42 results about "Flight schedule" patented technology

The invention provides a low-altitude service management system, and the system comprises a data interaction service module which is used for obtaining the flight data of a low-altitude aircraft; the flight management service module is used for receiving a flight request of a low-altitude aircraft reported by a user and generating a flight timetable based on a preset rule according to the flight request; the flight request comprises a flight airspace and a flight plan; the tracking service module is used for meshing the low-altitude geographic data into a plurality of first grids, the types of the first grids comprise airspace grids and obstacle grids, for each airspace grid, corresponding obstacle information is obtained through a grid search method, whether a collision risk exists or not is judged according to the flight data and the obstacle information, and if yes, the collision risk is judged; first alarm information is generated; and judging whether the low-altitude aircraft conforms to the flight airspace, the flight plan and the flight timetable or not according to the flight data, and generating second alarm information. The flight safety of the low-altitude aircraft is improved.

The present invention is applicable to the technical field of airport transfer hub capacity assessment and provides a multi-scale airport network flight transfer comprehensive index calculation method, which includes the following steps: data preparation, including airport network layout, airport layout, flight schedule, and transfer flight demand; calculation of the transfer flight proportion, feasible transfer number, average transfer waiting time, and transfer success rate of each airport; calculation of the average transfer flight proportion, average feasible transfer number, average transfer waiting time, and average transfer success rate of all airports and regions; calculation of the industry level of transfer flight proportion, feasible transfer number, average transfer waiting time, and transfer success rate of each airport and region; and calculation of the flight transfer index of each airport and region. The present invention can be used to dynamically evaluate the spatial distribution of flight time resource transfer supply and demand and its rationality, thereby providing data support for the rational planning and adjustment of flight time resources.

The application provides a low-altitude service management system, which comprises a data interaction service module, a flight data of a low-altitude aircraft is acquired by the data interaction service module; a flight management service module, a flight request of the low-altitude aircraft is accepted by the flight management service module, and a flight schedule is generated based on preset rules according to the flight request; the flight request comprises a flight airspace and a flight plan; a tracking service module, low-altitude geographic data is divided into a plurality of first grids by the tracking service module, the types of the first grids comprise airspace grids and obstacle grids, corresponding obstacle information is obtained by a grid search method for each airspace grid, and whether there is a collision risk is judged according to the flight data and the obstacle information, and first alarm information is generated; and whether the low-altitude aircraft conforms to the flight airspace, the flight plan and the flight schedule is judged according to the flight data, and second alarm information is generated. The application improves the safety of the flight of the low-altitude aircraft.

The application discloses an airport flight adjustment method based on an improved entropy gravity model, acquires multi-source data about an airport, constructs a relevant evaluation system of the airport, analyzes the weight through a TOPSIS algorithm, calculates the coupling degree between two airports in a region, obtains the distance between the airports based on the latitude and longitude coordinates of the airports, solves traffic generation and traffic attraction functions by using fuzzy compromise planning, calculates the entropy values of traffic generation, traffic attraction and airport distance by using an entropy weight method, and constructs an improved entropy gravity model, calculates the OD (Origin-Destination) quantity between the airports, obtains an ideal flight schedule in combination with flight passenger capacity and airport proportion, and adjusts original flights in combination with actual flight numbers. The application combines the coupling degree between the airports, enhances traffic impedance, and is more accurate in ideal OD quantity prediction. The ideal flight information obtained in combination with the flight passenger capacity and the airport proportion is suitable for route recommendation, is helpful to the development of small airports, and can also relieve the passenger carrying pressure of hub airports.

