Method and system for determining minimum value of flight segment running time

Abstract

The present invention discloses a method and system for determining the minimum value of the flight segment operation time, belonging to the technical field of new concepts and new standards for flight segment operation time, including: obtaining historical flight operation data; performing data preprocessing on the historical flight operation data to obtain the flight sample mean and the flight sample standard deviation; calculating the minimum value of the flight segment operation time based on the flight sample mean and the flight sample standard deviation; proposing a new concept and new method to determine the minimum value of the flight segment operation time, obtaining a new standard, facilitating the review of the rationality of flight segment connection in the flight plan arrangement of airlines, and being able to be used to guide flight plan arrangement and operation quality analysis; applying the idea of statistics to the determination of the minimum value of the flight segment operation time, being able to solve the problem of early arrival of current flights, further presenting data facts clearly, discovering the law of early arrival of flights, providing ideas and methods for flight plan arrangement work, and providing decision support for pre-flight plan management personnel.

Description

Technical Field

[0001] The present invention relates to a method and system for determining the minimum value of flight segment operation time, and belongs to the technical field of new concepts and new standards for flight segment operation time. Background Art

[0002] With the rapid development of the global economy and tourism, the air transportation industry has advanced by leaps and bounds, playing an extremely important role in driving the world economy and promoting the development of tourism, and enabling interconnection between different continents, countries, and cities. However, under this background, the air traffic flow has increased, flight conflicts have occurred frequently, and abnormal flight phenomena such as flights arriving at the airport ahead of schedule, flights arriving at the airport late, flights departing from the airport ahead of schedule, and flights departing from the airport late have become increasingly obvious. These abnormal flight phenomena will affect the runway and apron allocation plans. At a certain stage, it will cause the airport ground operation personnel and vehicles to be frequently mobilized temporarily, disrupting the operation order of personnel and vehicles, reducing the airport operation efficiency, increasing safety risks, and lowering passenger satisfaction. Therefore, it is necessary to solve the above problems at the root.

[0003] In recent years, the Civil Aviation Administration of China has attached great importance to the research work on the formulation of flight segment operation time standards, and regarded it as an important factor for the safe, efficient, and punctual operation of civil aviation flights. It can be seen that it is very important to formulate reasonable flight segment operation time standards. As an important reference basis in the process of civil aviation flight plan preparation, the formulation of civil aviation flight segment operation time standards is extremely urgent. Summary of the Invention

[0004] The purpose of the present invention is to provide a method and system for determining the minimum value of flight segment operation time, so as to solve the problems of low airport operation efficiency, high safety risks, and low passenger satisfaction in the prior art.

[0005] To achieve the above purpose, the present invention is implemented by adopting the following technical solutions:

[0006] In the first aspect, the present invention provides a method for determining the minimum value of flight segment operation time, including:

[0007] Obtain historical flight operation data;

[0008] Perform data preprocessing on the historical flight operation data to obtain the flight sample mean and the flight sample standard deviation;

[0009] Calculate the minimum value of the flight segment operation time based on the flight sample mean and the flight sample standard deviation.

[0010] Combined with the first aspect, further, the historical flight operation data is obtained through the following method: The historical flight operation data is collected by using the method of project research, and the historical flight operation data is collected by using the method of optical disc or encrypted email during the project research process.

[0011] In combination with the first aspect, further, the collection period of the historical flight operation data includes at least the flight operation data of the complete summer and autumn and winter and spring flight seasons within one year.

[0012] In combination with the first aspect, further, the data preprocessing includes quantity statistics, valid data statistics, and field parsing;

[0013] The quantity statistics is carried out according to months, flight seasons, and the number of records;

[0014] The valid data are the data that simultaneously meet the conditions that the flight date is not empty, the planned aircraft type is not empty, the planned departure airport is the same as the actual departure airport, the planned landing airport is the same as the actual landing airport, the actual departure airport and the actual landing airport are not the same, the actual push-back time is not empty, and the actual taxi-in time is not empty;

[0015] The field parsing includes selecting key fields to conduct statistical analysis on the historical flight operation data.

