455 results about "Waiting time" patented technology

The present invention discloses a third party registration processing method based on the IMS network, which comprises that a UE completes the registration on a S-CSCF entity; the S-CSCF entity starts a waiting timer; the UE and a P-CSCF entity initiate and complete a registration status subscribing respectively to the S-CSCF entity; the S-CSCF entity initiate a third party registration to an AS when the waiting time of the waiting timer is enough. Through the present invention, the S-CSCF entity performs a waiting after the UE is successfully registered, to make the subscribing success of the registration status of the P-CSCF and the UE take precedence over the third party registration and avoid the situation of conflicting data of the UE, the P-CSCF, the S-CSCF and an HSS, to make the UE, the P-CSCF and the S-CSCF effectively process the abnormal circumstance occurred when the third party registration fails.

The invention relates to the technical field of elevator group control, in particular to an elevator group control method and system based on deep learning, and the method comprises the steps: building an elevator taking behavior time sequence data set through collecting historical elevator taking behavior data and combining with an elevator calling request and the number of people waiting for an elevator obtained through image recognition; the elevator taking frequency, the elevator calling interval and the passenger number fluctuation are modeled by adopting a long-short-term memory network, passenger flow periodical characteristics in workdays, holidays and peak periods are extracted, the passenger flow of each floor in the future is predicted, and pre-scheduling deployment of idle elevators is completed in advance. In the scheduling stage, state input containing the elevator running state and predicted flow is constructed, a reinforcement learning model is introduced for strategy optimization, a reward function is constructed based on passenger waiting time, response timeout and the service completion number, a scheduling strategy is driven to continuously converge, elevator response distribution is optimized, and position presetting and path adjustment are preset. And the scheduling intelligence and the service efficiency are improved.

The invention discloses an intelligent scheduling method based on task optimization. According to the method, firstly, the task load of each time period is predicted through historical data, and then an M / M / c queuing model is established to quantify a task queuing duration expected value as an optimization target. A two-stage optimization strategy is adopted: in the first stage, the optimal number of service desks in each time period is determined by applying dynamic planning, and accurate distribution of human resources is realized; in the second stage, specific employees are distributed to shifts through constraint planning, and meanwhile, complex constraints such as total working time fixing, continuous working duration, shift intervals and skill matching are met. According to the system, a queuing theory, constraint optimization and a prediction model can be combined, and on the premise of ensuring the feasibility of a scheduling scheme, the task processing waiting time is effectively shortened, and the service quality and the human resource utilization rate are improved.

The invention is suitable for the technical field of traffic control, and provides a road section pedestrian crossing signal control method and system based on human and vehicle postures. The method comprises the following steps: acquiring instantaneous speed and position data of a head vehicle on each lane in front of a pedestrian crossing in real time, and calculating the maximum crossing time by combining the length of the pedestrian crossing and the type of a pedestrian; determining the length of the upstream and downstream judgment area of the pedestrian crossing based on the road design speed and the street crossing time; monitoring the number of pedestrians and the longest waiting time in the waiting area, and judging whether a first triggering condition is met or not by combining a reasonable waiting time threshold value and a capacity threshold value; judging whether a second triggering condition is met or not by comparing the theoretical driving time of the vehicle with the pedestrian crossing time in the judgment area; and when the first and second trigger conditions are met simultaneously, starting a pedestrian green light phase, otherwise, maintaining the current signal state. According to the invention, the waiting time of pedestrians and vehicles can be effectively reduced, and the intersection passing efficiency and safety are improved.

The invention provides a timed task execution optimization method and system. The method comprises the following steps: forming a timed task execution optimization system architecture; determining a corresponding calculation factor to obtain a dynamic priority score; predicting the to-be-predicted task data by using the task prediction model to obtain a task execution time prediction value; analyzing the to-be-executed task queue, calculating the average waiting time, determining a multiple factor according to the task priority and the system load state, and identifying the task with the task execution time prediction value larger than the dynamic threshold value in the to-be-executed task queue as a long task; performing automatic fragmentation processing on the long task, generating a fragmentation result, determining a scheduling sequence based on the dynamic priority score and the task execution time prediction value, and generating a scheduling decision; and performing resource availability evaluation on the resource use data to obtain a node resource evaluation result, and allocating execution resources for the selected task. According to the method, the problems of efficiency and reliability of the timed task execution system in a high-load scene are solved.

