CN114638474A - A method for measuring the homogeneity of airport groups based on multidimensional indicators - Google Patents

Abstract

The invention provides an airport group homogeneity measurement method based on multidimensional indexes, which comprises the following steps: respectively designing corresponding homogenization measurement indexes based on the production construction level and the navigation network level of each airport in the airport group to be measured, and calculating the homogenization coefficient of each airport in the airport group relative to each homogenization measurement index, wherein the homogenization coefficient is used for quantifying the homogenization level; distributing weights to the homogeneity measurement indexes by an entropy weight method, and respectively calculating the comprehensive homogeneity level of production construction and the comprehensive homogeneity level of a navigation line network based on the weights; and distributing weights for the comprehensive homogenization level of the production construction and the comprehensive homogenization level of the air line network by using a Delphi weighting method to obtain the comprehensive homogenization level of the airport group. The method comprehensively measures the overall level of the homogenization development of the airport group, and can accurately position the airport pairs with serious homogenization tendency.

Description

A method for measuring the homogeneity of airport groups based on multidimensional indicators

technical field

The invention belongs to the technical field of civil aviation, and in particular relates to a method for measuring the homogeneity of airport groups based on multi-dimensional indicators.

Background technique

Airports are an important carrier for the development of the civil aviation industry. During the development of the civil aviation industry, many regional airport clusters have been created, and the exchanges between the airports in the airport clusters in terms of economy and talents have a trend of coordinated development. In the early days of the emergence of airport clusters, the public welfare of "grouping together for warmth" among airports within the airport cluster is relatively large, which can realize the sharing of resources between airports, which is conducive to the development and growth of a single airport, thus forming a "scale effect" and "agglomeration effect". " of the airport group. However, with the development and maturity of the airport group, the initial development model of the airport group will lead to a high degree of homogeneity between airports in terms of airport support capability, business level and air route network, which will lead to an unfavorable trend of homogenized competition. By measuring the homogeneity of different levels of airports within the airport group and studying the level of homogeneity between airports, it can provide theoretical basis and practical data support for my country to build a world-class airport group with healthy and coordinated development. Therefore, it has important theoretical significance and practical value to study the method of measuring the homogeneity of airport clusters.

There are few domestic and foreign studies on the homogeneity measurement of airport groups. The only quantitative studies focus on the analysis of the homogeneity of airport routes around the airline network or airline operation, and combine the node degree of the complex airline network to characterize it. The network structure characteristics of regional airports, or the research on the optimal operation of airport groups from the perspectives of airlines, passengers and airport operations.

SUMMARY OF THE INVENTION

In view of the above-mentioned defects in the prior art, the present invention provides a method for measuring the homogeneity of airport groups based on multi-dimensional indicators, which comprehensively measures the overall level of the homogenization development of airport groups.

The technical scheme proposed by the present invention is as follows:

The invention discloses a method for measuring the homogeneity of airport groups based on multi-dimensional indicators, comprising the following steps:

Based on the production and construction level and airline network level of each airport in the airport group to be measured, the corresponding homogenization metrics are respectively designed, and the homogenization coefficients of each airport pair in the airport group are calculated with respect to each homogenization metrics. The homogenization coefficient is used to quantify the homogenization level;

The entropy weight method is used to assign weights to the homogenization metrics, and based on the weights, the comprehensive homogeneity level of production and construction and the comprehensive homogeneity level of airline networks are calculated respectively;

The Delphi weighting method is used to assign weights to the comprehensive homogeneity level of the production and construction and the comprehensive homogeneity level of the airline network to obtain the comprehensive homogeneity level of the airport group.

Further, the homogenization metrics at the production and construction level include the number of airport runways, the number of parking spaces, the number of terminals, the number of take-offs and landings, and the passenger throughput; the homogenization metrics at the airline network level include airport pairs and all airports. The number of flights between third-party navigable airports, where the airport pair is a combination of any two airports in the airport group.

Further, the calculation process of the homogenization coefficient of each airport in the airport group to be measured is as follows:

为机场i的第k个同质化度量指标值，

为机场j的第k个同质化度量指标值。in,

is the k-th homogenization metric value of airport i,

is the k-th homogenization metric value of airport j.

