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International Journal of Trend in Scientific Research and Development (IJTSRD)
Volume 5 Issue 1, November-December 2020 Available Online: www.ijtsrd.com e-ISSN: 2456 – 6470
@ IJTSRD | Unique Paper ID – IJTSRD37911 | Volume – 5 | Issue – 1 | November-December 2020 Page 344
Review on the Passenger Throughput Forecast of Airport
Feng Li, Yi Wang, Ran Chen
School of Information, Beijing Wuzi University, Beijing, China
ABSTRACT
In recent years, China’s economy has developedrapidlyandthepeople’sliving
standards have continued to improve. A high-end means of transportation,
airplanes, is favored and accepted by more and more people with its
advantages of comfort, speed, and safety. Accompanying it is the increase in
pressure on passenger transportation in the aviation industry. The
development of China's civil aviation industry is relatively late and relatively
immature. It has only ushered in a development frenzy after the reform and
opening up. Therefore, the methodofpredictingairportpassengerthroughput
is also imperfect. The outdated forecasting method cannot predict the
situation of the airport well, so it is very important to seek a more scientific,
more complete and systematic forecasting method of airport passenger
throughput. This article has conducted a certain review and research on the
prediction methods of airport passenger throughput, and hopes to have
further research in this aspect.
Keywords: Airport; Passenger throughput; Prediction method
How to cite this paper: Feng Li | Yi Wang
| Ran Chen "Review on the Passenger
Throughput Forecast of Airport"
Published in
International Journal
of Trend in Scientific
Research and
Development(ijtsrd),
ISSN: 2456-6470,
Volume-5 | Issue-1,
December 2020,
pp.344-346, URL:
www.ijtsrd.com/papers/ijtsrd37911.pdf
Copyright © 2020 by author(s) and
International Journal ofTrendinScientific
Research and Development Journal. This
is an Open Access article distributed
under the terms of
the Creative
CommonsAttribution
License (CC BY 4.0)
(http://creativecommons.org/licenses/by/4.0)
1. INTRODUCTION
The air transportation industry can reflect the development
of economy and society. For example, the development of
Beijing Capital International Airport largely reflects the
development of China's civil aviation industry since the
reform and opening up. Beijing Capital International Airport
was officially built and put into use in 1958. So far, the
airport has been in operation for more than 60 years. Since
the reform and opening up in 1978, Beijing Capital
International Airport has entered an unprecedented rapid
development stage: in 1978, the annual passenger
throughput of Beijing airport was only 1.03 million, but 60
years later, it exceeded 100 million, with an average annual
growth rate of 12.1%. On December 28, 2018, Air China
CA932 arrived in Beijing from Frankfurt andlandedsafelyat
the capital airport. So far, the annual passenger throughput
of Beijing Airport exceeded 100-million person timesforthe
first time. It marks that Beijing Capital International Airport
is the first airport with an annual passenger throughput of
over 100 million in China, and also the second airport in the
world with an annual passenger throughput of more than
100 million after Atlanta Airport in the United States. It can
be seen that the development of the airport is closelyrelated
to the development of the local economy.
As an important indicator to measure the development of
civil aviation transportation, it is very valuabletopredictthe
passenger throughput scientifically and reasonably[1].Itcan
not only promote the development of prediction theory, but
also provide data suggestions for the subsequent
management and construction of the airport. Therefore,this
paper reviews the prediction methods of airport passenger
throughput, hoping to do some research in this area [2].
2. Research significance
For the transportation industry, scientific and systematic
decision-making is very meaningful for the effectiveness of
planning and management [3], andscientificdecision-making
is based on scientific prediction. Scientific prediction can
minimize the uncertain risks in the future and provide the
airport authorities with decision-making basis for
construction, investment, reconstruction, and operation. At
present, China's civil aviation industry is in a period of rapid
development, how to make theexpansionoftheairport meet
the overall needs of the society is a problem to be solved:
whether the construction project has value, whether the
corresponding timing is appropriate, must rely on accurate
passenger throughput forecast[4].Ascientificandreasonable
prediction method of airport passenger throughput can
correctly estimate the economic costs and benefits of
construction projects, and will not lead to decision-making
mistakes. From the perspective of overall benefits, scientific
passenger throughput forecast data can also promote the
coordinated promotion of surrounding industries,
comprehensive transportation industry and civil aviation
airport industry, so as to ensure reasonable overall layout
and orderly development of national economy [5].