[0016] In combination with the first aspect, further, the data preprocessing also includes data cleaning, and the data cleaning includes data missing value elimination and logical error correction;

[0017] The data missing value elimination is to eliminate the data with missing key fields that cannot be repaired or corrected;

[0018] The logical error correction is to supplement or eliminate the data that does not conform to the actual operation situation.

[0019] In combination with the first aspect, further, the data preprocessing also includes the steps of calculating the flight sample mean and the flight sample standard deviation.

[0020] In combination with the first aspect, further, the minimum value of the flight segment operation time is:

[0021]

[0022] where, is the flight sample mean, and s is the flight sample standard deviation.

[0023] In combination with the first aspect, further, the minimum value of the flight segment operation time is:

[0024]

[0025] where, is the flight sample mean, and s is the flight sample standard deviation.

[0026] In combination with the first aspect, further, it also includes flight segment revision, and the flight segment revision includes domestic flight segment revision and international flight segment revision.

[0027] In a second aspect, the present invention further provides a system for determining the minimum value of the flight segment operation time, including:

[0028] A data acquisition module: configured to acquire historical flight operation data;

[0029] A data preprocessing module: configured to perform data preprocessing on the historical flight operation data to obtain the flight sample mean and the flight sample standard deviation;

[0030] A flight segment operation time minimum value calculation module: configured to calculate the minimum value of the flight segment operation time according to the flight sample mean and the flight sample standard deviation.

[0031] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0032] The method and system for determining the minimum value of the flight segment operation time provided by the present invention calculate the minimum value of the flight segment operation time through the flight sample mean and the flight sample standard deviation, propose a new concept and method to determine the minimum value of the flight segment operation time, obtain a new standard, facilitate the review of the rationality of flight segment connection in the flight plan arrangement of airlines, and can be used to guide flight plan arrangement and operation quality analysis; applying the idea of statistics to the determination of the minimum value of the flight segment operation time can solve the problem of early arrival of current flights, further clarify the data facts, discover the law of early arrival of flights, provide ideas and methods for flight plan arrangement work, and provide decision-making support for pre-flight plan managers. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 is one of the flowcharts of a method for determining the minimum value of the flight segment operation time provided by an embodiment of the present invention;

[0034] Figure 2 is a schematic diagram of the confidence interval of flight samples provided by an embodiment of the present invention;

[0035] Figure 3 is the second flowchart of a method for determining the minimum value of the flight segment operation time provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0036] The present invention will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention and should not be used to limit the protection scope of the present invention.

[0037] Embodiment 1

[0038] As Figure 1 and Figure 3 shown, a method for determining the minimum value of the flight segment operation time provided by an embodiment of the present invention includes:

[0039] S1. Obtain historical flight operation data.

[0040] The method for collecting historical flight operation data mainly adopts the method of project research. Since some sensitive information is involved, confidentiality should be noted during the data collection process, and it is usually obtained by using optical discs or encrypted emails.

[0041] Moreover, in order to ensure the effectiveness and continuity of the data, the collection period usually needs to include the flight operation data of the complete summer and autumn, winter and spring flight seasons in a certain year.

[0042] S2. Perform data preprocessing on the historical flight operation data to obtain the flight sample mean and the flight sample standard deviation.

[0043] Data preprocessing includes quantity statistics, valid data statistics, and field parsing.

[0044] Quantity statistics: The obtained historical flight operation data is composed of Access tables divided by natural months, and quantity statistics are performed according to the corresponding months, flight seasons, and number of records.

[0045] Valid data statistics: The obtained historical flight operation data includes valid flight operation data and invalid flight operation data; the definition of valid flight operation data is: simultaneously satisfying that the flight date (FLTSDATE) is not empty, the planned aircraft type (AIRCFAFT_TYPE) is not empty, the planned departure airport (S_DEPAP) and the actual departure airport (R_DEPAP) are the same, the planned arrival airport (S_ARRAP) and the actual arrival airport (R_ARRAP) are the same, the actual departure airport (R_DEPAP) and the actual arrival airport (R_ARRAP) are different, the actual push-back time (R_OUTTIME) is not empty, and the actual taxi-in time (R_INNTIME) is not empty.