Further, the calculation process of the homogenization coefficient of each airport pair in the airport group to be measured regarding the number of flights between the airport pair and all third-party navigable airports is as follows:

Obtain the flight volume between each airport in the airport group to be measured and each third-party navigable airport;

Calculate the homogenization coefficient of each airport pair with respect to the flight volume between the airport pair and each third-party navigable airport based on the flight volume;

Assign a weight to the sum of the airport pair flight volumes corresponding to each third-party navigable airport, and calculate the weighted average of the homogenization coefficients of each airport pair with respect to the airport pair's flight volume with all third-party navigable airports, wherein the weighting The average is used as the homogenization factor for the airport pair with respect to the number of flights between the airport pair and all third-party navigable airports.

Further, the method also includes:

The homogenization coefficient of the number of flights between the airport pair and each third-party navigable airport is specifically calculated by the following formula:

Among them, q represents the number of flights, i and t represent the airport number of the centering airport, and s represents the number of the third-party navigable airport;

The weight assigned to the sum of the airport-to-airport volume corresponding to each third-party navigable airport is specifically assigned by the following formula:

The weighted average of the homogenization coefficients of the airport pairs and all third-party navigable airports for the airport pairs is specifically calculated by the following formula:

Further, the entropy weight method is specifically as follows:

Normalize the values of each homogenization metric;

calculating the proportion of each homogenization metric value;

calculating the information entropy of each homogenization metric value;

Calculate the weight of each homogenization metric value.

Further, the information entropy of the homogenization metric value is defined as follows:

Information entropy = ∑ the probability of each possible event * the amount of information contained in each possible event.

Further, the calculation of the amount of information contained in each possible event adopts the uncertainty function f:

f=log(1/P)=-logP

where P is the probability of each possible event.

Further, the Delphi empowerment method is specifically as follows:

The prior art usually measures the homogeneity of airport groups from a single dimension. The method for measuring the homogeneity of airport groups based on multi-dimensional indicators proposed by the present invention builds a multi-dimensional quantitative indicator system for the homogeneity of airport groups, including the infrastructure, production and operation of airports. Indicators and various indicators of the airline network, establish a comprehensive homogenization measurement system model based on the weighting of homogenization measurement indicators, comprehensively measure the overall level of the homogenization development of the airport group, and accurately locate the airports with a serious homogenization tendency. right.

Description of drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the accompanying drawings required for describing the technical solutions will be briefly introduced below. Obviously, the exemplary embodiments of the present invention and their descriptions are only It is used to explain the present invention and does not constitute an improper limitation of the present invention. For those of ordinary skill in the art, other drawings can also be obtained according to the provided drawings without creative efforts. In the attached image:

Fig. 1 is the schematic flow chart of the method of embodiment 1 of the present invention;

2 is a schematic structural diagram of a multi-dimensional quantitative index system for homogenization of airport clusters in the method according to Embodiment 1 of the present invention;

FIG. 3 is a schematic diagram of the calculation process of the homogenization level of the flight volume between two airports and third-party navigable airports in the method of Embodiment 1 of the present invention.

Detailed ways

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

Example 1

Referring to FIG. 1 , the present embodiment provides a method for measuring the homogeneity of an airport group based on a multi-dimensional index, and the method includes the following steps:

S1: Build a homogeneous multi-dimensional quantitative index system for airport groups;

Specifically, the airport homogeneity multi-dimensional quantitative index system focuses on the research goal of the homogeneity measurement of airport groups, and formulates relevant indicators from the airport production and construction level and the airline network level. In this embodiment, the relevant indicators at the airport production and construction level are airport runways The number of parking spaces, the number of terminals, the number of take-offs and landings, and the passenger throughput are 5 items; the relevant indicators at the level of the airline network are the number of flights between two airports in the airport group and a third-party general airport. The indicators together constitute a multi-dimensional indicator of the homogeneity measure of the airport group. Referring to Fig. 1, Fig. 1 shows a schematic diagram of the system structure of the homogenized multi-dimensional quantitative index of the airport group;

Among them, the calculation method of the homogenization coefficient of the homogenization index of a certain airport production and construction level for the airports in the airport group is as follows. The homogeneity measurement of the airport group is based on the similarity measurement. The degree of homogeneity between objects is based on one-dimensional or multi-dimensional attributes, and the size of the homogeneity coefficient is usually used to characterize the level of homogeneity between different objects. The size of the homogeneity coefficient of the airport group can be used to measure the similarities and differences of the airports within the airport group in terms of functional positioning and route network layout, so as to evaluate the rationality and scientificity of the functional positioning of the airport group. The difference between airport i and airport j in the airport group The homogenization coefficient of an index M is represented by H, namely:

为机场i的第k个指标，

为机场j的第k个指标。H的取值介于[0,1]之间，

和

的差值越大，则同质化系数H的取值越接近0，表明两者之间的同质化程度越低；反之，若

和

的差值越小，则同质化系数H的取值越接近1，表明两机场间的同质化程度越高；若

和

的取值均为0时，则同质化系数H的取值不存在；若

和

的取值相反时，则同质化系数H的度量无意义，因此在实际应用中，应避免度量存在负值的指标之间的同质化程度；In the formula,

is the k-th index of airport i,

is the kth index of airport j. The value of H is between [0,1],

and

The larger the difference is, the closer the value of the homogenization coefficient H is to 0, indicating that the degree of homogeneity between the two is lower; on the contrary, if

and

The smaller the difference is, the closer the value of the homogenization coefficient H is to 1, indicating that the degree of homogeneity between the two airports is higher; if

and

When the value of is 0, the value of the homogenization coefficient H does not exist; if

and

When the value of is opposite, the measurement of the homogeneity coefficient H is meaningless, so in practical applications, it should be avoided to measure the degree of homogeneity between indicators with negative values;

For the homogeneity measurement of the airport group, there is no negative value in the relevant indicators such as airport production and construction and airline network of the airport group. When measuring the homogeneity level between different objects, the homogeneity coefficient can be guaranteed to fall within in the range [0,1]. From the perspective of similarity measurement, it is stipulated that when the homogenization coefficient H≥0.5, the degree of homogeneity is high; when the homogenization coefficient H<0.5, the degree of homogeneity is low;

Among them, the homogeneity index at the airline network level is calculated as follows:

Step 1: Obtain the internal airports A _i , A _i ∈A,i=1,2,...,n and all external navigable airports B _s , B _s ∈ B,s=1,2,..., The number of flights between n is q _is , as shown in Table 1:

Table 1 The number of flights between airport A and general airport B

Step 2: On the basis of the flight volume obtained in Step 1, refer to formula (1) to calculate the homogenization coefficient of the flight volume q _is , q _ts between the airports A _i and A _t in the airport group with respect to the flight volume of a general airport, As follows:

The results of the second step are shown in Table 2:

Table 2 Homogenization coefficient of flight volume between A _i , A _t and navigable airport B

Step 3: Calculate the weighted average of A _i , A _t on the flight volume homogenization coefficient of all navigable airports by column, as the homogeneity level of A _i , A _t in the flight volume of navigable airports. According to the flight volume of the internal airports and the navigable airports in the airport group, A _i and A _t correspond to the sum of the two flights of each navigable airport and give weights _ws , and the weights are set as follows:

The weighted average of the homogeneity coefficients of the two airports A _i and A _t about all the navigable airports B is shown in formula (4 _{) .} The transformation coefficient H _it .

S2: Use the entropy weight method to assign weights to the homogenization metrics, and calculate the comprehensive homogeneity level of production and construction and the comprehensive homogeneity level of airline networks based on the weights;

Synthesize the multi-dimensional airport cluster homogenization index. Since the homogenization multi-dimensional quantitative index system considers many types and quantities of homogenization indexes, when solving the homogenization between airports based on each index, each basic index of the first layer shown in Figure 2 is A basic homogenization matrix will be generated. In order to finally obtain the comprehensive homogenization level matrix of the airport group, two layers of weighting need to be performed.

Combined with the characteristics of the indicators, for the homogenization indicators at the first level of airport production and construction, the entropy weight method is introduced to give objective weights to various indicators of airport production and construction. Entropy is a physical concept of thermodynamics. A measure of order, the larger the entropy, the more chaotic the system, and the smaller the entropy, the more orderly the system. Information entropy draws on the concept of entropy in thermodynamics and is used to describe the average amount of information in an event. Therefore, mathematically, information entropy is the expectation of the amount of information contained in an event. According to the definition of expectation, the formula of information entropy can be imagined. As follows:

Information entropy = ∑ probability of each possible event * amount of information contained in each possible event (5)

The calculation of the amount of information contained in each possible event uses the uncertainty function f

f=log(1/P)=-logP(6)

Using the uncertainty function, on the one hand, it can ensure that the amount of information is a monotonically decreasing function of probability P, and on the other hand, it can ensure that the uncertainty generated by two independent events should be equal to the sum of their respective uncertainties, that is, it has additivity. Putting the uncertainty function into equation (5), we can get:

Among them, W is entropy, U is the set of all possible events, there are n values: U ₁ ,...,U _i ,...,U _n , the corresponding probability is P ₁ ,...,P _i ,...,P _n , the base of the logarithm is generally 2.