The invention provides a multi-factor collaborative dynamic priority task scheduling method based on waiting time feedback, which is characterized by comprising the following steps of: initializing waiting time, task criticality and weight values of queue length, initializing a mixed task set and a task waiting queue, and initializing the task waiting queue into an empty set; entering a task waiting queue; updating the priorities of all tasks in the task waiting queue; sorting the tasks in the task waiting queue according to the priority; monitoring whether a new task arrives in real time; judging whether the newly arrived task meets a preemption condition or not; updating the historical average waiting time of the task; updating weight values of task waiting time and queue length; and judging whether all tasks in the mixed task set are scheduled. According to the method, long-term hunger of low-priority tasks is avoided, and the average waiting time of the tasks is shortened; the preemption threshold value is dynamically adjusted, and the context switching overhead is reduced; a dynamic weight mechanism is designed, and the self-adaptive capacity of the system is improved.

Methods, systems, and apparatuses are provided for wait timers of Non-Terrestrial Network (NTN) Store and Forward (S&F) in a wireless communication system, wherein a method for a UE comprises initiating a first procedure to a first network, wherein the first procedure is an attach, tracking area update (TAU) procedure, or a service request procedure, receiving a configuration of a wait time for an S&F operation, starting a first timer based on the wait time, wherein the UE is prohibited to initiate the first procedure to the first network for the S&F operation when the first timer is running, and stopping the first timer if the UE initiates or successfully completes a second procedure in a cell of a second network, wherein the second procedure is an attach, TAU procedure, or a service request procedure.

The invention discloses an intelligent outpatient service guidance and triage management method and system based on artificial intelligence. The method comprises the following steps that patient information, symptoms and outpatient service data are collected to generate triage input; constructing a triage optimization model based on the input, setting waiting time, path cost, load rate and priority satisfaction degree as targets, and setting a time window, resources and dependency constraints; an improved squirrel search algorithm is initialized, a population code is adopted to represent a distribution scheme, and a fitness function is established; updating the candidate scheme according to a fitness function in iteration; repairing and locally optimizing the updating scheme; when the operation data fluctuates, self-adaptive adjustment is triggered, and updating is continued; and when the fitness function converges or the iteration upper limit is reached, outputting an optimal triage scheme, including departments, time windows and path allocation, and executing incremental optimization when the patient arrives or the shift arrangement is changed. The triage efficiency is improved, the load is balanced, and the requirements of priority patients are met.

The invention provides an AI dialogue device and method for financial analysis, and belongs to the technical field of artificial intelligence. The device comprises an intention recognition module used for recognizing a financial intention queried by a user; the task scheduling module is used for activating the processing unit according to the intention; the tool calling module is used for calling an external tool to obtain information; the concurrent execution module is used for executing calling of a plurality of external tools in parallel; the result fusion module is used for integrating multi-source information; the reply generation module is used for generating a final reply; and the streaming output module is used for gradually transmitting the final reply to the client in the form of data stream. According to the method, the total data acquisition time is shortened by concurrently executing multiple tool calls, and part of content is displayed to the user in advance through streaming output before the final reply is completely generated, so that the waiting time perceived by the user is remarkably shortened, and the real-time response experience of the system is optimized while the professional property of financial analysis is ensured.

The invention discloses a process manufacturing factory material scheduling system based on intelligent agents. The system comprises a central coordination intelligent agent, a plurality of process intelligent agents, a video subsystem and a trolley subsystem. The scheduling method based on the system comprises the following steps: S1, initializing the system; s2, real-time state monitoring; s3, dolly scheduling decision making: the process agent calculates the priority of each transport task according to the priority function; s4, according to the queue capacity of the downstream workshop and the current outlet material quantity, S5, path decision making; s6, returning a path decision; s7, performing global optimization adjustment; s8, performing exception handling and cooperative adjustment; according to the invention, organic combination of local autonomy and global coordination is realized, the real-time response capability of the system is ensured, global optimization is also realized, and compared with traditional centralized control, the system is faster in response; multiple constraint conditions and optimization targets are considered, the average waiting time of materials can be reduced by one third, and the trolley utilization rate can be improved by one fourth.