[0046] Filter out the valid flight operation data, perform statistical analysis on it, and respectively perform statistics on the number of historical flight records, the number of valid records, and the valid ratio according to natural months. Combine the current impact of the epidemic to analyze the situation of historical flight operation data.

[0047] Field parsing: In order to facilitate the calculation of the flight segment operation time, key fields are selected to analyze each Access table, and the list of involved airlines is sorted out.

[0048] In order to achieve data sharing, reduce data redundancy, increase data independence, and facilitate data recovery, SQL Server is used to store and calculate flight operation data.

[0049] Use R language for data operations, including data calculation and statistical analysis; for the elimination of unqualified data and the supplementation of some information, data cleaning is carried out. The cleaning work mainly includes the elimination of data missing and the correction of logical errors. The elimination of data missing is to eliminate the data with missing key fields that cannot be repaired or corrected. The possible situations may include the missing or unrecognizable model data (FLIGHTID), the missing actual push-out time (R_OUTTIME), and the missing actual pull-in time (R_INNTIME); the correction of logical errors refers to the supplementation or elimination of the data that does not conform to the actual operation situation to ensure its authenticity. The possible situations may include the same actual departure airport (R_DEPAP) and actual arrival airport (R_ARRAP), different planned arrival airport (S_ARRAP) and actual arrival airport (R_ARRAP), different planned departure airport (S_DEPAP) and actual departure airport (R_DEPAP), and the actual pull-in time (R_INNTIME) being earlier than the actual push-out time (R_OUTTIME).

[0050] Use SQL Server to conduct statistics on the obtained flight operation data, analyze the situation of the original flight records, the situation of the valid flight records, and the proportion of the valid flight records, and conduct statistics according to the flight seasons respectively; through the form of drawing the composition diagrams of the original flight operation data and the valid flight operation data, conduct data screening analysis; add the model conditions to conduct statistics on the number of valid flight segments in the summer and autumn, and winter and spring flight seasons.

[0051] Data preprocessing also includes the steps of calculating the flight sample mean and the flight sample standard deviation.

[0052] The empirical rule can be used to describe the data set. The empirical rule is the result of the practical experience obtained by researchers in many fields through observing many different types of real data sets. That is, if a data set has an approximately mound-shaped symmetric distribution, the following empirical rule can be used to describe the data set:

[0053] 1) Approximately 68% of the flight operation data is within 1 standard deviation of the mean (that is, for the flight sample data within the range, and for the flight population data within the range of μ + σ);

[0054] 2) Approximately 95% of the flight operation data is within 2 standard deviations of the mean (that is, for the flight sample data within the range, and for the flight population data within the range of μ + 2σ);

[0055] 3) Almost all of the flight operation data is within 3 standard deviations of the mean (that is, for the flight sample data within the range, and for the flight population data within the range of μ + 3σ).

[0056] The Chebyshev's rule can be used to describe a data set. The Chebyshev's rule was proven by the Russian mathematician Pafnuty L. Chebyshev and can be applied to any data set, regardless of the frequency distribution of the data. The specific content is as follows:

[0057] 1) There may be very few flight operation data falling within 1 standard deviation of the mean, that is, for the flight sample data in the interval range, and for the overall flight data in the interval (μ + σ);

[0058] 2) At least of the flight operation data falls within 2 standard deviations of the mean, that is, for the flight sample data in the interval range, and for the overall flight data in the interval (μ + 2σ);

[0059] 3) At least of the flight operation data falls within 3 standard deviations of the mean, that is, for the flight sample data in the interval range, and for the overall flight data in the interval (μ + 3σ);

[0060] 4) Generally, for any number k greater than 1, at least of the flight operation data falls within k standard deviations of the mean, that is, for the flight sample data in the interval range, and for the overall population in the interval (μ ± kσ).

[0061] represents the flight sample mean, s represents the flight sample standard deviation, μ represents the overall flight mean, and σ represents the overall flight standard deviation.

