Airport flight time toughness index calculation method

Abstract

The invention is suitable for the technical field of evaluation of external impact response capability of an airport, and provides an airport flight time toughness index calculation method, which comprises the following steps of: obtaining delay time sequences of a flight plan time in a certain season and an actual execution time in different days in a certain period of time; identifying the mode characteristics of the delay time sequence of a certain flight plan moment in the period of time; dividing the period of time of a certain flight plan moment into a plurality of periods, and identifying a flight delay normal stage, a delay increase stage, a stable delay stage and a delay decrease recovery stage of each period; calculating a normality index, a resistance index, a robustness index and a restorability index of a certain flight time in the period of time; and dynamically evaluating the toughness index of a certain flight time in the period of time. The method provides theoretical basis and decision reference for airport flight time delay prevention and control, recovery and toughness level improvement under different random interferences, thereby providing data support for reasonable planning and adjustment of flight time resources.

Description

Technical Field

[0001] The present invention belongs to the technical field of airport response capability assessment, and in particular, relates to a method for calculating an airport flight schedule resilience index. Background Art

[0002] The Airport Flight Schedule Resilience Index is a quantitative indicator used to evaluate the stability and resilience of an airport's flight schedule when facing external shocks (such as bad weather, emergencies, etc.). This index generally reflects the airport system's ability to resist disturbances, absorb disturbances, and quickly recover from interruptions to normal operation.

[0003] The components of the resilience index include: Vulnerability: refers to the speed and degree of decline in the function of an airport system when it is subjected to external shocks. For example, when encountering bad weather, the flight cancellation rate and delay rate of an airport can be used to measure its vulnerability. Robustness: represents the ability of an airport to maintain a basic level of operations in the face of shocks, which can be reflected by maintaining a high proportion of normal take-offs and landings during disasters; Resilience: refers to the speed at which an airport recovers from an inefficient operating state or a complete disruption to normal operating conditions. Resilience can be measured by the speed at which flights resume normal operations after a disaster.

[0004] The Airport Flight Schedule Resilience Index is an important tool for evaluating and improving the airport's ability to respond to emergencies. Through scientific and reasonable evaluation and analysis, it can help airport managers take effective measures to improve the airport's operating efficiency and service quality and ensure the safety and comfort of passengers. At present, the Airport Flight Schedule Resilience Index is a new concept and its calculation method needs to be explored urgently. Summary of the invention

[0005] The purpose of an embodiment of the present invention is to provide a method for calculating an airport flight schedule resilience index, aiming to solve the problems raised in the above-mentioned background technology.

[0006] The embodiment of the present invention is implemented as follows: a method for calculating an airport flight schedule resilience index comprises the following steps: Obtain the delay time series of the flight schedule in a certain season and the actual execution time on different days in a certain period of time; Based on big data technology, the delay time series of a flight schedule within the period of time is identified, including average value, maximum value, minimum value and change trend; Divide the time period of a flight's scheduled time into several cycles, and identify the normal flight delay phase, delay increase phase, stable delay phase, and delay reduction recovery phase of each cycle; Calculate the normality index, resistance index, robustness index, and recovery index of a certain flight schedule during this period; Dynamically evaluate the resilience index of a certain flight schedule during this period.

[0007] Preferably, the steps of obtaining the delay time series of the planned schedule of a certain season's flight and the actual execution time of different days during a certain period specifically include: Set a certain time period range , involving N days; Obtain the planned schedule of a certain season's flight on different dates within this time period range and the actual execution time ; Calculate the delay time of a certain season's flight on different dates within this time period range , and obtain its delay time series .

[0008] Preferably, the steps of identifying the pattern characteristics of the delay time series of a certain flight schedule during this period based on big data technology, including: average value, maximum value, minimum value, and change trend, specifically include: The average value of the delay time series of a certain flight during this period is , the maximum value is , the minimum value is ; Let the change trend of a certain flight plan on date be , be the change trend threshold of a certain flight plan on date . If , it is the stage of increasing delay; if , it is the stage of stable delay, , or the stage of normal delay, ; if , it is the stage of decreasing delay and recovery.

[0009] Preferably, the steps of dividing the period of a certain flight plan into several cycles and identifying the normal delay stage, increasing delay stage, stable delay stage, and decreasing delay and recovery stage of each cycle specifically include: For the delay time series of a certain flight plan within this time period range, according to the consecutive days on different dates of , determine M normal flight delay stages, i.e., , , ..., , ..., ; According to the start times of a certain flight plan in adjacent and normal flight delay stages, and determine the delay period, i.e., ; Extract the time series of the delay period of a certain flight plan , and calculate the average value , maximum value , minimum value ; According to the change trend at different dates , determine its normal flight delay stage , delay increase stage , stable delay stage , delay reduction and recovery stage .

