19 results about "Airline operations" patented technology

The invention discloses an aviation fleet capacity and airline network matching method and system, and belongs to the technical field of airline operation management. The method comprises the following steps: 1) determining a basic set according to an airline network, and obtaining associated parameters; 2) constructing a two-stage model: firstly generating a transport capacity distribution scene of a multi-group model combination through integer linear programming, then inputting scene data and actual case data as decision units into an SBM-DEA model for solving, calculating a corresponding matching degree, and constructing a virtual boundary and a real boundary of an actual case; calculating the distance between the virtual boundary and the actual boundary of the actual case, and determining the difference between the virtual boundary and the actual boundary so as to determine a matching degree score; and 3) dynamically optimizing fleet configuration according to the matching degree of the aviation fleet capacity and the airline network and the matching degree score obtained by the two-stage optimization model.Real-time quantification of the matching degree is realized through the two-stage optimization model, the hysteresis defect of a traditional static method is overcome, and the utilization efficiency of fleet resources is remarkably improved.

A method and system for airline operation center (AOC) data communications are disclosed. The method comprises providing a computing device for use onboard an aircraft, with the computing device hosting at least one application configured to interact with at least one avionics processing unit onboard the aircraft. The method further comprises automatically retrieving, by the at least one application, AOC information for storage and processing on the computing device, and transmitting by the at least one application, the AOC information from the computing device to the at least one avionics processing unit. The AOC information is used by the at least one avionics processing unit to execute an AOC application hosted by the at least one avionics processing unit.

The invention discloses a team order processing method and device, a storage medium and electronic equipment, and the method is applied to the field of aviation information processing, and comprises the steps: obtaining a nesting mode and a seat borrowing mode when an airline company processes a team order, and determining the information of each to-be-sold shipping space; obtaining passenger information from the target order; calculating the average freight rate of each passenger in the target order according to a nesting mode, a seat borrowing mode, the information of each to-be-sold shipping space, the passenger type and the target number of each passenger type; and determining a target freight rate of each passenger according to the average freight rate of each passenger and a preset transaction amount of the target order, and processing the target order according to the target freight rate. According to the invention, the method solves a problem that the operation cost of an airline company is high because the flight transportation cost is increased or the number of seats is changed in the time period before the agent pays the fare when the airline company carries out the transaction according to the preset freight rate of the team travel in the related technology.

The application provides an airline route operation mode selection analysis method based on fuel price change, comprising: determining total profit of an airline operating a single route; based on profit maximization condition, analyzing influence of aircraft fuel price change on flight ticket price, fuel consumption, flight frequency, passenger load factor and flight seat number in the single route; based on profit maximization condition, analyzing differences between hub-and-spoke route network and point-to-point route network in fuel consumption, flight frequency and flight seat number; and determining influence of aircraft fuel price change on total profit of the airline operating HS route network or FC route network; the application is based on establishing a mathematical function expression about fuel price, can more intuitively carry out influence of fuel price change on airline service quality, aircraft design characteristics and route network structure, and provides a basis for airline decision-making.

Systems and methods of planning and scheduling resources of an airline include using machine learning models to generate custom behavioral characteristics for a plurality of operational components of the airline based on operations data. The custom behavioral characteristics are used to define inputs and outcomes in simulations of the operational components of the airline. The simulation outputs performance indicators and a feedback loop captures previously ignored interactions between the operational components of the airline based on the performance indicators and custom behavioral characteristics of inputs and outcomes corresponding to the plurality of operational components of the airline.

The invention relates to a method and a system for adjusting an airline operation strategy according to a civil aviation airline dynamic risk. The method comprises the following steps: calculating an abnormal confidence coefficient score according to an airline throughput; calculating a throughput deviation rate according to the route throughput and a preset throughput; calculating an environment risk factor according to the weather information and the season information; calculating a final risk value according to the abnormal confidence score, the throughput deviation rate and the environmental risk factor; adjusting a route operation strategy according to the final risk value; according to the method, the final risk value is calculated through factors such as the air line throughput, the weather information and the season information, automatic risk calculation can be realized, the air line operation risk can be obtained in time by considering various risk influence factors, and the risk early warning efficiency is improved; and an airline operation strategy is adjusted according to the final risk value, so that the airline operation loss is reduced, reference can be provided for aviation finance, and the investment risk of aviation finance is reduced.