The invention discloses an aircraft maintenance task allocation and scheduling method based on a cutting strategy and time constraint, and relates to the technical field of aviation maintenance management and operation planning optimization. The method comprises the following steps: determining a maintenance opportunity that each airplane stays on the ground and meets a maintenance resource condition according to a known flight timetable; according to the technical scheme, a mathematical heuristic solving algorithm is designed, a hybrid algorithm combining a constructive heuristic algorithm and an accurate solving technology is developed, an infeasible solution is dynamically repaired through two core processes of resource monitoring and airworthiness monitoring, and an approximate optimal solution is quickly found in a large-range search space; a maintenance task is decomposed into feasible parts through a cutting strategy to adapt to a limited time box, and the problem of infeasibility caused by resource conflicts is solved; and meanwhile, solving is performed through a mathematical heuristic algorithm, so that the total cost including direct maintenance cost and extra waste cost caused by advanced maintenance is minimized while the calculation efficiency is ensured.

This invention discloses a strategic delay prediction method for airport flight schedules based on delay decomposition and combination, relating to the field of air traffic control and planning technology. It enables timely and effective prediction of arrival and departure delays for airport flights. The invention includes: a strategic delay prediction method for airport flight schedules based on delay decomposition and combination, used to obtain an airport capacity probability map using the airport flight schedule and historical flight operation data, and to obtain predicted values ​​for airport flight arrival and departure delays based on the airport flight schedule, airport operation mode modeling, and airport capacity probability map. This invention is applicable to the evaluation of the rationality and effectiveness of airport flight time / schedule arrangement during the strategic phase.

A tire inflation optimization device is provided that is configured to determine an optimal inflation pressure for a tire mounted on an aircraft. The device includes a memory and a controller. The memory stores information associating tire gas properties with aircraft scheduling parameters and a reference pressure for the tire. The controller is configured to receive future scheduling information indicative of a future flight schedule of the aircraft and to determine an optimal inflation pressure for the tire based on the received future scheduling information, the stored information associating tire gas properties with aircraft scheduling parameters, and the stored reference pressure. A method of determining an optimal inflation pressure for an aircraft tire is also provided, as is an aircraft including a tire in combination with the foregoing tire inflation optimization device.

A flight management apparatus includes a reception unit that receives, from a user's terminal, flight schedule information including user identification information for identifying the user, a flight path or a flight range in which a flight apparatus is scheduled to fly, and a flight schedule period in which the flight apparatus is scheduled to fly, an aircraft identification unit that identifies aircraft information related to the flight apparatus and associated with the user identification information, a carrier identification unit that identifies a communication carrier providing a communication service available to the flight apparatus on the basis of the aircraft information, a determination unit that determines whether the flight apparatus is communicable during flight using the communication service on the basis of the communication carrier and the flight path or the flight range, and a transmission unit that transmits a determination result to the user's terminal.

This invention relates to the field of aviation data processing technology, and in particular to a cache update method, storage medium, and device based on flight completeness. The method includes: responding to cache update trigger conditions, determining all flights on the target route and their corresponding airline interfaces; concurrently sending data requests and initiating a two-stage waiting period, with a first waiting period receiving a fast response and a second waiting period receiving a delayed response; verifying the returned data based on flight schedules and inventory status databases, and including the data in a cache candidate set; during the second waiting period, when receiving queries from high-priority users, bypassing the anti-penetration mechanism to retry interfaces that have not returned data and verifying them; after the waiting period ends, merging the candidate set data and writing it into the main cache to form the final flight list. This invention improves cache completeness and user query credibility by using a phased waiting period to accommodate interface response differences, a targeted retry mechanism to improve the response speed of urgent requests, and dual verification to ensure data accuracy.

This invention discloses a method and system for coordinated operation scheduling of aircraft and vehicles at airport surfaces. The method includes: collecting multi-source airport operation and support resource data to construct an input data set for coordinated operation of aircraft and vehicles; constructing a parking stand allocation model based on coordinated scheduling, comprehensively considering flight schedules, parking stand resources, and support service constraints; constructing initial and secondary vehicle scheduling models and designing dynamic adjustment strategies; using the NSGA-II algorithm with fusion local search to solve the parking stand allocation and initial vehicle scheduling problems, and using a large neighborhood search algorithm combined with simulated annealing to solve the secondary vehicle scheduling problem. This invention overcomes the limitations of traditional single optimization models, solves the problems of low resource utilization and conflicts caused by independent scheduling of aircraft and ground vehicles, and fills the gap in airport surface coordinated operation scheduling technology.

