378 results about "Arrival time" patented technology

The invention provides a ship lockage appointment scheduling optimization method, system, equipment and medium, and belongs to the field of shipping traffic scheduling, and the method comprises the steps: based on an arrival time prediction model, according to the planned arrival time, historical actual arrival time and ship attribute data of at least two appointment ships, obtaining a ship lockage appointment scheduling optimization model; generating a mean value and a standard deviation of the estimated arrival time corresponding to each reserved ship; based on the mean value and the standard deviation of the estimated arrival time, constructing a multi-target optimization model meeting a preset optimization target and a preset constraint condition; calculating corresponding scheduling reference time according to the mean value and the standard deviation of the estimated arrival time, and creating an initial scheduling scheme population according to the scheduling reference time; and based on a non-dominated sorting genetic algorithm and a variable neighborhood search algorithm, solving the multi-objective optimization model according to the initial scheduling scheme population to obtain a final scheduling scheme. According to the invention, the traffic jam of the hub is effectively relieved, and the lockage efficiency of the ship is improved.

The invention relates to the technical field of intelligent prediction, and discloses an emergency resource reserve intelligent prediction system and method based on a graph neural network, and the system comprises a space-time diagram construction module which collects port, berth, channel segment, emergency warehouse and ship information, passing time window information and emergency information, and constructs an event flow heterogeneous space-time diagram; the backbone screening module is used for screening backbone sub-graphs and setting a relation feature conversion rule and a time feature representation rule; the graph memory updating module is used for updating node and edge features; the multi-task prediction module is used for outputting quantile demand prediction, reachability scores, transportation timeliness and safety stock threshold values; the consistency constraint training module is used for executing consistency constraint training; the inventory allocation decision-making module is used for generating allocation distribution quantity and outputting predicted arrival time; and the berth time window recharging module is used for generating a berth operation time window and recharging the actual arrival time. According to the invention, emergency resource demand prediction, inventory threshold calculation and allocation and berth operation linkage decision are realized.

The invention discloses a time management optimization method and a display device for an ambulance, and belongs to the technical field of medical first aid management. The method comprises the steps of obtaining an exclusive data set and multi-dimensional dynamic data of a target patient in real time, calling a preset demand rule base, calculating the emergency degree of the target patient in combination with the exclusive data set, and performing emergency level division; constructing a transfer planning model, screening a resource-adaptive target hospital for a target patient, synchronously planning a global optimal driving path, calculating predicted arrival time, and generating an individual transfer plan; global summarization is carried out on target patients to be transferred to form a matrix to be transferred, resource adaptation verification is carried out on the basis of a target hospital, an actual target transfer set is generated, and the transfer process is monitored in real time to update the predicted arrival time in real time; and after the transfer is completed, obtaining the actual arrival time, calculating the predicted deviation value, marking the deviation reason, forming an optimized data set, shortening the transfer time efficiency, and reducing the treatment delay risk.

The invention discloses an online car-hailing order allocation method and system based on an artificial intelligence algorithm, and relates to the technical field of intelligent scheduling, and the method comprises the steps: obtaining to-be-allocated order data and driver data; determining a candidate driver set by adopting a dynamic search radius and a multi-state driver screening strategy, and calculating an estimated arrival time in combination with a real-time traffic condition; establishing a multi-factor order receiving willingness evaluation model, and calculating the order receiving probability of each order-driver combination; constructing a comprehensive matching degree evaluation model, calculating the matching degree of all order-driver combinations, and generating a matching degree matrix; processing the matching degree matrix by adopting a global optimization algorithm, and outputting an order-driver allocation result; and pushing an order to a driver in the order-driver allocation result, monitoring a response state, and performing reallocation processing on a non-response condition. Through the multi-factor order receiving willingness evaluation and the global optimization algorithm, the success rate and matching precision of order allocation are improved, the order waiting time is shortened, and the overall allocation efficiency is improved.

The invention relates to the technical field of server hardware fault diagnosis, in particular to an intelligent fault diagnosis method and system for a server mainboard and a storage medium. The method comprises the following steps: configuring monitoring parameters in a bus link controller of a server mainboard, and setting an undisturbed sampling window as a training sequence time period and an idle symbol time period in a bus physical layer data transmission process; periodically reading a link adaptive equalization parameter, an error count value and symbol arrival time through a bus link controller register, and simultaneously collecting a temperature parameter and a voltage parameter at the current moment; and combining the link adaptive equalization parameter, the error count value, the symbol arrival time, the temperature parameter and the voltage parameter at the same sampling moment as a signal quality vector at the moment. According to the method, two data transmission-free windows of the training sequence time period and the idle symbol time period are identified and utilized, so that the monitoring operation and the service data are staggered, and the sampling operation is ensured not to interfere with normal data transmission.