The invention discloses an integrated optimization method based on an abnormal state urban rail transit operation end period timetable and a jump stop plan. The method comprises the following steps: acquiring passenger demand data and train operation parameters in an operation end period; according to the passenger demand data and the train operation parameters, a mixed integer multi-objective optimization model is constructed, and the model comprises an objective function and constraint conditions; solving the mixed integer multi-objective optimization model by adopting a multi-objective whale optimization algorithm to obtain a Pareto optimal solution set; and outputting the Pareto optimal solution set for generating a time table and a jump stop plan of the operation end period. According to the method, the time table and the jump stop plan are integrated and optimized, so that the total waiting time of the passengers is remarkably shortened in the operation ending period, meanwhile, the number of the passengers who are not served due to jump stop is effectively reduced, and the overall operation efficiency and the service fairness are improved; according to the method, various optimization schemes can be flexibly generated, and decision basis is provided for operating enterprises.

The invention relates to the technical field of intelligent traffic system (ITS) and urban public traffic scheduling control, in particular to an intelligent bus scheduling method based on multi-source data fusion, which comprises the following steps: S1, a central scheduling platform receives and stores multi-source data; s2, obtaining a fusion feature sequence; s3, sending to a calibrated demand prediction model to obtain a point prediction and demand interval; s4, constructing a transport capacity interval with an upper bound and a lower bound based on the vehicle availability, the driver shift, the maximum passenger capacity of the single vehicle and the road section speed distribution; s5, calculating overlapping ratio = intersection / prediction interval length; when the vehicle number is lower than the threshold value, distributed robust multi-target scheduling optimization of an ambiguity set defined by the Wasserstein radius is solved, the departure interval and the vehicle distribution number are updated, and the target is that the vehicle waiting time condition is weighted in a risk value and an empty driving rate, and the vehicle number, the employees, the departure interval and the insertable control point constraint are met; and S6, issuing an instruction and executing according to a vehicle positioning and control point arrival event. And unified modeling and robust triggering in the same space-time key interval are realized.

The invention discloses an intelligent elevator calling system and method based on user behavior modeling and multi-dimensional priority scheduling, and relates to the technical field of intelligent elevator scheduling and user behavior analysis. The method comprises the steps that historical elevator calling data of a user is collected to construct a behavior model, and an elevator pre-calling request is predicted and generated; and after a real-time elevator calling request is received, user identities, watching time and floor distance parameters are extracted, priority scores are calculated according to a formula, the optimal elevator is scheduled according to score ranking, and the state is fed back. The waiting time of the user is shortened through elevator pre-calling, the multi-dimensional priority balances special user requirements and elevator efficiency, scenes such as hospitals and shopping malls are dynamically adapted, and the elevator resource utilization rate and the user experience are improved.

The invention provides a government affair hotline resource optimization method and device based on time sequence prediction and reinforcement learning. The method comprises the steps of obtaining historical service work order data of a preset historical time period from a government affair hotline service platform; according to the historical service work order, utilizing a time sequence prediction model to predict future service work order data in a preset future time period; and determining a resource scheduling strategy in the preset future time period by using a reinforcement learning model. According to the technical scheme provided by the invention, in order to improve the working efficiency and reduce the user waiting time and unnecessary troubles in the process that government affair hotlines serve people, the historical work order data is deeply analyzed by using the time sequence prediction model, and possible problem hotspots and service demand peak periods in the future can be more accurately predicted. The distribution strategy of manpower and technical resources is dynamically adjusted in combination with a reinforcement learning algorithm, and it is ensured that the optimal government affair hotline service response speed and service level can be kept in different time periods.