This application discloses a system and method for constructing an intelligent flight allocation model. The system for constructing an intelligent flight allocation model for an airport cluster includes: an acquisition unit for acquiring flight information, airport information, and corridor information of airport cluster N; a construction unit configured to construct an intelligent flight allocation model for the airport cluster based on the flight information, airport information, and corridor information of airport cluster N, wherein the intelligent flight allocation model includes an objective function, decision variables, and constraints; an optimization unit configured to optimize the intelligent flight allocation model for the airport cluster based on the constraints; and a solution unit configured to solve the optimized intelligent flight allocation model for the airport cluster to obtain the flight timetable for airport cluster N. This invention solves the flight timetable management problem from the perspective of mutual coordination, avoiding potential risks to on-time performance from the initial generation of flight timetables, and providing a scientific management solution for strategic flight timetable optimization for airport clusters.

The invention relates to an unmanned aerial vehicle airspace scheduling method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring flight data and environment data of an unmanned aerial vehicle; dividing the airspace into a core area, a buffer area and a free area based on the flight data; on the basis of shift data in the environment data and the flight data, predicting the meteorological condition of the core area in the target time period; when the weather condition is thunderstorm weather, adjusting the flight task of each unmanned aerial vehicle based on the flight data and the weather condition; and performing control scheduling on the unmanned aerial vehicle based on the adjusted flight task. Thus, the core area, the buffer area and the free area are dynamically divided based on the flight data, conflicts caused by disordered passing of multiple unmanned aerial vehicles in the core area are reduced, idle resources in the free area are activated, and the utilization rate of unmanned aerial vehicle resources is increased; moreover, thunderstorm weather is directionally predicted by focusing on the core area instead of whole-airspace generalization prediction, so that the calculation cost is reduced, and resources can be concentrated in the airspace which is most required to be guaranteed.

This invention discloses a flight schedule merging and compression method based on a schedule matrix. The method includes: S1, acquiring the original flight schedule data and grouping the data according to the same operational attributes; S2, constructing a two-dimensional schedule matrix for each group of flight schedule data based on the start and end date range, wherein the two dimensions of the schedule matrix correspond to consecutive natural weeks and Monday to Sunday within a natural week, respectively, and each cell in the schedule matrix represents the flight operation status for the corresponding date; S3, traversing the dimensions of the schedule matrix corresponding to natural weeks and comparing the flight operation status of adjacent natural weeks: if the natural weeks are consecutive and have the same schedule structure, they are merged into one schedule segment, and the start and end dates of the schedule segment are updated, retaining the original schedule structure; otherwise, they are divided into different schedule segments; S4, outputting all schedule segments to form a merged and compressed set of flight schedule records. This invention can reduce duplicate records and improve data processing efficiency.

The present application relates to the technical field of flight management, in particular to a kind of flight departure guarantee resource configuration scheduling optimization management method, comprising: according to the runway, run sequence and time interval corresponding to flight schedule list, flight schedule list is constructed in the form of front order and rear order with flight state diagram;With the maximum capacity and minimum adjustment time interval of each node in flight state diagram in unit time period as constraint condition, determine the transition cost of each state in flight state transition process, sort each flight into time-adjusted flight list with transition cost;Iterative solution is carried out using time-adjusted flight list, determine the optimal adjustment time interval in unit time, determine the adjustment quantity in unit time period according to adjustment time interval combined with time slot allocation;When adjustment quantity meets preset constraint rule, corresponding flight is combined with data, and the combined data is regarded as the output adjustment scheme;The efficiency and executability of flight scheduling processing are realized.

