16results about How to "Realize reasonable deployment" patented technology

The invention discloses an intelligent operation sewage pipeline system and an implementation method thereof, and the intelligent operation sewage pipeline system comprises monitoring equipment, a cloud server, a GIS map model, a management platform and an operation management terminal which achieve data interaction through a 5G data network or the Internet. And the data is processed and analyzed by combining big data analysis, an intelligent algorithm and an image algorithm, so that prompting, decision making, renovation and evaluation of the defects of the sewage pipeline are realized. The specific implementation method comprises the steps of constructing the intelligent operation sewage pipeline system, arranging monitoring equipment, establishing a GIS map model, setting a management module, constructing functions of each module and the like. Effective scheduling of the sewage pipeline operation system and reasonable allocation of operation and maintenance resources are realized, and the efficiency and quality of sewage pipeline operation are improved. The problems of external water entry, sewage leakage, sewage overflow, road collapse and the like caused by sewage pipeline defects are solved.

The invention provides a power distribution network power flow regression method and device based on SVR data driving, and relates to the technical field of power distribution network analysis, and the method comprises the steps: obtaining target input information containing the state information of each node of a power distribution network; the nodes of the power distribution network comprise at least one of PV nodes and PQ nodes; the state information of the PV node comprises active power and voltage amplitude; the state information of the PQ node comprises active power and reactive power; inputting the target input information into the power flow regression model to obtain a target output result; the model is constructed based on a support vector regression (SVR) model; the objective function of the model is obtained based on a second mapping relation between the known quantity and the unknown quantity. According to the power distribution network power flow regression method and device based on SVR data driving provided by the invention, the high-accuracy power flow solution is calculated through the power distribution network power flow regression model based on SVR data driving, and then reasonable allocation of the power distribution network is realized.

The invention discloses a priority-driven hybrid shared parking and charging resource optimization method, and aims to solve the problems of unreasonable resource allocation, unbalanced supply and demand of parking spaces and low utilization rate of charging parking spaces of an existing shared parking lot. The method comprises the following steps: firstly, constructing a priority matching mechanism of multiple types of parking spaces and parking demands, setting priorities according to parking demand types and parking space attributes, and preferentially meeting the matching of mixed demands and charging parking spaces; secondly, parking space and demand data of a parking lot are collected, an optimization model with operation profit maximization as a target is constructed, and target functions comprise profit, cost and penalty cost; the timeliness and rationality of supply and demand matching are ensured by introducing the time window constraint of the parking demand and the shared parking space supply; and establishing a constraint relationship between demand and supply, and optimizing the resource allocation efficiency. The parking and charging resource utilization efficiency can be remarkably improved, the user experience is improved, the parking problem is relieved, and popularization of the shared parking policy is facilitated.

The invention discloses a rescue response situation analysis display method and system, a medium and a product, and relates to the field of situation display, and the method comprises the steps: obtaining real-time perception data and historical rescue data of a rescue area; determining obstacle information of the rescue area based on the unmanned aerial vehicle image data and the satellite image data; generating a dynamic environment situation of the rescue area according to the obstacle type, the obstacle position and the sensor data; determining a plurality of rescue path schemes based on the obstacle distribution change and the weather environment change; predicting a resource allocation scheme of each rescue path according to the rescue paths, the historical rescue path data and the historical resource allocation data; and associating the resource allocation scheme with the rescue path scheme, and performing visual display. By implementing the method, the rescue efficiency is improved.

The embodiment of the invention provides a model deployment scheme generation method and device, a model processing method and device and electronic equipment, and relates to the technical field of model deployment, large language models and the like. According to the specific implementation scheme, processor parameters of all processors in target equipment are obtained, wherein the target equipment is used for deploying a to-be-deployed model; based on the model information and the processor parameters, a deployment scheme is generated, the deployment scheme comprises first specified information, the to-be-deployed model comprises a plurality of processing layers, and the first specified information is used for specifying processors deployed by model weights of the processing layers. Based on the deployment scheme provided by the embodiment of the invention, reasonable deployment of processor resources in the target equipment can be realized, so that reasonable deployment of the model in the target equipment is realized.