Therefore, the scientificanalysisandpredictionoftheannual
passenger throughput of the airport has a very far-reaching
practical significance for the construction, planning,
investment and operation of civil aviation airports and the
results of the prediction can also be used for reference by
other cities in China [6].
IJTSRD37911
International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470
@ IJTSRD | Unique Paper ID – IJTSRD37911 | Volume – 5 | Issue – 1 | November-December 2020 Page 345
3. Literature review
In recent years, many experts and scholars have devoted
themselves to the prediction of airport passenger
throughput. Some experts and scholars mainly study the
main influencing factors of airport passenger throughput,
and some experts and scholars mainly study the main
prediction methods of airport passenger throughput. Their
research results have great reference value.
3.1. Overview of influencing factors of airport
passenger throughput
Experts and scholars have done a lot of research on the
influencing factors of passenger throughput of civil aviation
airport. Pengpeng Jiao [7] used the PCA to analyze the main
influencing factors of airport passenger throughput in
"Research on the Influencing Mechanism and Prediction
Method of Airport Passenger Throughput", and then
established a multiple linear regression model. The results
can accurately predict the future airport passenger
throughput. Zidong Zhang and Jianhong Xu [8] also used the
PCA to analyze the main influencing factors in the "Main
Influencing Factors of Airport Passenger Throughput", and
selected four domestic famous airports for empirical
analysis, the results show that although the ranking of each
influencing factor is different in different airports, the most
important influencing factors are similar. Chongjun Xiong,
Xuanxi Ning and Yingli Pan [9] and Cuiping Li [10] have used
the time series data to conduct qualitative and quantitative
analysis on the main influencing factors of the passenger
throughput of civil aviation airports, and use the grey
prediction method to carry out correlation analysis on
various factors affecting China's civil aviation passenger
transport system. The results show that the most important
factors affecting airport passenger throughput are GNP, the
average salary of employees and the total amount of foreign
trade. Through the above literature on the main influencing
factors of airport passenger throughput, we can know that
any airport passenger throughput is the result of a varietyof
factors.
3.2. Overview of airport passenger throughput
forecasting methods
According to the literature,thepredictionmethodsofairport
passenger throughput can be roughly divided into
qualitative prediction method and quantitative prediction
method, and the quantitative prediction method can be
divided into econometric method and time series prediction
method. Time series forecasting method is based on the
continuity of the development of things, using the past time
series data for statistics and analysis to calculate the
development trend of things, and then predict the future
development and change ofa regressionforecastingmethod,
which can be used for short-term, medium-term and long-
term prediction. The common time series forecasting
methods include moving average method, exponential
smoothing method and trend forecasting method.
Econometric method is based on the relationship between
the object of study and other things to promote or restrict
each other, so as to find its internal laws for data fitting.
Some common econometric models include neural network
model, multiple linear regression model and so on.
3.2.1. Qualitative prediction method
Qualitative prediction method is also called empirical
judgment method. The qualitative prediction method is
based on people's experience, judgment and analysis ability
to judge the nature of things, focusing on predicting the
development trend, direction and major turning point of
things. The common qualitative prediction methods mainly
include market survey forecasting method, analogymethod,
expert prediction method and Delphi method. Among them,
Delphi method is a kind of expert investigation method,
which is a method to judge and predict the research
problems according to people's existing experience.
3.2.2. Quantitative prediction method
Quantitative prediction method is a kindofmethodthatuses
some specific historical data or factor variable values, uses
certain mathematical methodsormodelstoscientificallyand
thoroughly analyze and process the obtained data, find out
the potential laws in the data or the regular relations with
other factors, so as to realize the prediction.
With the development of the times and the progress of
science and technology, there are many effective airport
passenger throughput predictionmethods,someofthemore
common quantitative prediction methods are: time series
prediction method, trend extrapolation prediction method,
regression analysis prediction method, econometric
prediction method, neural network prediction method and
grey prediction method [11].