[0062] When making statistical inferences about the flight segment operation time, the flight sample mean can be used as a point estimate of the overall flight mean μ, but the probability properties of the flight segment operation time still cannot be accurately obtained; The central limit theorem states that when the sample is large enough (n ≥ 30), the sampling distribution of the flight sample mean is approximately a normal distribution; At this time, combined with the concept of the confidence interval, the random interval of the overall flight mean can be inferred as follows:

[0063] The large sample (1 - α) 100% confidence interval for the overall flight mean μ is:

[0064]

[0065] z α / 2 is the z value for which the area to its right is α / 2, σ represents the standard deviation of the sampling population, and n is the sample size. represents the sample mean. When the value of σ is unknown (which is usually the case), the sample standard deviation s can be used to approximately replace σ in the confidence interval formula, and the approximation is generally quite satisfactory when n ≥ 30.

[0066] 1 - α is called the coverage of the confidence interval. Usually, a 95% confidence interval is adopted, and the corresponding α = 0.05, as Figure 2 shown.

[0067] S3. Calculate the minimum value of the segment running time based on the flight sample mean and the flight sample standard deviation.

[0068] Combining the random characteristics of the segment running time during the actual operation of the flight and the standard methods commonly used in engineering science, select as the first scheme for determining the minimum value of the segment running time.

[0069] Considering the random characteristics of the mean value of the segment running time during the actual operation of the flight and the standard methods commonly used in engineering science, the present invention decides to calculate the 95% confidence interval of the mean value of the segment running time and take as the second scheme for determining the minimum value of the segment running time.

[0070] As Figure 3 shown, a method for determining the minimum value of the segment running time provided by an embodiment of the present invention further includes segment revision, and the segment revision includes domestic segment revision and international segment revision.

[0071] Perform domestic segment revision on the flight operation data:

[0072] In the analysis of domestic segment operation data, analyze the domestic segment overview, and conduct classification and summary by month, by flight season, and by aircraft type; analyze the airline segment operation data, focusing on the flight segments of the three major airlines; analyze the airport segment operation data, count the number of domestic segments of each airport annually, and calculate the average taxi-in time of the coordinated airport average taxi-out time and average flight time The calculation formulas are as follows:

[0073] r1 = R_DEPTIME - R_INNTIME,

[0074] r2 = R_OUTTIME - R_ARRTIME,

[0075]

[0076]

[0077] r = R_ARRTIME - R_DEPTIME,

[0078]

[0079] wherein, r1 is the taxi-in time, r2 is the taxi-out time, r is the average flight time, r1', r1'', r1'''... r1 n are respectively the taxi-in times of each flight segment, are respectively the taxi-out times of each flight segment, is the average taxi-in time, is the average taxi-out time, r is the flight time, r', r'', r'''... r n are respectively the flight times of each flight segment, is the average flight time.

[0080] In order to study the minimum standard of flight segment operation time, it is necessary to determine the domestic flight segments to be announced and analyze them:

[0081] 1) Compare the flight segments in the domestic flight standard flight segment operation time announced in the most recent year with the flight segments statistically obtained from the domestic valid flight operation data collected by the present invention, and analyze the number of dormant, already flown, and newly added flight segments;

[0082] 2) Divide the domestic valid flight operation data collected by the present invention according to years and flight seasons to obtain the distribution of flight segment comparison situations in each flight season;

[0083] 3) Combine the international environment, actual operation conditions, etc. during the research period to determine the domestic flight segments to be announced and their quantities for this revision.

[0084] It is divided into the analysis of the minimum result of domestic flight segment operation time and the verification of the minimum result of domestic flight segment operation time:

[0085] 1) According to the domestic flight segments to be announced, analyze their results, and statistically count the sample flight coverage rate according to intervals. The calculation formula for the sample flight coverage rate is as follows:

[0086]

[0087] wherein, α is the sample flight coverage rate, m is the number of sample flights in the corresponding scheme, and M is the total number of sample flights.

[0088] Compare and analyze the number of flight segments covered by Scheme 1 and Scheme 2 to obtain the statistical table of sample flight coverage;

[0089] By comprehensively comparing the two solutions, the sample flight coverage rules of Solution 1 and Solution 2 are found, and it is recommended that the aviation authority can make a choice in combination with the actual operation situation of the airline when announcing the minimum standard of flight segment operation time.