The invention belongs to the technical field of airport luggage systems, and particularly relates to a system and a method for dynamically adjusting early arrival resources and containerized resources. The system comprises a resource dynamic adjusting and planning system, wherein the resource dynamic adjusting and planning system is in communication connection with a real-time data collector, a data collection prediction model and a data solver; the data acquisition prediction model acquires data including flight data, luggage system data, early arrival resources, container resources and passenger and luggage data in an airport flight timetable, and after model construction is carried out, an early arrival resource allocation scheme and a container resource allocation scheme are obtained; and the resource dynamic adjustment planning system is used for receiving real-time latest flight dynamic and actual luggage flow data, comparing actual data with a model prediction scheme, continuously calibrating and optimizing model parameters by utilizing feedback circulation, and realizing rolling type dynamic planning of early arrival resources and container resources. The invention provides a system and a method for dynamically adjusting early arrival resources and containerized resources. The system and the method are used for dynamically adjusting the early arrival resources and the containerized resources.

A method and apparatus for collecting and processing flight fuel data, and a computer-readable medium. The method includes: acquiring flight schedule information of a flight from a flight list; determining and acquiring flight fuel data matching the flight schedule information of the flight; collecting, by a pre-constructed data collection component, the flight schedule information of the flight and a matched flight fuel data based on a set data collection protocol; and determining a fuel load planning center of gravity based on pre-configured fuel calculation parameters and the matched flight fuel data, to obtain a center of gravity index value of the flight.

The present disclosure relates to the technical field of voyage planning, and provides an aircraft flight interlining planning method, system, device and medium. The method comprises constructing a flight information graph using flight information of multiple cities. The flight information of each city a in the flight information graph comprises: city a, coordinates of city a, city b having a direct flight with city a, and average duration of a flight directly from city a to city b. Based on the information in the flight information graph, a heuristic function, a loss function and an expected loss function of an A* path planning algorithm are constructed, and path planning is performed using the A* path planning algorithm to output a planned path from a starting node to a target node. Based on the planned path, flights are matched to obtain a matching result and output. The present application can make full use of data in the flight schedule to make the planned flight interlining more scientific.

The application provides a tower flight command training scene generation method based on a training flight schedule, which can replace most of the manual input training scene process and improve the efficiency of producing flight command training scenes. It comprises the following steps: step one, obtaining single cell image data in the training flight schedule; step two, obtaining single flight plan line segment position information; step three, screening the information required for generating a training scene according to the single cell image data obtained in step one and the single flight plan line segment position information obtained in step two, and obtaining a screenshot list of required text information; step four, removing interference and error details according to the screenshot list of required text information obtained in step three, and obtaining a processed text information screenshot list; and step five, traversing each screenshot to extract the text therein and saving the text in corresponding line segment data information through a Tesseract character recognition framework according to the processed text information screenshot list obtained in step four.

The application discloses a kind of based on execution rate prediction's flight time whole life cycle dynamic management method, including constructing core table system and date interval week enumeration formula, according to rule split and calculate and process airline application information, process flight time cancellation, process flight time return and approved quota, process flight time return and approved quota, daily update flight actual operation execution state, season operation in real time and estimate and predict time execution rate, after season end, the actual execution rate of whole time is counted;The application solves the problems that the existing system lacks flight time whole life cycle closed-loop management and control capability, time execution rate monitoring lags behind, lacks pre-warning capability, breaks the limitation that traditional mode can only rely on manual checking to carry out post-execution rate analysis after season ends, builds whole-process execution rate prediction and early warning capability relying on real-time operation data, helps airlines to adjust operation strategy in time, reduces the idle and waste of flight time resources.

This invention relates to the field of air traffic management and intelligent control technology, specifically to an airport gate control system and method based on dynamic control of the airport surface; it includes the following steps: constructing a dynamic digital twin model capable of predicting future situations by real-time fusion of flight, surface surveillance, high-precision meteorological, and aircraft status data; predicting multi-dimensional operational conflicts, including weather mismatch and abnormal flight schedules, based on this model; intelligently generating and evaluating a coordinated control plan that integrates impact domain diffusion adjustment and fault-oriented safe gate strategies when receiving events such as sudden weather changes or aircraft malfunctions; parsing the optimal plan into differentiated instructions for roles such as control tower, apron, and ground services, and issuing them, tracking the execution status throughout the process; and finally, enabling the system rule base to self-optimize through a closed-loop feedback mechanism. This invention achieves efficient, coordinated, and early response to complex dynamic disturbances, improving the efficiency, safety, and resource utilization of airport ground operations.

