used for receiving vehicle position information through a GPS satellite signal; a main processor is used for the vehicle-mounted information received by the second RF module and the vehicle position information received by the GPS module; the vehicle-mounted information and the vehicle position information after being processed by the main process are sent to the background monitoring center through a GPRS (General Packet Radio Service) module through a GPRS network; and the background monitoring center displays the vehicle-mounted information and the vehicle position information. The invention can carry out real time monitoring, management and dispatching on the vehicle at any time, reduce the cost of logistics industry and play an active role in reducing the proportion of the logistics cost in GDP (Gross Domestic Product).

The invention discloses an industry water supplying quantity determining method with the water supplying priority level taken into consideration in water resource allocation. The industry water supplying quantity is determined according to the industry water supplying priority level in the future water resource allocation of appointed areas, an industry water supplying priority level three-layer structure is established through a wetted perimeter method, a line outer-wrapping method, a water balance method, an SOR method and various survey data. The water supplying quantity calculation of various water supplying industries is scientifically and effectively achieved according to the different water level limitation of water users of the water supplying industries and the different water supplying priority levels. According to the industry water supplying quantity determining method, the water supplying priority level of ecological water level control is introduced, the different water level limitation and the different water supplying priority levels of the water users in life, industries, ship locks, ecology, agriculture and the like, the water supplying quantities are independently determined, the increase of the utilization rate of the water resources is promoted, the water ecology is protected, and water resource management and allocation are more scientific and effective.

The invention discloses a wireless packet remote monitoring system for a city road light-emitting diode (LED) lamp. The system mainly comprises a monitoring center, a remote monitoring terminal, remote terminal equipment and a street lamp; the monitoring center communicates with the remote monitoring terminal through a transmission network; and the remote monitoring terminal is in communication connection with multiple pieces of remote terminal equipment arranged on the street lamp. Because micro control unit (MCU) and system on chip (SOC) technologies are integrated to form an intelligent module with an adaptive control algorithm in the remote terminal equipment, and a series of LED lamp constant current modules driving different voltages and powers can be formed through electrically erasable programmable read only memory (EEPROM) digital write-in, the invention has the advantages that: information is exchanged timely and accurately, intelligent monitoring is realized and scheduling and management degree is high.

The invention relates to a flight gate position conflict solution based on preference ordering, and the method comprises three steps: configuration, allocation data preparation and position dynamic adjustment. The above solution can achieve the selection of the optimal gate position through the preference cores so that airplanes with the gate position conflicts can dock. The solution is accurate in information, is short in processing time, can quickly avoid the conflict between the gate positions, reduces the work intensity of a worker, and improves the airport safeguard efficiency.

Embodiments of the invention provide a host machine resource distribution method and device and a host machine scheduling method and device. The host machine resource distribution method comprises thefollowing steps of: firstly obtaining a first available resource amount of each host machine at the current moment by a server; calculating a second available resource amount of each host machine group and an available resource gross of the host machine groups according to the first available resource amount; calculating an average value of available resource amounts of all the host machine groups according to the quantity of the host machine groups and the available resource gross; respectively calculating a difference value between the second available resource amount of each host machine group and the average value; and finally adjusting the quantity of host machines in the host machine groups, the difference values of which satisfy a preset condition, according to the average value. By applying the scheme provided by the invention, the dynamic and balanced distribution of available resources of the whole host machine group can be ensured, so that the host machine scheduling time consumption is decreased and the host machine scheduling process is accelerated.

The present invention relates to a grid power generation adjustment method. Through setting the target of power generation adjustment, the power generation amount reallocation is carried out through renewable energy generator unit and thermal power generator unit constraint conditions, and after the clean energy of renewable energy generators is fully utilized to generate power, the power generation amount allocation of thermal power generators is adjusted. For a generator unit with large energy consumption, the transfer of a power generation right is carried out, a generator unit with few power generation is compensated, thus the power generation configuration is optimized, the efficiency and scheduling of power system power generation is improved, the clean energy is used with a priority, and the pollution of a power system generation link is reduced.