The entropy weight method is an objective weighting method. The method of determining the weight of the evaluation index only through sample data can more objectively assign weights to different levels of indicators, and can profoundly reflect the distinguishing ability of the indicators. The relevant steps of using the entropy weight method to weight the indicators are as follows:

First, the data is normalized, and the indicators of different dimensions are the same dimension. This paper uses 0-1 normalization. If the j-th index value of the i-th airport is x _ij , after normalization, it is x′ _ij , the normalized calculation formula is as follows:

计算第j个指标的信息熵

其中，K为常数，

Secondly, calculate the entropy and weight of the index, and calculate the proportion of the jth index of the ith airport:

Calculate the information entropy of the jth indicator

where K is a constant,

Finally, the weight of the j-th indicator can be calculated

This example uses the operation data of the Los Angeles airport group in 2020, and the calculated weight results of the homogenization indicators at the production and construction level of each airport are shown in Table 3:

Table 3 Homogenization index weight of production and construction layer

For the Los Angeles airport group, the number of parking spaces contains the largest amount of information, so its weight is also the largest, which is 0.23; the number of runways and the number of terminals contain relatively small amounts of information, neither exceeding 0.20; the number of take-offs and landings and passenger throughput Contains a fair amount of information.

Calculate the results of the comprehensive homogeneity level at the production and construction level of the Los Angeles airport cluster. Based on the determined weights of the production and construction indicators, the calculation process of the comprehensive homogeneity at the production and construction level is as follows:

分别代表赋予起降架次、旅客吞吐量、跑道数量、停机位数量和航站楼数量的权重，

分别代表机场群机场对之间关于起降架次、旅客吞吐量、跑道数量、停机位数量和航站楼数量的同质化系数，

代表机场群机场对之间关于生产建设综合同质化系数，本实施例的生产建设综合同质化水平计算结果如表4所示：in,

respectively represent the weights given to the number of take-offs and landings, passenger throughput, number of runways, number of parking spaces and number of terminals,

respectively represent the homogenization coefficients between the airport pairs in the airport group regarding the number of take-offs and landings, passenger throughput, number of runways, number of parking spaces and number of terminals,

On behalf of the comprehensive homogeneity coefficient of production and construction between the pairs of airports in the airport group, the calculation results of the comprehensive homogeneity level of production and construction in this embodiment are shown in Table 4:

Table 4 The comprehensive homogenization level of production and construction of the Los Angeles airport cluster

It can be seen from Table 4 that among the Los Angeles airports, Ontario-John Wayne Airport has the highest level of comprehensive homogeneity in production and construction, with a homogenization coefficient of up to 0.83; there are 5 pairs of airports with a homogenization coefficient of 0.50-0.80. From largest to smallest, Burbank-Ontario, Burbank-John Wayne, Long Beach-John Wayne, Long Beach-Ontario, and Burbank-Long Beach. The above-mentioned airport pairs have a high level of comprehensive homogeneity in airport production and construction, especially Ontario-John Wayne Airport is at a high level; the other airport pairs with a homogenization coefficient below 0.50 have a low level of homogeneity. There is a high homogenization tendency between the main airports and the secondary airports in the airport group.

According to the airport route network data of the Los Angeles airport group, the homogeneity level of the route network is calculated, and the calculation results are shown in Table 5:

Table 5 The homogeneity level of the route network of the Los Angeles airport group

It can be seen from Table 5 that among the Los Angeles airports, the Ontario-John Wayne and Burbank-John Wayne airports have the highest level of homogeneity in the route network, with a homogenization coefficient of 0.32, indicating that the number of navigable airports, directions and flights The homogeneity level of Ontario-John Wayne Airport and Burbank-John Wayne Airport is at a relatively high level in the Los Angeles airport cluster; the homogeneity coefficients of other airport pairs are all lower than 0.3 , the homogeneity level is low.