The invention relates to a charging pile intelligent distribution system and method, and the system comprises a user terminal module, the output end of the user terminal module is electrically connected with a cloud scheduling platform, and the output end of the cloud scheduling platform is electrically connected with a charging pile control module. According to the charging pile intelligent distribution system, through intelligent dynamic scheduling and elastic time window management, the utilization efficiency of charging resources is remarkably improved, the user waiting time is shortened, the power grid load balance is optimized, the system adopts a multi-target optimization algorithm, the user distance, the real-time electricity price and the charging pile load rate are comprehensively considered, and the system reliability is improved. According to the method, fairness distribution is ensured, emergency demand priority response is supported at the same time, scheduling transparency and data security are enhanced through application of the block chain technology, a credit rating mechanism effectively restrains user performance behaviors, and the system can dynamically adjust power distribution and quickly deal with equipment abnormity through cooperation of load balancing and fault self-healing functions, so that the system performance is improved. And the service continuity is ensured.

The invention relates to the technical field of information processing and commanding and dispatching, and discloses an information commanding and disposing method and system based on multi-source information fusion. According to the method, information flow features are analyzed through an event emergency degree evaluation algorithm, and an emergency degree score is calculated in combination with an event type rule base and an arrival rate deviation degree; obtaining the queue length and the average waiting time of the processing queue, and calculating a queue congestion factor; a dynamic priority value is calculated according to the product relation of the emergency degree and the queue congestion factor, and when the system load is increased, the priority difference between the high and low emergency degree information flows is increased; reordering the processing queues based on the dynamic priority values; when the queue congestion factor exceeds a threshold, the sampling frequency of the low priority information stream is reduced and the processing node extension is triggered. According to the method, the technical problem that key information is delayed to be processed in a multi-source information flow concurrence scene is solved, and the real-time performance of information processing in an emergency scene is improved.

The invention relates to a high-concurrency request processing method for reducing Linux kernel resource loss. The high-concurrency request processing method comprises the following steps: receiving a user request and extracting a routing key; the requests are distributed to one fragment in the fixed N fragments through a fragment event executor, each fragment is bound with a single thread and a bounded queue, and the same routing key requests are executed in the same fragment in a strongly sequenced mode according to the enqueue sequence; calling a coprogram state machine to push a business process in the fragment execution thread, and returning a state result of migrating to a next state, keeping a current state or terminating the process through a state processing function; dynamically triggering self-adaptive back pressure based on queue depth or waiting time delay, and adjusting a request submission strategy according to a queue filling rate and exponentially weighted moving average waiting time delay; and submitting the long blocking task to an asynchronous task subsystem, and performing isolated execution through an independent bounded queue and a small concurrent thread pool. The same-key sequence is guaranteed through fragmentation single-thread execution, and thread switching and lock contention are remarkably reduced.

The invention discloses a resource processing method and device, equipment and a storage medium, and the method comprises the steps: evaluating the priority of tasks submitted to a Kueue queue, so as to determine the admission sequence of the tasks; when the task is admitted and runs, the resource use condition in the task running process is monitored in real time; and according to the resource use condition, judging whether to trigger a task capacity expansion and contraction strategy so as to dynamically adjust the resource distribution of the task. On one hand, the resource size of the task and the overall resource of the queue can be dynamically adjusted to optimize the resource allocation efficiency so as to improve the system performance, and on the other hand, the task waiting time can be shortened, the task processing efficiency can be improved, load balancing can be realized, and the resource bottleneck can be avoided.

The present application relates to elevator dispatching technical field, disclose a kind of elevator dispatching arbitration method, comprising the following steps: step 1: receiving multi-source call request, corresponding identity fingerprint is assigned to each call request and monitors the waiting time of each call request;Step 2: obtain the current load of target elevator and car remaining space, whether the current load of target elevator and car remaining space meets corresponding call request is judged;When the current load of target elevator or car remaining space does not meet corresponding call request, then cancel the call request;When the current load of target elevator and car remaining space both meet corresponding call request, then carry out step 3;Step 3: using dispatching score model to calculate call request, obtain the score of call request;Step 4: using shadow dispatcher to send shadow instruction to target elevator, shadow instruction triggers the corresponding stop layer action of target elevator.Simultaneously, a kind of elevator dispatching arbitration system is also disclosed.

