65results about How to "Realize intelligent distribution" patented technology

A charge power distribution system for dual-path charging comprises a card-swiping unit, a system control unit, a charging module 1, a charging module 2, a power output switch unit and a charging output unit; the card swiping unit is used for obtaining user grade information; the charging module 1 and the charging module 2 are used for providing system charging output power; the power output switch unit is used for adjusting the output power of a charging interface; the charging output unit is used for outputting charging power and obtaining charging power demand information of a charged vehicle and feeding back the charging power demand information to the system control unit; the system control unit is used for controlling the power output switch unit according to the user grade information and the charging power demand information, which are fed back by the charging output unit, of the charged vehicle and a vehicle to be charged.

The invention belongs to the field of power supply for electric vehicles, and particularly relates to an intelligent street lamp management system with an electric vehicle wireless charging management function. The system comprises a monitoring center, a street lamp centralized controller communicating with the monitoring center through a GPRS network, multiple single lamp controllers communicating with the street lamp centralized controller through power lines, and multiple electric vehicle wireless charging piles communicating with the monitoring center through the GPRS network, wherein the street lamp centralized controller is arranged in a transformer; a power line led out from the transformer is laid on the road surface; one end of each single lamp controller is arranged in a lamp rod, and the other end is connected with the power line; each electric vehicle wireless charging pile is located below the power line corresponding to each single lamp controller; the electric vehicle wireless charging pile is a wireless charging transmission module; and the power line and each wireless charging transmission module are not physically connected. The electric vehicle wireless charging management function is added on the basis of realizing intelligent management on the street lamps, linkage with the intelligent street lamp management system is realized, and unified control and management are realized.

The invention discloses a method for pre-distributing aircraft berths in an airport. The method comprises the following step of distributing the berths by adopting a score penalty distribution method, wherein a score penalty range is a closed interval from 0 to 100 scores, the 100 scores represent that an aircraft cannot berth, the 0 score represents that the berth is most suitable for berthing, other scores represent different precedence orders, and a low score has a priority; score penalty standards comprise fixed score penalty and scheduled flight conflict score penalty; the fixed score penalty comprises type score penalty, airline company score penalty, international and national type score penalty and far and near berth score penalty; and a rule of the scheduled flight conflict score penalty is that when two airports are berthed at the same position, the conflict score penalty is 100 scores, and when the interval time is longer than the station-crossing shortest guarantee time, the score penalty is 0 score, wherein a score penalty calculation formula is that score=0.2*n^2, and n is a minute difference value of the interval time and the shortest guarantee time. According to the method disclosed by the invention, the berths of the airports can be intelligently distributed by a procedure, and actual utilization requirements are met.

The invention provides a power consumption service acceptance time limit management method and device, and relates to the technical field of power consumption service management. The method is applied to a server which communicates with a user terminal and multiple service terminals, and comprises the following steps: acquiring a transaction plan for a power consumption service; receiving a task progress periodically sent by the service terminal corresponding to a processed task node; when the task progress is completed, sending a starting notice to the service terminal of a next task node; determining a completion time limit of the next task node of the task node according to time when the starting notice is sent, a total task time limit and a time length at least required by completing the next task node of the task node; sending the completion time limit to the service terminal which processes the next task node of the task node. By such a design, the completion time limit of each link in the power consumption service can be intelligently allocated according to a practical condition, so that time for accepting the service is saved, and meanwhile, overtime for service transaction is also reduced.

The invention provides a log routing load balancing implementation method and a device. The method comprises the steps of obtaining cluster resource use condition monitoring data of a log storage layer of a cloud platform log storage system; performing load balancing processing according to the use condition monitoring data and a preset storage threshold, and determining updated routing configuration information; and processing a log file of the cloud platform log storage system according to the updated routing configuration information. According to the method, different applications are automatically distributed to the basis of different storage layer clusters in a balanced manner according to the early log data volume of each application and the storage condition of each cluster of thecurrent storage layer, a deployment container does not need to be manually reconfigured, automatic configuration updating is realized, and the configuration workload of operation and maintenance personnel is greatly reduced. Load balance adjustment of clusters of a storage layer and a buffer layer can be completed in a self-adaptive mode, and intelligent distribution of log storage clusters is achieved. Therefore, each cluster is efficiently utilized, and unnecessary resource waste is reduced.