The embodiment of the invention discloses a memory scheduling method. The memory scheduling method is used for simplifying memory division and improving the scheduling efficiency. The method provided by the embodiment of the invention comprises the following steps: dividing a memory into a plurality of memory blocks according to a pre-set rule, wherein the size of each memory block is a fixed value; when receiving a target task request, determining a plurality of sub-requirements corresponding to the target task request, wherein the size of each sub-requirement is smaller than the size of the memory block with the maximum capacity in the plurality of memory blocks; establishing a mapping relation of the plurality of sub-requirements and the plurality of memory blocks; and according to the mapping relation of the plurality of sub-requirements and the plurality of memory blocks, applying for a corresponding memory block set corresponding to the target task request from a memory management module. The embodiment of the invention also provides a scheduling device which is used for simplifying the memory division and improving the scheduling efficiency.

An MRI apparatus consolidates and stores maintenance and / or performance data automatically measured by a measurement unit and data manually input via an input device. The automatically measured data may include an adjustment value, a state value or an error record. The manually input data may include a software and / or hardware upgrade record, a customized situation record, a network connection record, a repair record, a check record, a maintenance record or an installation record, for example. Both types of data can be obtained swiftly and faults or malfunctions can be recovered from quickly or even prevented in advance. The stored data may be communicated among a plurality of MRI apparatuses, a service center apparatus and a maintenance support apparatus via a communications network.

The invention discloses a big data-based optimization method of a ground public-transportation fixed-line timetable. First, all collinear public-transportation lines are extracted for target lines, which need to be studied, according to GPS trajectory data, IC card swiping data of the collinear public-transportation lines and number data of vehicles arriving at each station in unit time are extracted, and vehicle running time data are extracted; then all the extracted data are analyzed and processed; passenger preference coefficients are calculated on the basis of passenger flow data, full-dayworking time periods of the public-transportation lines, maximum passenger capacity of the public-transportation service vehicles, standard full-load rates, first / last-vehicle departure time, and maximum and minimum vehicle departure intervals are determined; and then the processed data are input into a constructed multi-objective optimization model to obtain an optimized public-transportation vehicle departure timetable. The optimization method of the ground public-transportation fixed-line timetable provided by the invention can satisfy passenger flow demand, enhance public-transportation operation efficiency, reduce public-transportation travel delay, improve service reliability, and improve passenger satisfaction degrees.

The invention discloses a Hadoop Yarn (Yet another Resource Negotiator) network bandwidth resource scheduling and isolating method and device. The scheduling method is performed at an RM (Resource Manager) side and comprises the steps of receiving work resource requests sent by an AM (Application Master), wherein the work resource requests comprise network bandwidth resource demand quantity of each task in work; and correspondingly allocating a container to each task through adoption of a preset fair scheduling algorithm according to the network bandwidth resource demand quantity of each task, wherein the network bandwidth resource demand quantity of the corresponding task is packaged in each container. The isolating method is performed at an NM (Node Manager) side and comprises the steps of obtaining a plurality of containers from the Am, wherein the network bandwidth resource demand quantity of the corresponding task is packaged in each container; and isolating a network bandwidth resource occupied by each task according to the network bandwidth resource demand quantity of each task. According to the methods and the devices, the scheduling for the network bandwidth resources is increased in a Yarn cluster, so the mutual interference among the tasks resulting from competition for the network bandwidth resources can be avoided.

The implementation mode of the invention provides a method and a device for medical guidance of physical examination. The method comprises the following steps of acquiring time buckets and physical examination items for processing: acquiring the history examination number of persons for physical examination items during the time bucket; calculating an average value of the history examination number of persons for the physical examination items during the time bucket according to the history examination number of persons; acquiring the estimated number of persons participating in the physical examination items during the time bucket according to the reservation number of the persons participating in the physical examination items; summing the average value of the history examination number of persons and the estimated physical examination number of persons and marking the summing result as lambda; acquiring the physical examination time of each object to be examined for the physical examination items during the time bucket, calculating the average service time for the physical examination items according to the history examination number of persons, and marking a reciprocal of the average service time as mu; when processing resources for processing data of objects to be examined are allocated for the physical examination items corresponding to the time bucket, enabling the processing resources not to be smaller than a quotient value of the lambda and the mu; performing medical guidance on a medical guidance request of the objects to be examined according to the allocated processing resources. According to the implementation mode of the invention, the medical guidance efficiency can be improved.