3.2.3. Comparative analysis of the two methods
Table 1 Comparative analysis of advantages and disadvantages
Advantage Disadvantage Suitable situation
Time series
(1) Simple operation
(2) Only needs the passenger
throughput data over the
years.
(3) Small non-system error.
(1) The prediction value is easy
to lag behind.
(2) It is not suitable for long-
term prediction.
Short-term forecast
Trend
extrapolation
(1) The process is simple and fast.
(2) The data processing is easy to
operate.
(1) It can only predict stable
and continuous trend in time
and space.
(2) requires high data timing.
Airports with relatively
stable social and economic
environment
Regression
analysis
(1) The preliminary data is easy to
obtain.
(2) The model is easy to establish
and the calculation is simple.
(1) Univariate regression model
is simple, but its accuracy is
low.
(2) Multiple regression model
data collection is difficult.
Airports with early
navigable years
International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470
@ IJTSRD | Unique Paper ID – IJTSRD37911 | Volume – 5 | Issue – 1 | November-December 2020 Page 346
Econometric
prediction
method
(1) The economic meaning of the
model is clear and the
calculation is simple.
(2) If exogenous variables and
throughput trend are correctly
judged, the prediction accuracy
is higher.
(1)The workload of data
collection is heavy.
(2)Exogenous variable selection
is easy to vary from person
to person.
Airports in the period of
investment and growth
Neural
network
(1) The prediction model can be
modified continuously.
(2) The calculation is very fast
after the correction.
(1) It is easy to over fit in
training.
(2) The actual prediction error is
large.
Large airports
Grey
prediction
method
(1) Less data is required and the
principle is simple.
(2) The accuracy of short-term
prediction is high and the
model can be tested.
(1) It involves more advanced
mathematical methods.
(2) The calculations are
cumbersome.
Short-term forecast or new
airport
In recent years, with the rapid development of China's air
transport industry, experts and scholars have developed
many main prediction methods of airport passenger
throughput. Guoyan Li, Nan Li and Zhiqing Wang [12]
introduced the main prediction methods of China's airport
passenger throughput and some shortcomings and
deficiencies in "Prediction Method and Current Situation of
China's Airport Passenger Throughput". Shanlin Hui [13]
made a discussion on the shortcomings of the prediction
model of China's civil aviation airport passengerthroughput
in "Discussion on the Prediction Method of Passenger
Throughput of Civil Airport", it is proposed that the most
appropriate prediction methodshouldbeselectedaccording
to the actual situation for targeted prediction, and a more
accurate prediction result is finally obtained by combining
the qualitative prediction method with the quantitative
prediction method. Hui Zhang and Zhe Wang [14] compared
and analyzed the prediction methods of various airport
passenger throughput in "DiscussiononAirportThroughput
Prediction Methods", and elaborated in detail each
advantages and disadvantages of the two methods, the
applicable airport types and so on.
This paper mainly compares the advantages and
disadvantages of some common quantitative prediction
methods (see Table 1). From table 1, we can draw a
conclusion that each forecasting method has its own
advantages and disadvantages, as well as its applicable
situation. When we predict the passenger traffic volume of
the airport, we need to consider not only the airport's own
factors, but also the applicability of each prediction method,
and make appropriate use of it according to the local
conditions.
Fund: The study was supported by BeijingSocial Science
Foundation (18GLB022), Beijing Municipal Education
Commission “shipei” Project in 2019, Beijing Wuzi
University Major Research Projects (2019XJZD12).
References
[1] Zidong Zhang, Jianhong Xu. Main influencing factors
of airport passenger throughput [J].Urban Transport,
2007(06):54-57.
[2] Yanjiao Shu. Study on prediction method of airport
passenger throughput [D]. Nanjing University of
Aeronautics and Astronautics, 2008.
[3] Tao Xin. Research on the application of grey
correlation theory in passenger throughput
prediction of tourist airport[D].ShandongUniversity,
2012.
[4] Wenhao Xu. Influencing factors and trend prediction
of passenger throughput of Shanghai civil aviation
airport [D]. Shanghai Academy of Social Sciences,
2019.