[0010] Preferably, the steps of calculating the normality index, resistance index, robustness index, and recovery index of a certain flight moment during this period are specifically as follows: The normality index of a certain flight moment during this period is ; The resistance index of a certain flight moment during this period is ; The robustness index of a certain flight moment during this period is ; The recovery index of a certain flight moment during this period is .

[0011] Preferably, the steps of dynamically evaluating the resilience index of a certain flight moment during this period are specifically as follows: Calculate the time proportion of the normality index , resistance index , robustness index , and recovery index of a certain flight moment during this period; Obtain the resilience index of a certain flight moment during this period.

[0012] A method for calculating the resilience index of airport flight schedules provided by an embodiment of the present invention analyzes the planned delay time series pattern of flights at an airport, identifies its cycle and trend of change, and dynamically evaluates the resilience index of each airport flight schedule, including normality index, resistance index, robustness index, recovery index, etc., so as to provide a theoretical basis and decision-making reference for the prevention and control of airport flight schedule delays, recovery, and improvement of resilience level under different random interferences, and provide data support for the reasonable planning and adjustment of flight schedule resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It is a flowchart of a method for calculating the resilience index of airport flight schedules provided by an embodiment of the present invention; Figure 2 It is a specific flowchart of a method for calculating the resilience index of airport flight schedules provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0014] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0015] The following describes the specific implementation of the present invention in detail with reference to specific embodiments.

[0016] As Figure 1 shown, it is a flowchart of a method for calculating the resilience index of airport flight schedules provided by an embodiment of the present invention, including the following steps: S1. Obtain the delay time series of the planned flight schedules in a certain season and the actual execution times on different days within a certain period; S2. Based on big data technology, identify the pattern features of the delay time series of a certain flight's planned schedule within this period, including: average value, maximum value, minimum value, and trend of change; S3. Combine industry standards to divide this period of a certain flight's planned schedule into several cycles, and identify the normal stage of flight delay, the stage of increasing delay, the stable delay stage, and the stage of decreasing and recovering delay in each cycle; S4. Calculate the normality index, resistance index, robustness index, and recovery index of a certain flight schedule within this period; S5. Dynamically evaluate the resilience index of a certain flight schedule within this period.

[0017] As Figure 2 shown, it is a more specific flowchart of a method for calculating the resilience index of airport flight schedules provided by an embodiment of the present invention, including the following steps: S1. Data preparation, involving flight planned schedules, time period ranges, historical operation data, etc., including: S11. Set a time period range , involving N days; S12. Obtain the scheduled times of a certain seasonal flight on different dates within this time period range ; ( ) S13. Obtain the actual execution times of a certain seasonal flight on different dates within this time period range ; ( ) S2. Calculate the delay times of a certain seasonal flight on different dates within this time period range ; ( ) and obtain its delay time series accordingly ; S3. The average value of the delay time series of a certain flight within this time period is , the maximum value is , and the minimum value is ; ; S4. Let the change trend of a certain flight scheduled on date be , and be the change trend threshold of a certain flight scheduled on date . If , it is the stage of increasing delay; if , it is the stage of stable delay ( ) or the stage of normal delay ( ); if , it is the stage of decreasing delay and recovery; S5. For the delay time series of a certain flight scheduled within this time period range , according to the of different dates for consecutive days ), determine M stages of normal flight delay, that is , ,..., ,..., ; S6. Determine the delay cycle according to the start times and of the stages of normal flight delay for adjacent and flights, that is ; S7. Extract the delay cycle time series of a certain flight schedule , and calculate the average value of this time series , maximum value , minimum value ; S8. According to the change trend on different dates , determine its normal flight delay stage (i.e., , , ), the stage of increasing flight delay (i.e., , ), the stage of stable flight delay (i.e., , ), the stage of decreasing flight delay and recovery (i.e., , ); S9. The steps to calculate the normality index, resistance index, robustness index, and recovery index of a certain flight time during this period are as follows: The normality index of a certain flight time during this period is ; The resistance index of a certain flight time during this period is ; The robustness index of a certain flight time during this period is ; The recovery index of a certain flight time during this period is ; S10. Calculate the time proportion of the normality index, resistance index, robustness index, and recovery index of a certain flight time during this period , the time proportion of the resistance index , the time proportion of the robustness index , the time proportion of the recovery index ; S11. Obtain the resilience index of a certain flight time during this period .