S3: Use the Delphi weighting method to assign weights to the comprehensive homogenization level of the production and construction and the comprehensive homogenization level of the airline network, and obtain the comprehensive homogenization level of the airport group;

For the second-layer production and construction comprehensive homogeneity level and the airline network comprehensive homogeneity level (it should be noted that since there is only one homogeneity measurement index at the airline network level in this embodiment, the airport group airline network is homogeneous The integration level is the comprehensive homogeneity level of the airline network), and the Delphi method is introduced to set the weights, so as to obtain the comprehensive homogeneity level of the airport group. The Delphi weighting method is calculated as follows:

The Delphi method is used to give weights to the comprehensive homogenization index of production and construction and the comprehensive homogenization index of airline network. Here, the weight of the comprehensive homogeneity of production and construction of the airport group is 0.4, and the weight of the comprehensive homogeneity of the airline network is 0.6. The airline network is a more important factor affecting the homogeneity level of the airport group. The final result of the comprehensive homogeneity level of the Los Angeles airport cluster (only the upper triangle part is shown) is shown in Table 6:

Table 6 The comprehensive homogeneity level of the Los Angeles airport cluster

Under the dual effects of production and construction indicators and route network indicators, among the Los Angeles airports, Ontario-John Wayne Airport still has the highest level of comprehensive homogeneity, with a homogenization coefficient of 0.53, while the comprehensive homogeneity among other airports is still the highest. The coefficients are all lower than 0.50, indicating that the comprehensive homogeneity level among other airports is at a low level. Combined with the homogenization calculation results of the first-level indicators, except for Ontario-John Wayne Airport, in terms of production and construction indicators, although the homogeneity level between airports is generally at the upper-middle level, the homogeneity of the airline network The level is relatively low, so the level of comprehensive homogeneity is generally not high, which reflects the differentiated layout of the Los Angeles airport group in terms of the route network. While maintaining the coordinated development of the overall production and construction indicators, the airport functions have been diversified. In particular, it is pointed out that Ontario and John Wayne Airport, as the two major airports in Los Angeles, have a high tendency to homogenize in airport production and construction and route network. In order to avoid vicious competition, the government and relevant departments should carry out various Control, on the premise of ensuring that the production and construction indicators do not decline, further optimize the differentiated layout of the airline network, so that the Los Angeles airport group will move forward healthily to a world-class airport group.

Table 7 shows the comprehensive homogeneity coefficient matrix obtained by using the multi-dimensional index-based airport group homogeneity measurement method described in this embodiment and the airline network homogeneity obtained by using the traditional airport airline network level homogeneity measurement technology matrix:

Table 7 Comprehensive homogenization coefficient matrix and airline network homogenization matrix

It can be seen from Table 7 that among the Los Angeles airports, the Ontario-John Wayne and Burbank-John Wayne airports have the highest level of homogeneity in the route network, with a homogenization coefficient of 0.32, indicating that in terms of the route network, Ontario-John Wayne has the highest level of homogeneity. The homogeneity level of the airport and Burbank-John Wayne Airport is at a high level in the Los Angeles airport group; the homogeneity coefficients of other airport pairs are all lower than 0.3, and the homogeneity level is low. The homogeneity level of the airport group is calculated only based on the distribution of the airline network. The homogeneity level of all airports in the Los Angeles airport group is below 0.5. The multi-dimensional index airport group homogenization index system proposed by the present invention is used for calculation. Ontario-John The comprehensive homogeneity level of Wayne Airport is 0.53, which is at a relatively high level. Referring to the development positioning of the two airports in the Los Angeles airport group, Ontario and John Wayne Airport, as the two major airports in Los Angeles, have outstanding achievements in airport production and construction and route network. The higher the homogenization tendency, the more comprehensive the analysis results of the multi-dimensional airport group homogenization index system proposed by the present invention.

In addition, an embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium can store a program, and when the program is executed, the program includes any multi-dimensional index-based airport group homogeneity described in the above method embodiments. Some or all of the steps of the metric method.

In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit. The above-mentioned integrated units may be implemented in the form of hardware, or may be implemented in the form of software functional units.

The integrated unit, if implemented as a software functional unit and sold or used as a stand-alone product, may be stored in a computer-readable memory. Based on such understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a memory, Several instructions are included to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing relevant hardware through a program, and the program can be stored in a computer-readable memory, and the memory can include: a flash disk , read-only memory, random access memory, magnetic or optical disk, etc.