The invention discloses an airport multi-class screen remote on-off control method, which comprises the following steps: S1, generating a screen on-off instruction through a control platform deployed on a central management server, the instruction type comprises a global one-key startup and shutdown instruction, a group startup and shutdown instruction classified according to screens or divided by physical regions, and a single-point startup and shutdown instruction for a single screen; s2, the control platform issues the startup and shutdown instructions to intelligent control terminals corresponding to the display screens through an airport local area network or the Internet of Things; s3, the intelligent control terminal receives and executes the instruction, and controls the on-off state of a relay switch module of the intelligent control terminal; the system has the beneficial effects that unified remote management of all display screens in an airport is realized through the central control platform, multiple control modes such as global control, grouping control and single-point control are supported, timed startup and shutdown tasks can be automatically executed according to a flight timetable, a traditional low-efficiency manual field operation mode is thoroughly changed, and the working efficiency is improved. And the refinement and automation of management are realized.

The invention provides a flight plan conflict detection method and device. The method comprises the following steps: obtaining a latest group version flight plan; and based on the latest group version flight plan, concurrently executing five types of conflict detection: red head moment conflict detection, group moment conflict detection, flight quantity newly-increased conflict detection, flight quantity reduced conflict detection and airline conflict detection, and generating a conflict detection result. And flight plan conflicts and conflict types can be rapidly and effectively detected.

The present invention discloses a method for predicting the delay distribution of a strategic flight schedule based on machine learning. The method comprises fitting the delay distribution of each flight using a normal distribution based on historical flight operation data, and splicing the obtained delay distribution into the strategic flight schedule to obtain a data set. Features used in the strategic flight schedule for predicting flight delay distribution are selected, and different types of features are encoded. A machine learning algorithm is used to learn and predict flight delay distribution information in the strategic flight schedule. For the prediction results, evaluation indicators are proposed to evaluate the prediction results of different machine learning algorithms. Finally, a machine learning algorithm with better performance is selected to predict the delay distribution of the strategic flight schedule. The method provides flight schedule coordinators with potential delay distribution information of the strategic schedule. When bottlenecks in airport on-time performance are discovered, actions are taken to reduce flight delays, thereby supporting strategic flight schedule performance evaluation and strategic flight schedule optimization.

The application discloses a civil aviation flight schedule configuration method for popular travel, which comprises the following steps: firstly, a multi-dimensional weight system for popular travel is determined, and the weight of each flight in the passenger type, airline type, route type and time type dimensions is calculated according to the flight schedule application data; then, the contribution degree of each flight to popular travel is evaluated by comprehensively considering the weight of each dimension, and the weight of each flight in the flight schedule offset is determined; next, a civil aviation flight schedule configuration model for popular travel is established, aiming at minimizing the total weight of the time offset and constraining the same; finally, the established flight schedule model is solved by using a Gurobi solver in a Python environment to obtain a civil aviation flight schedule table for popular travel. The application establishes a civil aviation flight schedule configuration model for popular travel, balances the popular travel demand, configuration efficiency and fairness, and improves the operability of the civil aviation flight schedule configuration.

The invention relates to the technical field of international logistics, and discloses an international logistics chain transportation method and system, and the method comprises the following steps: S1, collecting logistics environment information based on real-time environment monitoring data, including weather conditions, traffic flow, flight time, port conditions, current positions of goods, and states of transportation tools; s2, cleaning, standardizing and fusing the acquired environment data to obtain available real-time data; and S3, based on the multi-objective optimization model, comprehensively considering timeliness, cost, resource utilization rate and environmental influence, and carrying out link splitting and path selection optimization to obtain an optimal path selection scheme. Link splitting and path selection optimization are carried out based on the multi-objective optimization model, and then global balance among timeliness, transportation cost, resource utilization rate and environmental influence is realized, so that the problem that a path scheme does not have overall optimality due to the fact that most of traditional path design methods only pay attention to a single objective is solved.