The invention belongs to the technical field of artificial intelligence allocation, and discloses a hospital index assessment total analysis task allocation system and method. The method comprises the steps that a data acquisition module acquires target assessment analysis data and sends the target assessment analysis data to a data analysis module; the data analysis module analyzes the target assessment analysis data according to a preset operation rule and corresponding decomposed file data in a preset feature library to obtain target capability feedback data; the task allocation module decomposes the target assessment task based on the assessment characteristic requirement data and the target capability feedback data, and completes the allocation of the target assessment task according to the obtained target decomposition task to obtain a target allocation task; and the task monitoring module performs target value measurement and calculation on the target allocation task to obtain a current task progress corresponding to the target allocation task, and updates the target allocation task according to the current task progress. In this way, the execution progress of the task can be monitored while the assessment task is allocated according to the actual situation of the hospital.

The invention discloses a control method capable of reducing alloy ton steel cost consumption. The control method comprises a step 1) of calculating alloy ton steel standard consumption according to steel grade component element target values, component element recovery rate and alloy component element content value and according to a formula; a step 2) of designing an alloy adding model and calculating ton steel cost according to the alloy adding model; and a step 3) of calculating alloy adding variety and adding amount of smelting heat according to the alloy adding model with the minimum ton steel cost value based on results calculated through the step 2). After the control method is adopted, through the added alloy variety and weight, it can be guaranteed that alloy ton steel cost minimization is achieved on the premise that steel grade components are stable.

The invention provides a goods distribution method and device, an electronic device and a storage medium, wherein the method comprises the steps of obtaining the quantity information of goods in at least one candidate container and the distance information between the at least one candidate container and a target receiving position after receiving goods order information; selecting the target container from the at least one candidate container based on the quantity information of the goods in the at least one candidate container and the distance information between the at least one candidate container and the target receiving position; and using a distribution robot and the selected target container for goods delivery based on orders. By the adoption of the scheme, the target container canbe selected from the candidate containers, the distribution robot and the selected target container can be used for goods delivery based on orders, so that the problem that the labor cost is high when distribution is conducted in a manual mode is solved, the intelligent distribution is achieved, and meanwhile the distribution efficiency is improved.

The invention discloses a task scheduling method and device, and relates to the technical field of computers. A specific embodiment of the task scheduling method comprises the steps: determining taskactuators, and sending a workload calculation instruction to each task actuator; receiving a result value fed back by each task executor, and determining the time required for feeding back the resultvalue by each task executor so as to calculate the working efficiency of each task executor; and determining a to-be-processed task amount, and performing task allocation according to the working efficiency of each task executor. According to the embodiment, the processing capacity of each task executor is accurately evaluated in a workload proving mode, and intelligent task allocation is achievedaccording to the processing capacity of each task executor and the to-be-processed task amount, and the task processing speed is increased.

The invention relates to a switch and particularly relates to a single-phase capacitor switching switch. The switch comprises a lower casing and an insulating cylinder which is installed on an upper side of the lower casing, an insulating pull rod is installed between the lower casing and the insulating cylinder, a conductive clip is installed in the insulating cylinder, the insulating cylinder atan upper end of the conductive clip is equipped with a vacuum tube, the lower casing is internally equipped with a permanent magnet structure coil which is connected to a switch-off handle and a switch-off rod through a first switch-off spring, a main shaft is installed in the lower casing, and a side of the main shaft is equipped with a spring mechanism. The intelligent separate compensation inthe field of high-voltage capacitor switching can be achieved. A problem that the intelligent separate compensation cannot be achieved and only common compensation can be achieved in the field of high-voltage capacitor switching at present is solved in the aspect of electric energy quality required by the nation.