The invention provides a highway emergency deployment and control management method and system, and relates to the technical field of highway management. According to the invention, the emergency task information is directly obtained from the task issuing center system, and diversified data sources are processed in real time, so that efficient task response is realized; meanwhile, intelligent prediction and evaluation are carried out by utilizing a pre-constructed event association prediction model and a pre-constructed department association model, so that the occurrence probability of an accident and the to-be-executed probability of a backup department can be accurately predicted; on the basis, by calculating the weight of the backup execution department and dividing the order waiting level, reasonable allocation of emergency resources is achieved, it is ensured that the key department can respond rapidly at the key moment, and the measures jointly ensure rapidness, accuracy and high efficiency of emergency processing.

This application discloses a method, system, electronic device, and storage medium for creating virtual machine instances, relating to the field of cloud computing technology. The method includes: receiving a resource scheduling request from a console, wherein the resource scheduling request requests a target scheduling system to prepare resources for a virtual machine instance to be created for a target scenario; preparing resources for the virtual machine instance based on the resource scheduling request; in response to the completion of resource preparation, obtaining target physical resources to be used by the virtual machine instance from a target physical resource pool, wherein the target physical resource pool is a shared physical resource pool used when creating different virtual machine instances for different application scenarios; and creating the virtual machine instance using the target physical resources. This application solves the technical problems of high creation cost and low resource utilization in related technologies when creating virtual machine instances.

The invention provides a computing power scheduling method and device and a readable storage medium, and relates to the technical field of communication, and the method comprises the steps that the computing power scheduling device receives a computing power request from a computing power demand end, the computing power request is used for requesting to select a computing power node for a service, and the computing power request comprises a first field, the first field is used for indicating an application scene for selecting the computing power node. The computing power scheduling device determines at least one computing power node in a computing power node set according to node selection parameters corresponding to the application scene, and the at least one computing power node is a computing power node supporting providing computing power service for the business. Wherein the node selection parameters comprise one or more of computing power node availability parameters, service end-to-end availability and end-to-end computing power demand parameters of the computing power demand end. The computing power service quality can be improved, and reasonable allocation of computing power resources is realized.

This application relates to an intent recognition method, computer device, computer-readable storage medium, and computer program product, which can be used in the field of computer technology. The method includes: when a user requests online customer service, obtaining the user's waybill status information, attribute information, and behavior logs; constructing the user's current features based on the waybill status information, attribute information, and behavior logs; selecting target historical features matching the current features from a historical feature database; inputting a preset reasoning case, target historical intent information corresponding to the target historical features, and the current features into an intent recognition model for intent recognition, obtaining the user's intent recognition result; the intent recognition result includes the predicted result of the user's inquiry question. This method can improve the efficiency of intent recognition.

A rescue response situation analysis and display method, system, medium and product, which relate to the field of situation display, and include: obtaining real-time perception data and historical rescue data of the rescue area; determining obstacle information of the rescue area based on drone image data and satellite image data; generating dynamic environmental situation of the rescue area according to obstacle type, obstacle location and sensor data; determining multiple rescue path plans based on obstacle distribution changes and weather environment changes; predicting resource allocation plans for each rescue path according to the rescue path, historical rescue path data and historical resource allocation data; associating resource allocation plans with rescue path plans for visual display. Implementing this method can improve rescue efficiency.

The invention discloses a matrix workshop scheduling method based on a genetic algorithm, and the method comprises the steps: S1, generating a related data case through a case generator according to the characteristics of a matrix workshop; s2, generating a chromosome through MSOSAS coding; s3, performing initialization setting on the population, and performing global selection, local selection and random selection according to a preset proportion to obtain a selected initial solution; s4, carrying out fitness calculation on the plurality of chromosomes; s5, according to the fitness and the crossover probability, selecting a preset number of populations to carry out machine crossover and process crossover; according to the fitness value and the mutation probability, selecting a preset number of populations to carry out machine mutation and process mutation, and generating an optimal chromosome; and S6, decoding the optimal chromosome, and generating the machine selection, the process sequence, the preset capability and the processing time of the workpiece during processing. According to the invention, the scheduling problem of the matrix type workshop is solved, and the production scheduling of the matrix type workshop with high flexibility and high adaptability is realized.