[0018] Taking a certain flight CZ3546 from January 1, 2009 for 100 consecutive days as an example, obtain the scheduled time and the actual execution time on different dates ( ), as well as its delay time ( ). The delay time series during this period is ; Calculate this delay time series The average value , the maximum value , the minimum value ; Let , calculate the change trend of a certain flight plan on the date , such as , , , , , , , etc., as shown in Table 1 specifically: Table 1

[0019] Determine and as the normal stage, with a cycle of , extract the delay cycle time series of a certain flight plan , calculate the average value of this delay time series , , the maximum value , the minimum value ; Determine its normal stage of flight delay , the stage of increasing delay , the stable delay stage , the stage of decreasing delay and recovery ; Calculate the normality index of a certain flight moment during this period . The larger this value is, the higher the actual operation normality of the flight plan schedule; The resistance index of a certain flight moment during this period . The larger this value is, the stronger the interference of the actual operation of the flight plan schedule; The robustness index of a certain flight moment during this period . The larger this value is, the longer the abnormal operation time of the flight plan schedule; The recovery index of a certain flight moment during this period . The larger this value is, the longer the recovery cycle of the flight plan schedule; Calculate the time proportion of the normality index of a certain flight moment during this period , the time proportion of the resistance index , the time proportion of the robustness index , the time proportion of the recovery index ; Obtain the resilience index of a certain flight moment during this period = 0.12 + 0.025 + 0 + 0.8 = 0.925. The larger this value is, the stronger and more robust the ability of the flight schedule to recover under random interference is.

[0020] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for calculating the airport flight schedule resilience index, characterized in that: The following steps are involved: Obtain the delay time series of the flight schedule in a certain season and the actual execution time on different days in a certain period of time; Based on big data technology, the delay time series of a flight schedule within the period of time is identified, including average value, maximum value, minimum value and change trend; Divide the time period of a flight's scheduled time into several cycles, and identify the normal flight delay phase, delay increase phase, stable delay phase, and delay reduction recovery phase of each cycle; Calculate the normality index, resistance index, robustness index and recovery index of a flight schedule during that period; Dynamically evaluate the resilience index of a flight schedule during that period.

2. The method for calculating the airport flight schedule resilience index according to claim 1, characterized in that: The steps to obtain the delay time series of the flight schedule in a certain season and the actual execution time on different days in a certain period of time include: Set a time range , involving N days; Get the different dates of flights in a certain season within this period Planning time and actual execution time ; Calculate the number of flights in a certain season on different dates within this period Delay time , and thus obtain its delay time series .

3. The method for calculating the airport flight schedule resilience index according to claim 2, characterized in that: Based on big data technology, the pattern characteristics of the delay time series of a certain flight schedule within the period of time are identified, including the steps of average value, maximum value, minimum value and change trend, specifically including: The delay time series of a flight during this period The average for , maximum value for , minimum for ; Let a flight be scheduled on date Trends of change for , Plan a flight on a date If the change trend threshold of , then it is the delay increase stage; if , then it is the stable delay stage, , or delay the normal stage, ;like , then it is the delay reduction recovery stage.

4. The method for calculating the airport flight schedule resilience index according to claim 3, characterized in that: The steps of dividing the time period of a flight schedule into several cycles and identifying the normal flight delay phase, delay increase phase, stable delay phase, and delay reduction recovery phase of each cycle include: The delay time series of a flight plan within this time period , according to the continuous Different days of , , determine the normal stages of M flight delays, that is, , , ..., , ..., ; According to a flight plan, and The start time of the normal phase of flight delays and Determine the delay period, i.e. ; Extract the delay period time series of a flight plan , calculate the average value of the time series , maximum value , minimum ; according to On different dates Trends of change , determine the normal stage of flight delay , Delay increase stage , Stable delay stage , delay reduction recovery phase .

5. The method for calculating the airport flight schedule resilience index according to claim 4, characterized in that: The steps for calculating the normality index, resistance index, robustness index and recovery index of a flight schedule during the period are as follows: The normality index of a flight schedule during this period is ; The resistance index of a flight schedule during this period is ; The robustness index of a flight schedule during this period is ; The recovery index of a flight schedule during this period is .

6. The method for calculating the airport flight schedule resilience index according to claim 5, characterized in that: The steps to dynamically evaluate the resilience index of a flight schedule during this period are as follows: Calculate the normality index time ratio of a flight schedule during this period , resistance index time ratio , robustness index time ratio , recovery index time ratio ; Get the resilience index of a flight schedule during this period 。

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