The invention provides a disinfection task allocation method and device, a storage medium and equipment. The method comprises the following steps: acquiring a bounding box generated by a user through frame selection on a preset disinfection map; according to the bounding box, determining a to-be-killed area selected by the bounding box, and calculating the area of the to-be-killed area and an average killing difficulty coefficient of a killing target object in the to-be-killed area; according to the area of the area to be disinfected and killed and the average disinfection and killing difficulty coefficient, determining the number of disinfection and killing personnel corresponding to the area to be disinfected and killed; and distributing a disinfection task according to the number of disinfection personnel and the identification information of the corresponding to-be-disinfected area. According to the method, the area of the disinfection area and the corresponding disinfection difficulty are combined, the disinfection difficulty is confirmed by the disinfection difficulty coefficient of each disinfection target object in the area, and the corresponding disinfection number of people is dynamically adjusted so as to adaptively adjust the disinfection number of people, so that the disinfection area is more matched with the disinfection number of people; the technical problem of unreasonable distribution of disinfection tasks can be effectively solved.

The invention discloses an automatic selling method and an automatic selling device for cassette items on a train. According to the characteristics of the train, the fixed automatic selling device forthe cassette items is mounted in a carriage of the train, and the cassette items to be sold are stored in the automatic selling device for the cassette items according to classification and sequence;the cassette items are automatically sold to the travelers on the train through an automatic selling system in the automatic selling device for the cassette items. According to the automatic sellingmethod and the automatic selling device which is fixed to the interior of the carriage disclosed by the invention, the cassette items are sold automatically through the automatic selling device; the automatic selling device for the cassette items is simple and convenient, brings convenience to train customers, and also reduces service staff on the train, and reduces labour cost.

The invention discloses a computing power scheduling method and device based on Kubernetes, and relates to the field of artificial intelligence. The method comprises the following steps: analyzing computing resources required by a machine learning current training task to decompose the type and quantity of a target accelerator card, screening out a corresponding machine node set according to a preset strategy in combination with computing power global data of all machine nodes in a Kubernetes cluster, and locking the computing resources of the machine nodes used by the current training task according to the corresponding machine node set, and establishing an inter-node mutual trust interconnection network on the machine nodes used by the training task, running the machine nodes used by thetraining task, and learning a training program to complete training. The device comprises an initial module, an analysis module, a screening module, an establishment module and a training module. According to the invention, intelligent distribution of resources is achieved, manual adjustment is not needed, and the efficiency is greatly improved.

The embodiments of the present invention disclose a product distribution method. The method includes the following steps that: at least two types of products to be distributed having the same functions in a first inventory are adopted to form a first product group, wherein the first inventory is used to provide products to be distributed; a first order for each type of products to be distributed in the first product group is obtained, wherein the first order contains the first demand quantity of each type of products to be distributed in the first product group; the difference value of the first demand quantity of each type of products to be distributed in the first product group and the quantity of each type of products to be distributed in the first product group is calculated, and firstparameters are obtained; the absolute value of the sum of parameters of which the numerical values are negative in the first parameters is calculated, so that a first quantity is obtained, and the sum of parameters of which the numerical values are positive in the first parameters is calculated, so that a second quantity can be obtained; and the products to be distributed in the first inventory are distributed to a first sub-inventory corresponding to the first order according to the first quantity and the second quantity. The embodiments of the present invention also disclose an electronic device and a computer storage medium.

The invention relates to a method for distributing an account number resource, a device and equipment. The method is applied to a resource distributing platform. The method comprises the steps of receiving a current consultation application request which is transmitted by a target user through a consultation service platform, wherein the current consultation application request is used for requesting a consultation account number resource of a video service platform, determining whether the target consultation account number resource which satisfies a preset resource using condition exists onthe resource distributing platform according to the current consultation application request; and if yes, distributing the target consultation account number resource to target users, thereby realizing intelligent distribution of the consultation account number resource. When an executed meeting is canceled midway, the resource distributing platform can perform re-distribution on the consultationresource account number which is used by the consultation, thereby improving utilization rate of the consultation resource account number.