[0090] 2) To verify the minimum value results of domestic flight segment operation time, historical collected data is used for verification, and the sample coverage rate of the minimum value of flight segment operation time and the corresponding number of flight segments are analyzed.

[0091] 3) Usually, the flight segment operation time is in 5 - minute time slices. Therefore, the rounding situation of the minimum value of domestic flight segment operation time is analyzed. After rounding up the calculated minimum value of flight segment operation time to the nearest 5, the difference between the minimum value of flight segment operation time and the rounded - up minimum value of flight segment operation time is calculated, and the integer - part - only analysis of the difference after discarding the decimal point is carried out. The corresponding flight segments and their proportion situations are counted according to the differences of 0, 1, 2, 3, 4, and the coverage of the flight segments to be announced is analyzed to see if it meets the requirements of the minimum value of domestic flight segment operation time.

[0092] Revise the international flight segment for flight operation data:

[0093] In the analysis of international flight segment operation data, the general situation of international flight segments is analyzed, and classified summaries are made by month, flight season, and aircraft type respectively; the flight segment operation data of airlines are analyzed, with a focus on the proportion of international flight segments operated by domestic airlines; the flight segment operation data of airports are analyzed, and the number of international flight segments of domestic airports is counted annually; the geographical locations of international flight segments are statistically analyzed from three aspects: continent, country, and city, and the distribution of the main international flight segments in China is counted.

[0094] To study the minimum standard of flight segment operation time, it is necessary to determine the internationally proposed flight segments to be announced and analyze them:

[0095] 1) Compare the flight segments in the standard flight segment operation time of international flights announced in the most recent year with the flight segments statistically obtained from the international valid flight operation data collected in this invention, and analyze the number of dormant, already - flown, and newly - added flight segments.

[0096] 2) For the international valid flight operation data collected in this invention, divide it by year and flight season to obtain the distribution of flight segment comparison situations in each flight season.

[0097] 3) Combining the international environment, actual operation situation, etc. during the research period, determine the internationally proposed flight segments to be revised this time and their quantities.

[0098] It is divided into the analysis of the minimum value result of international flight segment operation time and the verification of the minimum value result of international flight segment operation time:

[0099] 1) Analyze the results according to the internationally proposed published flight segments, and statistically count the sample flight coverage rate by intervals. The formula for the sample flight coverage rate is as follows:

[0100]

[0101] Among them, μ is the sample flight coverage rate, q is the number of sample flights of the corresponding plan, and Q is the total number of sample flights.

[0102] Compare and analyze the number of covered flight segments of Plan 1 and Plan 2 to obtain a statistical table of sample flight coverage;

[0103] Comprehensively compare the two plans, discover the sample flight coverage rules of Plan 1 and Plan 2, and suggest that the aviation authority can make a choice in combination with the actual operation situation of the airline when announcing the minimum standard of flight segment operation time.

[0104] 2) To verify the results of the minimum value of the international flight segment operation time, use historical collected data for verification, and analyze the sample coverage rate of the minimum value of the flight segment operation time and the corresponding number of flight segments;

[0105] 3) Usually, the flight segment operation time is in 5-minute time slices. Therefore, analyze the rounding situation of the minimum value of the international flight segment operation time; after rounding up the calculated minimum value of the flight segment operation time to the nearest 5, calculate the difference between the minimum value of the flight segment operation time and the rounded-up minimum value of the flight segment operation time, and perform integer analysis after discarding the decimal point of the difference. Statistically count the corresponding flight segments and their proportions according to the differences of 0, 1, 2, 3, and 4, and analyze whether the coverage of the proposed published flight segments meets the requirements of the minimum value of the international flight segment operation time.

[0106] Comparison between the value announced by the aviation authority and the minimum value of the flight segment operation time:

[0107] Compare the value announced by the aviation authority with the minimum value of the flight segment operation time, analyze the matching data situation, statistically count the value announced by the aviation authority in three cases: greater than the minimum value of the flight segment operation time, less than the minimum value of the flight segment operation time, and equal to the minimum value of the flight segment operation time, and analyze the number of flight segments and their proportions in the corresponding cases to further illustrate the rationality and effectiveness of the method proposed in the present invention.