Vehicle (100), comprising: a sending control unit (110-T) configured to send a message; a receiving control unit (110-R) configured to receive the message; one or more switches (120) configured to forward the message from the sending control unit (110-T) to the receiving control unit (110-R), wherein the sending control unit (110-T) and each of the one or more switches (120) include an output port for transmitting the message; and a processor configured to perform limited timing analysis to determine a total wait time w k during the transmission of the message from the sending control unit (110-T) to the receiving control unit (110-R) as a sum of all output port wait times w i,jto determine at all outgoing ports to which the message encounters, taking measures to avoid or mitigate the total waiting time w k during transmission a time limit for the message is exceeded, and the limited timing analysis includes performing an iterative process and determining a lower bound (LB), an upper bound (UB), and a median value.

The invention discloses an intelligent elevator reservation method, which belongs to the technical field of elevator control, and comprises the following steps: through interaction of a mobile terminal and an elevator control system, dynamic adaptation of a reservation entrance is realized, and a reservation instruction meeting user requirements is generated; the authenticity and legality of the reservation instruction are ensured through multi-dimensional security verification; a mathematical model is constructed and solved, optimal allocation and scheduling of elevator resources are achieved, an optimized running diagram is generated, the total waiting time of passengers is minimized, and the crowding degree and energy consumption of a lift car are reduced; according to the optimized running diagram, the elevator is scheduled in advance, multi-mode arrival prompting is carried out, and the waiting time of a user is shortened; the user collects secondary biological characteristics at the entrance of the elevator hall and matches the secondary biological characteristics with the reservation data to calculate the matching similarity, and the elevator control system records the operation data. Therefore, elevator resource allocation can be balanced, and the crowding degree and energy consumption in the peak period are reduced.

To perform efficient demand response.SOLUTION: A process proposal device includes a processor and a storage unit, the storage unit holds evaluation information in which each of an adjustable amount of power consumption, a retention time, and a required number of workers is associated with a DR priority score, the processor acquires process information indicating a plurality of processes for producing a product, a past production plan, and sensor data acquired corresponding to the past production plan, and calculates an adjustable amount of power consumption in each process included in the process information based on the process information and the past production plan, A stay time in each process is calculated based on a past production plan and sensor data, a required number of workers in each process is calculated based on the past production plan, a DR priority score of each process is calculated based on an adjustable amount of power consumption, the stay time, and the required number of workers in each process, and evaluation information, and the DR priority score of each process is output.SELECTED DRAWING: Figure 3

Methods and apparatuses for providing an estimated time of arrival at a point of interest (POI) in a navigation system are described. According to one embodiment, the method includes collecting driving data and trajectory data, generating parking time data of the vehicles by deriving times required for the vehicles to park based on the trajectory data and integrating the times required for the vehicles to park, deriving travel times of the vehicles traversing links leading to an entrance to the parking lot based on the driving data, calculating the vehicles' entry wait times by aggregating the travel times, and generating entry wait time data by integrating the vehicles' entry wait times, and deriving estimated times of arrival of the vehicles by summing the times required for the vehicles to park and the entry wait times, and generating estimated arrival time data by integrating the vehicles' estimated times of arrival.

Systems and methods for providing a dynamic delay factor for using a remote control. A plurality of remote-control button presses are received by from a user. At least one button press time associated with the plurality of remote-control button presses is determined. A delay factor is generated for the user based on the at least one button press time. And at least one content receiver event, such as a wait time for a next button press or a length of time to display a menu, is employed based on the generated delay factor.