The present invention relates to the field of voltage control technology, and in particular to an automatic voltage control method based on active power trend determination. The method comprises the following steps: performing multi-scale monitoring data acquisition according to a power grid management system to generate multi-scale power matrix data; performing new energy output power prediction according to the multi-scale power matrix data to generate new energy power prediction data; performing spatiotemporal node similarity processing according to the multi-scale power matrix data, and performing node voltage change trend analysis to obtain node voltage trend data; performing power grid voltage stability margin assessment according to the new energy power prediction data and the node voltage trend data to generate voltage stability margin assessment data; performing intelligent voltage regulation instruction generation based on the voltage stability margin assessment data to obtain intelligent voltage regulation instruction data. The present invention realizes automatic control of power grid voltage through power grid voltage stability margin assessment, and effectively solves the voltage stability problem caused by new energy output fluctuations.

The application discloses a kind of power tower operation and inspection strategy making method based on real-time monitoring, it is related to power tower maintenance technical field, and its technical solution points include the following steps: collecting the historical deformation detection data of power tower, historical operation state data, historical environmental monitoring data and corresponding historical operation and inspection maintenance scheme and implementation effect data, establish the operation and inspection foundation database of power tower in severe cold area;Screening fault characteristics in operation and inspection foundation database, determine the correlation threshold of tower deformation, abnormal operation and environmental factors in severe cold area according to fault characteristics, establish the abnormal early warning threshold set of tower state;Based on multi-source monitoring terminal, obtain the real-time deformation data, real-time operation parameter and real-time environmental data of power tower in severe cold area, the effect is to realize the real-time perception of tower deformation, operation state and severe cold environment, greatly improve data integrity and availability, provide reliable basis for accurate state determination.

This invention provides a filter rod production scheduling method, electronic device, storage medium, and program product, relating to the field of cigarette production technology. The method includes: predicting the ending inventory of filter rods for each brand in the next production cycle based on the current production schedule; determining whether the ending inventory of each brand of filter rods can meet production demand; if so, using the current production schedule as the production schedule for the next production cycle; if not, designating the brand that cannot meet production demand as the target brand; obtaining the inventory increment of filter rods for other brands besides the target brand within a first preset cycle, and determining the target production equipment from the units corresponding to the filter rods of other brands based on the inventory increment; updating the current production schedule based on the target production equipment, and returning to the steps of predicting the ending inventory of filter rods for each brand in the next production cycle. This invention enables the rational allocation of production equipment and improves the rationality and stability of the production scheduling scheme.

The embodiment of the invention relates to the technical field of data management, in particular to a collaborative management method and system for clinical test items, and the method comprises the steps: carrying out the live collection of each unit region of a test site, and obtaining the live information of the test site; the project progress of each clinical test project performed in the test site is monitored in real time to generate the test demand information of the subsequent time, the test capability of the test site in the subsequent time is analyzed based on the live information to obtain an unoccupied scheduling list, and the test demand information is subjected to implementation simulation in combination with the unoccupied scheduling list and the live information. And generating a project scheduling plan, sending a scheduling instruction to an executor of each clinical test project according to the project scheduling plan, and continuously collecting response information of the executor to the scheduling instruction so as to correct the project scheduling plan.

The present invention discloses a sensing-computing collaborative high-speed railway contact network defect real-time detection task scheduling system and method, which combines the sensing-computing collaborative framework, decouples the high-speed railway contact network defect detection task, splits the subtasks, establishes a sensing-computing collaborative high-speed railway contact network defect real-time detection scheduling model, designs and improves the cuckoo genetic algorithm scheduling method to obtain task scheduling decisions, and reasonably schedules tasks to edge devices. The system and method provided by the present invention effectively improve the task execution efficiency and edge device resource utilization in the contact network defect detection scenario, better meet the requirements of real-time detection, and realize the reasonable allocation of edge computing resources and tasks to be detected in the contact network defect detection scenario under the sensing-computing collaborative architecture.