This invention relates to the field of travel route planning technology, specifically to a method for extracting unstructured customer information from a travel platform. The invention first parses the current user's travel request text to construct a local route network; then, it queries the full static flight schedule for the target date, filtering out the planned flight volume for each directed edge; next, it reads the user's compliance requirements for the operating airlines, and, combined with the time planning rationality of the route, constructs a state transition matrix, performs graph iterative calculations, and obtains a transit accessibility score vector; further, based on the transit accessibility score vector, it determines whether to implement reachability interception; if no interception is implemented, it filters a set of candidate nodes, combines the user's preference instructions, generates a query instruction set, and calls the GDS interface to query, reducing the API call cost and operating expenses of the travel platform, effectively improving the query matching degree of complex itineraries, and enhancing user experience and enterprise management efficiency.

The application discloses an airport flight scheduling method and device based on big data, and a medium, to solve the technical problem that the existing airport flight scheduling is greatly different from the actual scheduling. It includes: determining the transit duration of each transfer of the to-be-scheduled flight of the flight schedule according to the historical scheduling information of the flight schedule, and determining the average duration corresponding to the to-be-scheduled flight according to the transit duration of each transfer, taking the average duration as the reference duration of the to-be-scheduled flight; determining the influence coefficient corresponding to each influence factor that has an influence on the to-be-scheduled flight according to the reference duration and the historical scheduling information, and determining the expected turnaround time corresponding to the to-be-scheduled flight according to each influence coefficient and the reference duration; arranging the flight time corresponding to all to-be-scheduled flights of the day based on the expected turnaround time corresponding to all to-be-scheduled flights of the day, and scheduling the flight schedule of the to-be-scheduled flight in the airport according to the arranged flight time.

The invention discloses a flight timetable optimization method and device, electronic equipment and a storage medium, and relates to the technical field of aviation, and the method comprises the steps: obtaining candidate flight time pairs of all airlines; determining a candidate scheme according to the candidate flight time pair; the candidate schemes comprise flight time pairs and candidate flight time pairs configured for each flight route in the historical flight time table; for each candidate scheme, calculating a first revenue according to the revenue of each route in the candidate scheme; wherein the income of each air route is obtained based on prediction of a first model, and the first model is further used for predicting the income of the air route at least according to the flight time pair and the candidate flight time pair; and determining a target scheme according to the first income of each candidate scheme. On the basis, the operation efficiency of the airline company can be improved, the aviation resource configuration is optimized, and the income of the airline company is maximized.

A system (100) for agent-based detection of semantic variations in the life cycle of documents, consisting of: a data acquisition module configured to collect real-time and historical data relating to flight operations, weather conditions, air traffic, airport operations and airline resources; a data processing module configured to normalize, validate, and preprocess the collected data; an artificial intelligence-based analysis engine configured to analyze the processed data and generate predictions of potential flight disruptions, including at least delays, cancellations, diversions, or flight schedule changes; and a communication and integration module configured to transmit the forecast results to a mobile application of the airline, the system (100) enables proactive notification and management of flight disruptions before they occur.

This application provides a flight schedule publishing method and electronic device, relating to the field of message processing technology. The method includes: acquiring a flight change message, the flight change message including a change type identifier for the corresponding flight; based on the change type identifier, converting the flight change message into a standardized message using pre-processing rules; sending the standardized message to a flight schedule processing system for flight change, and receiving change result information from the flight schedule processing system; and adjusting the changed flight status data using post-processing rules based on the change type identifier and change result information to achieve flight schedule publishing. This application embodiment can be used in the field of aviation message processing, enabling differentiated and precise message processing and data adjustment for different flight change types, achieving precision and efficiency in the flight schedule publishing process.