The invention discloses a coordinative optimization control method based on AGC and AVC. The method includes: selecting a power grid area controlled by AGC and AVC in a coordinative manner, setting power grid basic parameters, and initiating various particle parameters to produce an initial swarm; selecting a control target and constraint conditions, calculating the tidal currents of the selected power grid area, and determining the new positions and speed information of particles; introducing inertia weight and contraction factors to improve an initial particle swarm algorithm, performing particle swarm optimization calculation on the particles in the second step to obtain the optimized swarm; performing hybrid mutation on the optimized particles obtained in the third step, updating the new particles, and calculating the fitness function values of the particles before and after the mutation; performing simulated annealing attenuation on the particles obtained in the fourth step, and performing a new round of tidal current calculation; judging convergence conditions, and outputting optimization control results. The method has the advantages that the problems of AGC and AVC coordinative optimization control are solved, system tidal currents are optimized, and power grid frequency and voltage quality are improved.

The invention discloses a GPU resource management and intelligent scheduling method for deep learning, and the method comprises the following steps: 1, enabling a user to submit deep learning jobs through a front-end interface module, wherein the deep learning jobs comprise a to-be-executed deep learning program and a training data set; 2, after verification, adding the job to a queue to be scheduled corresponding to the scheduler; 3, starting an independent job manager for the job; 4, applying for computing resources required by job operation from a resource manager; 5, carrying out feature modeling and analysis on the to-be-scheduled job; 6, generating a resource scheduling scheme according to the operation characteristics and the cluster computing node characteristics; 7, scheduling thejob to a specified computing node according to a scheduling scheme; 8, enabling the job executor to start the container and execute a deep learning program. According to the method, the problems of low GPU resource utilization rate and poor job execution performance of an existing cluster resource scheduling method in a deep learning scene can be solved.

The invention provides a service information generation method and device, computer equipment and a storage medium, and the method comprises the steps of obtaining the current bubbling record information of a user side before a service request is transmitted, and the historical travel information of the user side; inputting the current bubbling record information and the historical travel information of the user side into a pre-trained order sending prediction model to obtain an order sending probability of the user side in a future preset duration; and generating service information corresponding to the service request based on the order sending probability of the user side in the future preset duration. And the generated service information can be used for providing further service content for the user, so that related resources can be scheduled in a targeted manner, and the resource scheduling timeliness rate and the resource utilization rate are improved.

The invention discloses a multilayer forest fire prevention center. The multilayer forest fire prevention center comprises an alarm, multiple bottom-layer monitoring centers, a remote monitoring system, a top-layer monitoring center and multiple intermediate-layer monitoring centers, wherein the top-layer monitoring center is provided with a top-layer alarm server, a cascade server and a top-layer network switch cabinet which are successively interconnected; the intermediate-layer monitoring centers comprise intermediate-layer alarm servers and intermediate-layer network switches; the intermediate-layer alarm servers are connected with the intermediate-layer network switches; the intermediate-layer network switches are interconnected with the top-layer network switch cabinet; the bottom-layer monitoring centers comprise video control servers, bottom-layer alarm servers and bottom-layer network switches; the remote monitoring system is connected with the bottom-layer network switches through a network; the bottom-layer network switches, the video control servers and the bottom-layer alarm servers are successively interconnected; the alarm is connected with the bottom-layer alarm servers; and the bottom-layer network switches are in redundancy connection with the intermediate-layer network switches. The multilayer forest fire prevention center has the advantages of scientific decision-making, high response capability and high operation efficiency.

The embodiment of the invention provides an IO request scheduling method and device. The method comprises: obtaining a to-be-scheduled target IO request, and determining whether the target IO request belongs to a current-limited IO request or not; when the target IO request belongs to the first type of IO requests which are not subjected to current limiting, determining the current moment as the scheduling moment of the target IO request; when the target IO request belongs to a current-limited second type IO request, determining a scheduling moment of the target IO request according to a current current-limiting resource proportion, wherein the current current-limiting resource proportion is a resource proportion used for processing the second type IO request in a current time period to which the current moment belongs, and obtaining the current current-limiting resource proportion through calculation according to a previous current-limiting resource proportion of a previous time period and load information of a first type of IO requests scheduled in the previous time period, wherein the scheduling moment is not less than the current moment; and adding the target IO request into an IO request set, and sequentially sending a plurality of IO requests in the IO request set to a disk for processing according to the scheduling time from small to large.