The invention belongs to the technical field of job shop scheduling, and particularly relates to a self-learning job shop scheduling method meeting waiting time constraint, which comprises the following steps: S0, constructing a job shop scheduling problem model with waiting time constraint; the method comprises the following steps: S1, acquiring job shop scheduling problem data, a configuration algorithm and operation parameters; s2, constructing chromosome individuals, generating chromosomes and initializing a population; s3, calculating the fitness value of each chromosome individual; s4, forming a new generation of population; s5, combining the fitness information of the current population, dynamically selecting a crossover rate Pc through a Q learning algorithm, and performing crossover operation on the population; s6, dynamically determining a mutation rate Pm in the same parameter combination space by using a Q learning algorithm, and performing mutation operation on the crossover progeny to generate an updated population; and S7, judging whether an iteration termination condition is met or not. According to the method, a feasible and near-optimal scheduling scheme can be efficiently generated on the premise of ensuring that the inter-process waiting time constraint is met.

This application relates to an elevator control method, device, and system; the method includes: when receiving a first hall call task, determining a first waiting time based on the login time of the first hall call task and the arrival time of the elevator responding to the first hall call task; and if a second hall call task is received while the elevator is performing a door closing action, comparing a time threshold with the first waiting time to control the elevator to perform a door reopening action or continue performing a door closing action; this method can improve the elevator's transportation efficiency while also enhancing the user's elevator riding experience.

The invention provides a task scheduling method and device and a storage medium, and the method comprises the steps: determining a plurality of task groups and the expected execution time of each task group according to a mode demand inputted by a user; traversing each task group, determining the waiting time of the current task group according to the expected execution time of the current task group for the traversed current task group, and storing the current task group to the target storage object according to the waiting time of the current task group; and the time wheel runs, and the task group in the time wheel is executed when the time wheel runs. According to the method, task scheduling and state management can be separated, task scheduling and state management can be cooperatively controlled, the scheduling performance and the scheduling reliability are considered, in the scheduling process, unified scheduling is carried out through the time wheel according to a fixed time unit, and the scheduling efficiency can be improved while flexible and refined task scheduling is realized. It is avoided that a thread is independently created for each task group, thread resources are saved, and the scheduling efficiency and the response efficiency are improved.

A molding system includes: a composition applying unit configured to apply a composition on a substrate; a molding unit configured to perform a molding process by bringing a mold into contact with the composition; a transport unit configured to transport the substrate between the composition applying unit and the molding unit; a unit configured to calculate an expected value of an interval time from the applying of the composition to start of the contact; and a control unit configured to perform control such that a difference between an actual interval time and a target value of the interval time is less than a predetermined value by changing at least one of a timing of the applying, a transport waiting time, a transport time, and a contact waiting time if the difference between the expected value and the target value of the interval time is equal to or greater than the predetermined value.

This allows operators to respond to users with minimal waiting time. [Solution] The information processing system (10) comprises a central control unit (12), an operator terminal (16), a user terminal (18), and an automated response device (20). Prior to the operator of the operator terminal responding to the user of the user terminal, the automated response device automatically responds to the user for a predetermined period of time. The automated response device sequentially asks the user questions about several items that need to be confirmed and obtains answers from the user. When it obtains answers from the user, it decides whether to include an icebreaker in the next question based on the remaining time and the number of items that need to be confirmed. If there is sufficient time remaining, the next question, which includes an icebreaker, is sent to the user terminal.

The embodiment of the invention provides a touch event processing method, a terminal and a storage medium, and relates to the technical field of terminals.The method comprises the steps that after a touch event is detected through an event packaging thread, touch data of the touch event is sent to a knuckle thread, and the touch event carrying a preset mark is sent to an event distribution thread. A touch event is detected through a knuckle thread, and after touch data of the touch event is obtained, a recognition algorithm is loaded to process the touch data to obtain a target type of the touch event, and the target type of the touch event is sent to an event distribution thread. After the event distribution thread receives the touch event and the target type, the preset mark of the touch event is modified into the target type, and the touch event is distributed according to the target type of the touch event, so that the waiting time of the event distribution thread can be saved, the time delay for responding to the touch operation of a user is reduced, and the user experience is improved. The smoothness of responding to the user touch operation is improved, and the user experience is improved.