The invention discloses a logistics arrival time forecasting system and method based on multi-data fusion, relates to the technical field of logistics arrival time forecasting, and aims to solve the technical problem that the deviation between the forecasting result of an existing logistics arrival time forecasting system and the actual arrival time is large. The system comprises a data acquisition module, a path planning module, a time calculation module and an early warning and output module. The output end of the data acquisition module is connected with the path planning module and the time calculation module, and the data acquisition module is used for acquiring multi-source data. The multi-source data comprises historical logistics data, order and delivery information data, weather data, real-time road condition data, map data, transportation tool characteristic data, cargo special demand data, transportation tool connection hidden loss data and transportation tool collaborative delay association data; and the output end of the path planning module is connected with the time calculation module. The method has the advantage of improving the accuracy of the arrival time forecast in the multimodal transport scene.

The present invention relates to an intelligent berthing method for inland anchorages, comprising the following steps: S1: a ship sends a berth application and obtains the ship's current information; S2: using the ship information to predict the ship's arrival time at each available anchorage; S3: collecting information on all currently moored ships at the anchorage and allocating berths to incoming ships based on the current berthing situation at the anchorage; S4: after a ship has moored, checking whether it has moored at the designated location as required; S5: after receiving a departure information, collecting the ship's departure time for use in allocating berths to subsequent incoming ships; and S6: upon reaching the scheduled departure time, the ship performs the departure operation. This method can predict ship arrival times and intelligently allocate berths to incoming ships, thereby reducing anchorage management costs, improving anchorage operation efficiency, and enhancing the intelligent construction of anchorages.

The invention relates to a medical-seeking registration appointment method and system and a medium, and relates to the technical field of medical information services. The method comprises the following steps: recommending a doctor and a corresponding doctor-seeing date to a user on the basis of registration information including a doctor-seeing department and the severity of an illness state of the user, determining doctor-seeing time and hospital arrival time of the user on the doctor-seeing date on the basis of the doctor-seeing date selected by the user and a doctor-seeing time determination condition preset by a system, and sending doctor-seeing information to a user terminal. In the process, the doctor is recommended based on the severity of the illness state, so that the waste of doctor resources can be reduced, and the doctor-seeing time and the hospital arrival time of the user at the doctor-seeing date are determined based on the doctor-seeing, the doctor-seeing date and the doctor-seeing time determination condition, so that the doctor-seeing efficiency is improved, and the doctor-seeing queuing time is reduced.

The invention provides a ship lock intelligent scheduling method and system considering ship classification and dangerous goods isolation, and the method comprises the steps: S1, obtaining the information of a to-be-scheduled ship and the information of a lock chamber, and constructing a conventional ship information list ListN and a dangerous ship information list ListD based on the danger level of the to-be-scheduled ship; s2, according to the management method of the hydro-junction where the lock chamber is located, the danger level of independent lockage is obtained, and the safety size of the ship needing independent lockage in the ListD is modified so that the lock chamber can be fully occupied by the ship; and S3, respectively taking the ListN and the ListD as an input list ListI, calculating a global highest scheduling score of the ListI based on the safety size, the arrival time and the type of the ship, and selecting a global optimal scheduling scheme corresponding to the higher global highest scheduling score in the ListN and the ListD as a final scheduling scheme. The united targets of improving the utilization rate of the lock chamber, reducing the waiting time of the ship, weighing the priority of the ship and isolating the dangerous goods ship are achieved.

The invention relates to the technical field of multi-machine cooperative control, in particular to a multi-machine cooperative automatic operation method and system for train loading. Comprising the steps that position information and predicted arrival time fluctuation data of a train are collected in real time through a sensor network, and an arrival time uncertainty quantitative index is obtained through a time sequence prediction model; according to the index, judging and determining an equipment allocation priority sequence; adjusting equipment working parameters and generating a preliminary adjustment scheme by combining the equipment state data and an optimization algorithm; according to the optimization parameters and the multi-machine cooperation requirements, a resource utilization model is constructed, a multi-machine cooperation rotation time table draft is obtained, refining is carried out, and finally a refining time table is generated; and based on the time table and the real-time feedback, updating the equipment cooperation time to obtain a final multi-machine cooperation scheduling scheme. The operation state of the loading equipment can be dynamically adjusted, the collaborative operation efficiency of the equipment is improved, loading delay is reduced, and the resource utilization rate is maximized.