The specific embodiments described above further describe the purpose, technical solutions and beneficial effects of the present application in detail. It should be understood that the above descriptions are only specific embodiments of the present application, and are not intended to limit the The protection scope, any modifications, equivalent replacements, improvements, etc. made on the basis of the technical solutions of the present application shall be included within the protection scope of the present application.

Claims (10)

1. A multidimensional index-based airport group homogeneity measurement method is characterized by comprising the following steps:

respectively designing corresponding homogenization measurement indexes based on the production construction level and the navigation network level of each airport in the airport group to be measured, and calculating the homogenization coefficient of each airport in the airport group relative to each homogenization measurement index, wherein the homogenization coefficient is used for quantifying the homogenization level;

distributing weights to the homogeneity measurement indexes by using an entropy weight method, and respectively calculating the comprehensive homogeneity level of production construction and the comprehensive homogeneity level of a navigation network based on the weights;

and distributing weights for the comprehensive homogenization level of the production construction and the comprehensive homogenization level of the air line network by using a Delphi weighting method to obtain the comprehensive homogenization level of the airport group.

2. The airport group homogeneity metric method based on multi-dimensional indexes as claimed in claim 1, wherein the production and construction level homogeneity metric indexes comprise airport runway number, parking space number, terminal building number, taking-off and landing number, passenger throughput; the navigation network level homogeneity measurement index comprises flight quantity between an airport pair and all third-party navigation airports, wherein the airport pair is a combination of any two airports in an airport group.

3. The airport group homogeneity measurement method based on multi-dimensional indexes as claimed in claim 1, wherein homogeneity coefficients of each airport in the airport group to be measured on the production and construction level homogeneity measurement indexes are calculated as follows:

wherein,

for the k-th homogeneity measure index value for airport i,

the k-th homogeneity measure index value for airport j.

4. The method for measuring the homogeneity of the airport group based on the multidimensional index as claimed in claim 2, wherein the homogeneity coefficient of each airport pair in the airport group to be measured with respect to the flight quality between the airport pair and all third-party navigation airports is calculated as follows:

acquiring flight quantity between each airport and each third-party navigation airport in the airport group to be measured;

calculating homogeneity coefficients of each airport pair with respect to the flight volume between the airport pair and each third-party navigable airport based on the flight volume;

and assigning a weight to the sum of the airport pairs corresponding to the airport pairs of the third-party navigation airports, and calculating a weighted average value of homogeneity coefficients of the airport pairs relative to the flight quantities of the airport pairs and all the third-party navigation airports, wherein the weighted average value is used as the homogeneity coefficient of the airport pairs relative to the flight quantities between the airport pairs and all the third-party navigation airports.

5. The method of claim 4, further comprising:

the homogeneity coefficient of each airport pair about the flight quantity between the airport pair and each third-party navigation airport is specifically calculated by the following formula:

wherein q represents the flight quantity, i, t represents the number of the airport in the middle, and s represents the number of the third party navigation airport;

the weight is specifically distributed to the sum of the flight quantity of the airport corresponding to each third-party navigation airport through the following formula:

the weighted average of the homogeneity coefficients of the airport pairs with respect to the flight mass of all third-party navigable airports is specifically calculated by the following formula:

6. the method of claim 1, wherein the entropy weight method is specifically as follows:

normalizing each homogeneity measurement index value;

calculating the proportion of each homogeneity measure index value;

calculating the information entropy of each homogenization metric index value;

and calculating the weight of each homogeneity measure index value.

7. The method of airport group homogeneity metric based on multidimensional measurements as claimed in claim 6, wherein the information entropy of the homogeneity metric index value is defined as follows:

information entropy ═ probability of each possible event ∑ information quantity contained in each possible event.

8. The method according to claim 7, wherein the calculation of the amount of information contained in each possible event uses an uncertainty function f:

f＝log(1/P)＝-log P

where P is the probability of each possible event.

9. The method of claim 1, wherein the Delphi weighting method is as follows:

the comprehensive homogenization level of the airport group is 1 multiplied by the weight of the comprehensive homogenization level of production construction and 2 multiplied by the weight of the comprehensive homogenization level of the navigation network.

10. A computer-readable storage medium having stored thereon computer-executable instructions that, when executed, implement the method for multi-dimensional index-based airport group homogeneity metric according to any one of claims 1 to 9.

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