The invention provides a cold and hot air route classification method and system, electronic equipment and a storage medium. The method comprises the steps of collecting original data of air routes, flights and passengers, performing statistics, summarization and anomaly detection on the collected original data, processing missing values and abnormal values in the original data, and constructing a complete and comprehensive data set; carrying out conversion, feature extraction and selection on the basis of statistical summarized data in the data set to obtain feature data, and inputting the feature data into a feature training model for training; inputting the trained feature data into a K-means clustering algorithm for clustering, and setting the value of K at the same time to obtain K different clusters; performing statistical feature and visual analysis on K different clusters obtained through clustering analysis to comprehensively evaluate the popularity degree and characteristics of each cluster so as to realize division of cold and hot air routes. According to the invention, automatic and accurate classification of cold and hot airlines can be effectively realized, and the operation management efficiency of an airline company is improved.

The present invention provides an image analysis and recognition system for aircraft component appearance defects. It is characterized by comprising: a video acquisition module that captures video images of the external structure of aircraft equipment components and transmits them in real time to an image processing engine; the image processing engine automatically and in real time identifies defects such as damage and dents in aircraft equipment components and their external structures in each frame of video image using a neural network image recognition and analysis algorithm, and transmits the defect recognition and analysis results to a data backend in real time; the data backend is used to match the defect recognition results found by the image processing engine with records in an aircraft defect index database, confirming and recording newly identified defects; the system implements real-time tracking and monitoring of aircraft component defect status, automatically learns and accumulates a defect feature database, accurately identifies and quickly verifies defects, and promotes the application and development of intelligent maintenance and inspection technologies in the field of airline operations and maintenance.

The invention discloses a flight plan changing method and device, equipment, a medium and a product, and relates to the technical field of flight plan management, and the method comprises the steps: adjusting an initial flight rule, and obtaining an adjusted flight rule; refreshing the flight plan based on the adjusted flight rule to obtain a to-be-effective flight plan; and performing flight plan change based on the to-be-effective flight plan. According to the method and the device, operation and control personnel of an airline company can specify the flight plan range needing to be refreshed and the flight rule category needing to be refreshed, so that the flight plan can be quickly changed, and the technical problem of low flight plan change efficiency in related technologies is solved.

The present invention relates to the field of computer technology applications, and in particular to a flight ring scheduling method that combines stopover slack time with flight delays, comprising: obtaining an initial task node set based on a pending flight task information table; obtaining an initial pending task node list based on a greedy algorithm; obtaining a target task node sequence set if the number of iterations does not reach a preset iteration threshold or the objective function value corresponding to the current node sequence set record set meets a convergence condition, and updating the current task node sequence set based on a sequence destruction method and a sequence reconstruction method to obtain an updated current task node sequence set, and use it as the current task node sequence set. The present invention enables the obtained target task node sequence set to have a minimum resource requirement value. In actual flight scheduling, it can reduce airline operating costs, take into account aircraft utilization and delays, and improve aircraft operating efficiency.

Addressing automated global inline recovery is challenging using state of the art approaches as it is non-trivial due to the complex dependencies between local actions and global effects. A method and system disclosed herein models inline recovery for intelligent airline operations as a stochastic optimization problem via Stochastic Minplus with State (SMS) agent that captures higher-order network-wide effects of airport-level local recovery actions. The system exploits domain knowledge encoded as a coordination graph to achieve scale for real-time decision making contribution: The MaxPlus algorithm from literature is modified to handle state-based coordination graphs with stochasticity and resource constraints. The heuristic for inline recovery targets aircraft delay and missed passenger (PAX) connections. Quick turn-around and flight delay is used as recovery actions. Heuristics are combined with simulation to incorporate uncertainty.

The invention relates to the field of computer technology application, in particular to a flight loop arrangement method combining station-crossing relaxation time and flight delay, which comprises the following steps: acquiring an initial task node set based on a flight task information table to be processed; based on a greedy algorithm, obtaining an initial to-be-processed task node list; if the number of iterations does not reach a preset iteration number threshold value or a target function value corresponding to the current node sequence set record set meets a convergence condition, obtaining a target task node sequence set, and updating the current task node sequence set based on a sequence destruction method and a sequence reconstruction method to obtain a target task node sequence set; and obtaining the updated current task node sequence set, and taking the updated current task node sequence set as the current task node sequence set. According to the invention, the obtained target task node sequence set has the minimum resource demand value. In actual flight orchestration, the operation cost of an airline company can be reduced, the aircraft utilization rate and delay are considered, and the aircraft operation efficiency is improved.