The invention relates to a material weighing acceptance technology, and relates to an intelligent construction site unattended reservation weighing material acceptance system. According to the method, the estimated arrival time is calculated according to the initial position of the reserved vehicle, the initial wagon balance number is allocated to the reserved vehicle, and when the reserved vehicle is about to arrive, the finally allocated wagon balance number of the reserved vehicle is determined according to the current use conditions of all wagon balances of a construction site; obtaining the position deviation degree of the reserved vehicle after driving into the wagon balance, judging whether the position of the vehicle needs to be adjusted or not, recording the total weight of the adjusted reserved vehicle and associating the total weight with the identified license plate number, obtaining the weight of the unloaded reserved vehicle, and calculating the net weight of materials by combining the total weight of the reserved vehicle associated with the license plate number. The weight range is compared with the weight range of the reservation application, and corresponding acceptance processing is executed according to a comparison result; reasonable wagon balance resource allocation is realized, weighing congestion and congestion are reduced, weighing time consumption is shortened, weighing data and acceptance results are improved, and labor cost is reduced.

The invention provides a building material scheduling management method, and belongs to the technical field of building material scheduling, and the method comprises the following steps: collecting material basis and stock information, constructing an evaluation model, and determining a weight by taking the influence on the project progress and the market scarcity degree as indexes; constructing an engineering three-dimensional model, disassembling the total construction period as an operation section, analyzing the association strength of materials and key nodes, and determining the morning and later periods of arrival; taking the stock information and the arrival time as input, constructing a transportation and time efficiency dual-objective function, and optimizing to obtain transportation details; in combination with the storage cost and the loss rate, constructing a storage income and consumable cost dual-objective function, and optimizing to obtain storage details; and a scheduling database is constructed, information is integrated, and a material demand superposition time point is identified. The systematic scheduling management method can realize accurate evaluation of material information, deep collaboration with the project progress, consideration of transportation and storage optimization, and integration of whole project material demand information, so as to improve scientificity and high efficiency of construction project material management.

This logistics network management device 1100: calculates, for each vehicle 1300, based on the expected arrival time at a delivery destination location at which the vehicle will arrive after an expected arrival at a delivery origin location and also based on information about vacant period of each shared unit 1210 at the delivery destination location, a recommended arrival time, which is the arrival time at the delivery destination location for which the period from arrival at the delivery destination location until the start of a prescribed operation is shortest; calculates a recommended departure time from the delivery origin location; and, for each vehicle 1300, when the vehicle 1300 can arrive at a shared unit 1210 that can be used at the delivery origin location at a time at or before the recommended departure time, displays information indicating that the vehicle 1300 should arrive at the stated time at the shared unit 1210 that can be used at the delivery origin location.

The invention provides an air-railway combined transportation-based travel route planning method and a related device. The method comprises the steps of obtaining a starting point position, a first departure moment corresponding to the starting point position and a destination position; based on an air-railway combined transport mechanism, according to the starting point position and the destination position, carrying out travel planning to obtain a plurality of travel routes; obtaining the total estimated duration, the total estimated cost and the estimated arrival time of each travel route in the plurality of travel routes to obtain a plurality of total estimated durations, a plurality of total estimated costs and a plurality of estimated arrival time; evaluating each travel route in the plurality of travel routes according to the plurality of total estimated durations, the plurality of total estimated costs and the plurality of estimated arrival moments to obtain a plurality of evaluation values; and selecting the maximum value in the plurality of evaluation values, and taking the travel route corresponding to the maximum value as a target recommended travel route. According to the invention, a reasonable air-railway combined transportation scheme can be recommended for the route planning.

The invention discloses a channel scheduling method and a storage medium, and the method comprises the steps: building a network flow-discretization ship kinematics model based on channel parameters which comprise ship lock parameters and ship channel parameters; first real-time data of the ship arriving at the ship lock is obtained in real time, a queuing strategy is obtained, and the first real-time data comprises ship arrival time, departure port information and destination port information; generating a ship lock scheduling plan based on the network flow-discrete ship kinematics model and a queuing strategy; and if the ship leaves the ship lock, generating a ship lane scheduling plan based on the network flow-discretization ship kinematics model. According to the method, the channel topology is abstracted into the network flow model with capacity constraint, and discretization simulation is carried out on ship microcosmic motion in a superposition manner, so that multi-scale coupling of macroscopic scheduling and microcosmic behaviors can be realized, the channel congestion prediction error rate is reduced, and the scheduling efficiency is improved.