The invention provides a wireless resource scheduling method and architecture system based on low-orbit constellation satellite communication, and the method comprises the steps: dividing the wirelessresource scheduling of a low-orbit constellation satellite communication system into three data processing architecture systems according to the factors affecting a business data access system, wherein the system comprises a first-stage wireless resource scheduling center, a second-stage satellite resource scheduling module and a third-stage user service scheduling module. The wireless resource scheduling center carries out satellite service area and resource planning according to global frequency spectrum, resources, services and other data, satellites carry out resource scheduling for terminal users according to planning data, and the user service scheduling module handles priority adaptation of different service data. Low-orbit constellation satellite communication system network access of multi-service data is realized. Resource scheduling is decoupled through a layered low-orbit constellation satellite communication system resource system architecture, and wireless resource scheduling of the low-orbit constellation satellite communication system is optimized through processing and analysis of related data.

A method of scheduling transmission of data in a wireless communication network comprising: establishing a data channel for transmitting user data from a user equipment to a network entity, establishing a signalling channel for transmitting signalling data from a user equipment to a network entity, transmitting over said signalling channel from the user equipment a first rate request message requesting additional resources from the network for transmission of data at an increased data rate over said data channel, maintaining said signalling channel for a period awaiting a rate grant message, and transmitting a second rate request message over said signalling channel during said period.

The embodiment of the invention discloses a multi-level scheduling method and device, a network chip and a storage medium. The method is applied to a network chip, the network chip comprises at leasttwo dispatchers of different levels, each dispatcher of different levels corresponds to at least one node used for data transmission, and the method comprises the steps of obtaining a dequeue dispatching request, and analyzing the number of the node of the level from the dequeue dispatching request; According to the dequeue scheduling request or the serial number of the node of the current level,determining the serial number of the node of the upper level and the priority serial number of the node of the upper level; Determining enqueue information needing to be scheduled from a preset firstmemory according to the number of the node of the current level; And according to the enqueue information needing to be scheduled, the number of the upper-level node and the priority number of the upper-level node, generating dequeue information.

The invention discloses a network resource reservation method, a PCE and and SDN network system, and relates to the field of communication. The method comprises the steps as follows: the PCE computesa forwarding path of service data based on a flow scheduling strategy; the PCE issues resource reservation information to a routing node through which the forwarding path passes, wherein the resourcereservation information comprises label information of the service data and the bandwidth reservation information corresponding to the label information; and the routing node sets reservation resources for the forwarding of the service data according to the resource reservation information. According to the method, the PCE and the SDN network provided by the invention, on the basis of overall optimized path computing, the bandwidth of the link passing through the node is reserved in advance, the frequent repeated computation of the PCE caused by the variation of the subsequent flow is reduced,and the SDN controller performance is enhanced; expansion is performed based on the existing PCEP protocol, so as to be easy to implement; concentrated flow scheduling under the complex network environment can be achieved, and the flow scheduling and optimized capacity of the operator in the network can be enhanced.

The invention relates to a power grid dispatching method and system applied to the technical field of power dispatching, and the method comprises: obtaining dispatching basic data which comprises spotmarket dispatching basic data and frequency modulation auxiliary service market dispatching basic data; verifying the scheduling basic data; and if the verification is passed, inputting the verifiedscheduling basic data into a preset scheduling plan model to obtain scheduling plan compilation schemes, the scheduling plan compilation schemes including a multi-day rolling power generation scheduling plan scheme and a day-ahead scheduling plan scheme. Thus, the scheduling technical support can adapt to the spot market in real time, and the technical problem that in the prior art, along with continuous updating of the spot market, frequency modulation and other information, an existing system cannot meet the increasing requirements is solved.

The invention provides a media access control safety protocol message transmission method and a related device. The method comprises the following steps: a first network device identifies a first priority of an original message and sets a priority field in a media access safety protocol (MACSEC) message corresponding to the original message, the original message comprises a plurality of types of data, and each type of data corresponds to a respective priority; and the first network device sends the MACsec message to a second network device, so that the second network device performs mapping according to the priority field to obtain a mapped second priority, and schedules or forwards the MACsec message according to the second priority. By setting the priority field in the MACsec message, the intermediate device can identify the priority of the MACsec message in the transmission process, and it is ensured that important messages are scheduled with high priority and are not discarded.