The invention belongs to the technical field of intelligent detection circuit control, and specifically relates to an industrial intelligent detection circuit control system. The industrial intelligent detection circuit control system comprises transformers, a control box, a current distributor, and current sensors. The current distributor is arranged in the control box. The current distributor divides a main input circuit into a main line circuit and multiple auxiliary line circuits. The main line circuit and each auxiliary line circuit are respectively provided with a leakage protection switch and a transformer. The current sensors are used to detect the auxiliary line circuits, detected data is analytically processed by a processor in the control box, and the intelligent control switches on the lines are controlled. The beneficial effects are as follows: intelligent distribution is realized; too large current of the auxiliary lines and damage to electrical equipment on the main line caused thereby are avoided; over-load operation of the circuit system is avoided; and convenience is brought to electricity utilization in industrial production.

The invention discloses a goods source optimal allocation model construction method, an optimal allocation model and an optimal allocation method, belongs to the field of deep learning, and aims to solve the technical problem of how to intelligently and optimally allocate goods sources in a marketing system. The method comprises the following steps: S100, constructing a BP neural network model andan LSTM recurrent neural network model; collecting retailer basic information data and retailer historical ordering data; S200, training a BP neural network model by using the retailer basic information data in the training sample; training an LSTM recurrent neural network model according to the output retailer goods source historical distribution data and the retailer historical ordering data inthe training sample; and S300, if the model accuracy does not accord with the threshold, circularly executing the step S200 until the model accuracy reaches the threshold. The model is the goods source optimal allocation model constructed by the method. According to the optimal allocation method, parameter decision-making goods source optimal allocation is carried out through the optimal allocation model constructed through the method.

The invention provides a resource management method and device and electronic equipment. The method comprises the following steps: receiving business personnel input to configure information parameters and state judgment rules of exclusive resources, the information parameters comprising resource type parameters, time parameters and operation parameters; receiving an access request of a client, wherein the access request comprises user identification information; sending page data to the client based on the access request so as to enable the client to display a page containing an exclusive resource receiving module, the page comprising a popup window for receiving user operation and a sharing link; acquiring page submission information of a page related to the exclusive resource to determine a receiving state of the exclusive resource; and judging the use condition of the exclusive resources received by the user so as to manage the exclusive resources. According to the method, resourcemanagement and allocation can be carried out more effectively, so that intelligent allocation of resources to specific crowds can be realized.

The invention provides a design method of a security edge federated learning system based on a block chain, and the method employs a consensus mechanism based on a practical Byzantine fault-tolerant method and a robust global model aggregation algorithm to resist the attack of a malicious edge device and a malicious edge server on federated learning training. The safe and credible edge federated learning system is realized, and the convergence performance of edge federated learning model training is effectively improved. In order to further improve the training speed of the block chain-based secure edge federated learning system and reduce the time delay of system model training and consensus, the invention also provides a resource optimization algorithm based on deep reinforcement learning, so that the rapid and efficient allocation of wireless bandwidth and sending power in a dynamic wireless channel environment is realized, and the resource optimization efficiency is improved. The resource utilization maximization of the secure edge federated learning system is improved, and then the training time delay minimization of the block chain-based secure edge federated learning system is realized.

The invention discloses a multi-die machine head for double-line extrusion and an extrusion method thereof, and the multi-die machine head comprises an extrusion screw rod, a rubber material distribution system, a first runner, a second runner, a first die hole and a second die hole. The extrusion screw rod is used for plasticizing and melting a rubber material and extruding the rubber material to a rubber material distribution system. The rubber material distribution system is connected with the extrusion screw rod and is used for controllably distributing the rubber material to the first runner and the second runner. The first runner is formed on a machine head body, is communicated with the rubber material distribution system and is used for receiving the rubber material distributed by the rubber material distribution system. The second runner is formed on the machine head body, is communicated with the rubber material distribution system and is used for receiving the rubber material distributed by the rubber material distribution system. The first die hole is communicated with the first runner and is used for receiving the rubber material conveyed by the first runner and extruding the rubber material to a cable core. The second die hole is communicated with the second runner and is used for receiving the rubber material conveyed by the second runner and extruding the rubber material to the cable core. The production efficiency of the extruder head is improved.