The invention discloses a discrete service flow predictive digital triggering method and system under time delay constraint, and relates to the field of network service quality assurance, and the method comprises the steps: collecting an arrival time sequence, a packet length sequence, network state data and service level protocol parameters of a plurality of discrete service flows; performing multi-scale dependency decomposition on the arrival time sequence, and predicting an arrival amount and a queuing length in a future time window; calculating and predicting a residual time delay budget in combination with the maximum tolerant time delay, and mapping the residual time delay budget into a digital triggering probability representing the scheduling urgency degree; and further fusing the stream importance index to determine the scheduling weight, and dynamically adjusting the service sequence and resource allocation of the edge nodes according to the scheduling weight. Therefore, advanced scheduling triggering of multiple paths of service flows is realized, and the time delay guarantee capability and the resource scheduling efficiency are improved.

Techniques for determining an estimated time of arrival associated with a pickup location are described herein. For example, a customer can order a good or service for pickup at a pickup location. In some examples, order data can include a pickup location intent, such as a drive-through location, a pickup window, or a parking location. A location of a user computing device can be determined and can be input to a machine-learning model trained to determine estimated times of arrival for a particular location. In some examples, the machine-learning model can be trained with ground truth data specific to the location for which the model is to determine estimated times of arrival. The machine-learning model can output the estimated time of arrival and can update the time at any regular or irregular intervals, which can be used to prioritize an order in an order queue.

The invention provides an online car-hailing order allocation method and system based on artificial intelligence, and a storage medium, and relates to the technical field of order allocation. The method comprises the following steps: constructing a complete order feature set by combining a starting point, a terminal point and an order type of an order, arrival time required by a passenger and historical scores of the passenger to a driver with current weather category and traffic flow information, constructing collected driver features, order features and environment features into feature vectors, and obtaining an order feature set based on a supervised learning method. Corresponding driver correlation indexes, order correlation indexes and environment correlation indexes are calculated, the model is trained, ordering is carried out according to order receiving probabilities, orders are preferentially recommended to the driver with the highest order receiving probability, and therefore the order matching success rate is increased, and the waiting time of passengers is shortened.

The invention relates to the technical field of anti-unmanned aerial vehicle detection, and discloses an unmanned aerial vehicle pilot grabbing method, electronic equipment and a computer readable storage medium, the method comprises the following steps: obtaining signal detection results of n detection equipment, n being a positive integer greater than 2; judging whether the n detection devices all detect the first target unmanned aerial vehicle or not according to the signal detection result; if the n detection devices all detect the first target unmanned aerial vehicle, the arrival time of a target remote control signal arriving at each detection device is obtained, n first arrival time is obtained, and the target remote control signal is used for indicating flight of the first target unmanned aerial vehicle; and according to the n first arrival times and the position information of the n detection devices, determining the position information of an emission source of the target remote control signal, so as to determine the position of the emission source as the position of a target pilot for controlling the first target unmanned aerial vehicle, and completing the position grabbing of the target pilot. Through the above mode, the method achieves the timely positioning of the black flying hand.

A system for estimating a delivery is disclosed. The system generates delivery time predictions, and generates a confidence score for each time prediction. The system also generates a publication determination for each particular time prediction based on the confidence score associated with each particular time prediction. The publication determination indicates whether to publish the particular time prediction or to not publish the particular time prediction.

This invention discloses a collaborative scheduling and path planning method for warehousing and logistics robot clusters, relating to the field of path coordination and planning technology. When constructing a directed topology graph, this method records the passage cost value and initializes a second-level occupancy record table to achieve accurate querying of the number of nodes occupied per second. When assigning tasks, if the starting node is full, the start is delayed to eliminate congestion at the starting point. During path generation, nodes are filtered based on their passage cost value, and nodes that are full at the arrival time are excluded to avoid leading to congestion points. When updating the record table, the robot number is entered at the arrival time, quantifying the occupancy into second-level data. During congestion analysis, the capacity of nodes with density ratios exceeding a threshold is temporarily reduced to shrink the number of occupants in advance. During traffic heat analysis, the passage cost value of the edges traversed is increased according to the robot type and loading level, so that subsequent paths bypass heavily loaded edges. During conflict resolution, temporary capacity is used to determine conflicts, and paths are regenerated according to the adjusted passage cost value, staggering spatiotemporal trajectories to reduce overlap.

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.