[0108] Compare the value announced by the aviation authority with the minimum value of the flight segment operation time, analyze the unmatched data situation, and statistically count from the perspectives of flight season, aircraft type, and flight time respectively.

[0109] Comparison between the value announced by the aviation authority and the latest actual operation data:

[0110] Compare the announced values of the parties to the latest actual operating data of the research year. Summarize the distribution according to the summer and autumn flight schedules. Count the number and proportion of flight segments with flight segment operation time < the minimum flight segment operation time, and the number and proportion of flight segments with flight segment operation time ≥ the minimum flight segment operation time, and find out its distribution law.

[0111] Compare the announced values of the parties to the latest actual operating data of the research year. Summarize the distribution according to the winter and spring flight schedules. Count the number and proportion of flight segments with flight segment operation time < the minimum flight segment operation time, and the number and proportion of flight segments with flight segment operation time ≥ the minimum flight segment operation time, and find out its distribution law.

[0112] Historical effect test based on the minimum flight segment operation time standard:

[0113] For domestic and international flight segments respectively, count the corresponding number of flight segments according to the proportion of sample flights meeting the minimum flight segment operation time standard. The proportion is counted in six cases: 100%, [95%, 100%), [90%, 95%), [85%, 90%), [80%, 85%), <80%, and count the proportion of the number of flight segments in these six cases to the total number of flight segments respectively.

[0114] Analysis of the situation based on the minimum flight segment operation time standard:

[0115] Analyze the overall situation of the minimum flight segment operation time standard. Combining the actual situation of the collected data, divide the flight segment sample data into intervals of ≥3500, [2500, 3500), [1500, 2500), [500, 1500), [400, 500), [300, 400), [200, 300), [100, 200), [0, 100), and count the number of flight segments in each interval, the arithmetic mean of the minimum flight segment operation time coverage rate, and the weighted average of the minimum flight segment operation time coverage rate.

[0116] Let w = [w1, w2, w3,... w n ,

[0117]

[0118] Among them, τ is the arithmetic mean of the minimum flight segment operation time coverage rate, and w = [w1, w2, w3,... w n is the sample of the minimum flight segment operation time.

[0119] κ = [κ1, κ2, κ3,..., κ n ,

[0120]

[0121] Among them, γ is the weighted average of the minimum coverage rate of the flight segment operation time, and κ = [κ1, κ2, κ3,..., κ n is the weight, and the weight can be calculated according to the number of flight segments in the corresponding interval.

[0122] Analyze the sample coverage rate of the minimum standard of the flight segment operation time, and select representative flight segments for analysis. The representative flight segments are obtained by sorting the city pairs according to the number of effective flight samples, and selecting the flight segments of the top 50, top 100, and top 200 city pairs with effective flight samples for detailed analysis; based on the proposed minimum standard of the flight segment operation time, perform visual analysis on the number of samples that meet the minimum standard of the flight segment operation time and the number of samples that do not meet the minimum standard of the flight segment operation time respectively.

[0123] Based on the statistics of the minimum value and standard value of the operation time of each flight segment proposed, perform visual analysis on the deviation situation (time reduction), and respectively count the distribution of flight segments of the top 50, top 100, and top 200 city pairs according to the flight season, aircraft type, and time reduction.

[0124] Embodiment 2

[0125] A system for determining the minimum value of the flight segment operation time provided by an embodiment of the present invention is characterized by including:

[0126] Data acquisition module: used to acquire historical flight operation data;

[0127] Data preprocessing module: used to perform data preprocessing on historical flight operation data to obtain the flight sample mean and flight sample standard deviation;

[0128] Flight segment operation time minimum value calculation module: used to calculate the minimum value of the flight segment operation time according to the flight sample mean and flight sample standard deviation.

[0129] Those skilled in the art should understand that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0130] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing device produce means for implementing the functions specified in one or more of the flows Figure 1 one or more of the flows and / or blocks Figure 1 or means for implementing the functions specified in one or more of the blocks.