The invention provides an intelligent flight mode-based aviation revision standby and landing task management method and system. The aviation revision standby and landing task management method comprises the following steps of S1, starting an aviation revision standby and landing task; s2, requesting weather information, intelligence information and aviation revision standby suggestions of surrounding airports from a ground control unit and an airline operation and control department; s3, according to the weather information, the intelligence information and the navigation revision standby proposal of the surrounding airports, generating a standby landing field sorting table; s4, automatically generating a standby landing plan according to the standby landing field sorting table; and S5, reporting the flight state, the fuel quantity condition and the landing preparation plan to a ground control unit and an airline operation and control department, and updating the flight plan and executing landing preparation after approval. The method can be used for task management of civil aircrafts in a flight changing and landing preparing task scene, the ground-air coordination function is replaced by system automation, and the working steps of a flight unit are optimized.

Systems and methods are directed to perform operations to optimize the provision of user services. The operations can include obtaining user data for a user of a multimodal transportation service provider. The operations can include obtaining, based at least in part on the user data, aviation data for one or more aviation service providers, the one or more aviation service providers comprising at least one of a flight facility operator or an airline operator. The operations can include determining, based at least in part on the user data and the aviation data, one or more service actions, the one or more service actions comprising at least one of a multimodal transportation service itinerary adjustment, a security process modification, or a user service optimization. The operations can include performing the one or more service actions.

The invention relates to a civil aviation route income risk early warning method and system. The method comprises the following steps: acquiring operation financial data of a civil aviation route; generating a route income trend chart according to the operation financial data; constructing a block chain; storing the operation financial data on the block chain, and storing the airline income trend chart outside the block chain; constructing a risk identification model based on a computer vision identification method; inputting the airline income trend chart into a risk identification model for risk prediction to obtain an airline income risk identification result; judging whether investment risks exist or not according to the airline income risk identification result, and if yes, outputting income risk early warning information; if not, obtaining operation financial data on the block chain through the smart contract; according to the method, the external investor can preliminarily know the operation condition of the airline company through the disclosed operation trend chart, and the investment risk of the investor is reduced while the financial data security of the company is ensured.

The application discloses a civil aviation logistics intelligent loading system based on adaptive constraint relaxation, which comprises a data input and preprocessing module, a constraint multi-objective modeling module, a three-population collaborative evolution optimization module and a scheme output and application module. The data input and preprocessing module is used for extracting multi-source data required by a loading task from an airline operation database, arranging and converting the data into a system readable format, loading the data into a system cache area and completing data preparation of a model. The constraint multi-objective modeling module is used for constructing a constraint multi-objective optimization model of the civil aviation logistics intelligent loading based on the data output by the data input and preprocessing module. The three-population collaborative evolution optimization module adopts a three-population collaborative evolution algorithm ThcAp as a core solver. The application has more flexible and intelligent constraint processing, stronger multi-objective optimization capability, higher algorithm robustness, better scene adaptability, significantly improved loading efficiency and comprehensive benefits.

Addressing automated global inline recovery is challenging using state of the art approaches as it is non-trivial due to the complex dependencies between local actions and global effects. A method and system disclosed herein models inline recovery for intelligent airline operations as a stochastic optimization problem via Stochastic Minplus with State (SMS) agent that captures higher-order network-wide effects of airport-level local recovery actions. The system exploits domain knowledge encoded as a coordination graph to achieve scale for real-time decision making. contribution: The MaxPlus algorithm from literature is modified to handle state-based coordination graphs with stochasticity and resource constraints. The heuristic for inline recovery targets aircraft delay and missed passenger (PAX) connections. Quick turn-around and flight delay is used as recovery actions. Heuristics are combined with simulation to incorporate uncertainty.

The application relates to the field of civil aviation technology, and relates to a planned maintenance work cost evaluation method and system for a supplier SB / SIL. The evaluation method comprises the following steps: S1, establishing a basic cost motive identification database; S2, establishing an SB / SIL storage analysis database module; S3, calculating and measuring total cost; and S4, outputting a quantitative analysis suggestion report corresponding to whether an SB / SIL maintenance item is implemented. The evaluation system comprises a basic cost motive identification database module, an SB / SIL storage analysis database module, an algorithm matching accounting module and an evaluation report generation module. The planned maintenance work cost evaluation method and system for the supplier SB / SIL can improve the judgment accuracy of whether maintenance work is implemented by a planning maintenance engineering department of an airline, thereby being favorable to saving maintenance costs of the airline, avoiding safety hazards and improving the reliability and safety of airline operation.