Provided is a technology capable of improving the satisfaction of passengers in a service for distributing content to the passengers of a vehicle. A control unit of an information processing device acquires a elapsed time, which is a time at which a vehicle actually passes a predetermined point midway along a predetermined travel route, and calculates, on the basis of the acquired elapsed time, a predetermined arrival time at which the vehicle is predicted to arrive at a destination of the predetermined travel route. When the predetermined distribution ending time of the content is earlier than the calculated predetermined arrival time, a control unit of the information processing apparatus calculates a remaining time length that is a difference between the predetermined arrival time and the predetermined distribution ending time. A control unit of the information processing device outputs suggestion information including information of the calculated remaining time length and information that prompts a delay of a predetermined distribution ending time of the content.

The present invention relates to a secure time transfer system and method based on bidirectional quantum key distribution. The transfer system may include a transmission channel between a communication terminal A and a communication terminal B, wherein communication terminals A and B may send single-photon signals to each other according to a quantum key distribution protocol and respectively detect the arriving single-photon signals; communication terminal A records the emission time t of the single-photon signal based on a local clock A. SA and arrival time t RA , the communication terminal B records the emission time t of the single photon signal based on the local clock B SB and arrival time t RB ; The communication terminal A also encrypts the transmission time t SA and arrival time t RA Transmitted to communication terminal B; communication terminal B according to the transmission time t SA Arrival time t RA , launch time t SB , and arrival time t RB Calculate the clock difference T between clocks A and B AB ; and, according to the clock error T AB Clock B is adjusted to compensate for the clock difference between clocks B and A, thereby achieving time transfer.

The invention discloses a flight plan automatic filling method and device for an electronic flight bag. The method comprises the following steps: extracting waypoint information of an original flight path from an original flight plan; acquiring a real-time position of the aircraft based on a preset time period; based on the real-time position and the waypoint information, determining a flight leg of the aircraft at the current moment through a preset leg discrimination algorithm; based on the flight segment, determining a newly added passed waypoint and a pre-flight waypoint of the aircraft; updating the state information of the newly-added passed waypoint into a passed state, and recording updating time; and based on the update time, filling the actual arrival time of the newly added passed waypoint in the flight plan electronic form, and correcting the predicted arrival time of the pre-flight waypoint. According to the method, the actual arrival time of the current waypoint in the flight plan can be automatically filled in, and the predicted arrival time of the next waypoint can be automatically corrected, so that the operation burden of flight crew is effectively reduced, and human errors are reduced.

The application discloses a method and device for determining anisotropy parameters in a stratum and a storage medium. The method comprises the following steps: determining a detection point; controlling an excitation point around the detection point to excite a wave, and obtaining a detection first-arrival time length corresponding to the excitation point at a predetermined receiving depth position below the detection point, wherein the receiving depth position is in a corresponding predetermined stratum, and the detection first-arrival time length is a time length required for a wave excited by the excitation point to reach the receiving depth position for the first time; determining a plurality of candidate anisotropy parameters; determining reflection wave time lengths corresponding to the plurality of candidate anisotropy parameters respectively in the receiving depth position based on a preset target direction angle; and determining a target anisotropy parameter of the predetermined stratum at the target direction angle based on the reflection wave time lengths corresponding to the plurality of candidate anisotropy parameters respectively and the detection first-arrival time length. The application solves the technical problem that the accuracy of anisotropy parameters in the related art is not ideal.

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.

This application provides a method and apparatus for detecting covert communication behavior, relating to the field of network security technology. On one hand, the method uses a dynamic time warping algorithm to determine the minimum cumulative distance between the packet length-timestamp sequence and the standard response traffic template sequence in the packet length dimension. This quantifies temporal misalignment differences, thus solving the problem of missed detection caused by the lack of temporal analysis capabilities in traditional methods. On the other hand, based on the arrival timestamp of the packet length-timestamp sequence, the method determines the differential entropy and the maximum time span of sudden events. The differential entropy can amplify the minute temporal fluctuations caused by the mechanical packet sending of tunnel traffic, while the maximum time span can identify deliberately lengthened idle periods in tunnel traffic. Combining these two methods can accurately capture gradual covert communication such as slow tunnels. Therefore, this method can improve the accuracy of detecting covert communication behavior.

Embodiments detect stops by an entity on a pre-planned trip including a plurality of stops and a planned sequence of stops, each stop including a geofence boundary. For each stop, embodiments add an arrival transition region extending inward from the geofence boundary. Embodiments receive a first geo-location message indicating a first location and corresponding to a first time for the entity and determine whether the first location falls within a first arrival transition region corresponding to a first stop having a first geofence boundary. When the first location falls within the first arrival transition region, embodiments wait for a predefined transitional time period. During the predefined transitional time period, when a second geo-location message is received indicating a second location inside the first geofence boundary and outside the first arrival transition region, the first time is determined to be an arrival time for the first stop.