[0131] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to operate in a specific manner, such that the instructions stored in the computer-readable memory produce a manufactured article including instruction means for implementing the functions specified in one or more of the flows Figure 1 one or more of the flows and / or blocks Figure 1 or means for implementing the functions specified in one or more of the blocks.

[0132] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more of the flows Figure 1 one or more of the flows and / or blocks Figure 1 or means for implementing the functions specified in one or more of the blocks.

[0133] The above is only the preferred embodiment of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the technical principle of the present invention, several improvements and modifications can be made, and these improvements and modifications should also be regarded as the protection scope of the present invention.

Claims

1. A method for determining the minimum value of the flight segment operation time, characterized in that, Including: Obtain historical flight operation data; Use SQL Server to perform data preprocessing on the historical flight operation data to obtain the flight sample mean and the flight sample standard deviation; Calculate the minimum value of the flight segment operation time based on the flight sample mean and the flight sample standard deviation; The data preprocessing includes quantity statistics, valid data statistics, and field parsing; The quantity statistics is performed according to months, flight seasons, and the number of records; The valid data are data that simultaneously meet the conditions that the flight date is not empty, the planned aircraft type is not empty, the planned departure airport is the same as the actual departure airport, the planned landing airport is the same as the actual landing airport, the actual departure airport is different from the actual landing airport, the actual push-back time is not empty, and the actual taxi-in time is not empty; The field parsing includes selecting key fields to perform statistical analysis on the historical flight operation data; The data preprocessing further includes data cleaning, and the data cleaning includes data missing value elimination and logical error correction; The data missing value elimination is to eliminate the data with missing key fields that cannot be repaired or corrected; The logical error correction is to supplement or eliminate the data that does not conform to the actual operation situation.

2. The method for determining the minimum value of the flight segment operation time according to claim 1, characterized in that, The historical flight operation data is obtained through the following method: Adopt the method of project research to collect the historical flight operation data, and use the method of optical disc or encrypted email to collect the historical flight operation data during the project research process.

3. The method for determining the minimum value of the flight segment operation time according to claim 2, wherein The collection period of the historical flight operation data includes at least the complete flight operation data of the summer and autumn, and winter and spring flight seasons within one year.

4. The method for determining the minimum value of the flight segment operation time according to claim 1, characterized in that The data preprocessing further includes the steps of calculating the flight sample mean and the flight sample standard deviation.

5. The method for determining the minimum value of the flight segment operation time according to claim 1, wherein The minimum value of the flight segment operation time is: ； Among them, is the mean value of flight samples, s is the standard deviation of flight samples.

6. The method for determining the minimum value of the flight segment operation time according to claim 1, wherein The minimum value of the flight segment operation time is: ； Among them, is the mean value of flight samples, s is the standard deviation of flight samples.

7. A method for determining the minimum value of the flight segment operation time according to claim 1, characterized in that It further includes flight segment revision, and the flight segment revision includes domestic flight segment revision and international flight segment revision.

8. A system for determining the minimum value of the flight segment running time, characterized in that, Including: Data acquisition module: Used to obtain historical flight operation data; Data preprocessing module: Used to use SQL Server to perform data preprocessing on the historical flight operation data to obtain the flight sample mean and the flight sample standard deviation; Flight segment operation time minimum value calculation module: Used to calculate the minimum value of the flight segment operation time based on the flight sample mean and the flight sample standard deviation; Among them, the data preprocessing includes quantity statistics, valid data statistics, and field parsing; The quantity statistics is performed according to months, flight seasons, and the number of records; The valid data are data that simultaneously meet the conditions that the flight date is not empty, the planned aircraft type is not empty, the planned departure airport is the same as the actual departure airport, the planned landing airport is the same as the actual landing airport, the actual departure airport is different from the actual landing airport, the actual push-back time is not empty, and the actual taxi-in time is not empty; The field parsing includes selecting key fields to perform statistical analysis on the historical flight operation data; The data preprocessing further includes data cleaning, and the data cleaning includes data missing value elimination and logical error correction; The data missing value elimination is to eliminate the data with missing key fields that cannot be repaired or corrected; The logical error correction is to supplement or eliminate the data that does not conform to the actual operation situation.

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