[5] Bangju Huang, Junsong Lin, Xiaoyu Zheng, Xuedong
Fang. Passenger throughput forecastofcivil transport
airport based on multiple linear regression analysis
[J]. Mathematics in Practice and Theory, 2013,
43(04):172-178.
[6] Hong LU. Shanghai Hongqiao Airport passenger
throughput forecast research [J]. Modern Business,
2017(26):185-186.
[7] Pengpeng Jiao. Study on influence mechanism and
prediction method of airport passenger throughput
[J]. Journal of Transportation Systems Engineering
and Information Technology, 2005(01):107-110.
[8] Zidong Zhang, Jianhong Xu. Main influencing factors
of airport passenger throughput [J].Urban Transport,
2007, 1l(6): 54-57.
[9] Chongjun Xiong, Xuanxi Ning, Yingli Pan. Researchon
Influencing Factors of civil aviation passenger
transport based on grey correlation theory [J].
Decision-making Reference, 2006, 1:52-53.
[10] Cuiping Li. Analysis on Influencing Factors of China's
civil aviation passenger traffic volume[J].Technology
and Industry, 2011, 1(1): 59-61.
[11] Hongjun Xu, Jungai Tian, Huitao Ma. New Regional
Airport Passenger Throughput Forecast Model Based
on Airport Groups [P]. Management and Service
Science (MASS), 2011 International Conference on,
2011.
[12] Guoyan Li, Nan Li, Zhiqing Wang. Prediction methods
and status quo of airport passenger throughput in
China [J]. China Civil Aviation, 2004 (05): 26-28.
[13] Shanlin Hui. Discussion on prediction method of
passenger throughput of civil airport [J]. Science and
Technology Association Forum, 2010, 1:142-143.
[14] Hui Zhang, Zhe Wang. Discussion on prediction
method of airport throughput [J].China Civil Aviation,
2008, 10 (94):67-68.

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Review on the Passenger Throughput Forecast of Airport

  • 1. International Journal of Trend in Scientific Research and Development (IJTSRD) Volume 5 Issue 1, November-December 2020 Available Online: www.ijtsrd.com e-ISSN: 2456 – 6470 @ IJTSRD | Unique Paper ID – IJTSRD37911 | Volume – 5 | Issue – 1 | November-December 2020 Page 344 Review on the Passenger Throughput Forecast of Airport Feng Li, Yi Wang, Ran Chen School of Information, Beijing Wuzi University, Beijing, China ABSTRACT In recent years, China’s economy has developedrapidlyandthepeople’sliving standards have continued to improve. A high-end means of transportation, airplanes, is favored and accepted by more and more people with its advantages of comfort, speed, and safety. Accompanying it is the increase in pressure on passenger transportation in the aviation industry. The development of China's civil aviation industry is relatively late and relatively immature. It has only ushered in a development frenzy after the reform and opening up. Therefore, the methodofpredictingairportpassengerthroughput is also imperfect. The outdated forecasting method cannot predict the situation of the airport well, so it is very important to seek a more scientific, more complete and systematic forecasting method of airport passenger throughput. This article has conducted a certain review and research on the prediction methods of airport passenger throughput, and hopes to have further research in this aspect. Keywords: Airport; Passenger throughput; Prediction method How to cite this paper: Feng Li | Yi Wang | Ran Chen "Review on the Passenger Throughput Forecast of Airport" Published in International Journal of Trend in Scientific Research and Development(ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-1, December 2020, pp.344-346, URL: www.ijtsrd.com/papers/ijtsrd37911.pdf Copyright © 2020 by author(s) and International Journal ofTrendinScientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative CommonsAttribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0) 1. INTRODUCTION The air transportation industry can reflect the development of economy and society. For example, the development of Beijing Capital International Airport largely reflects the development of China's civil aviation industry since the reform and opening up. Beijing Capital International Airport was officially built and put into use in 1958. So far, the airport has been in operation for more than 60 years. Since the reform and opening up in 1978, Beijing Capital International Airport has entered an unprecedented rapid development stage: in 1978, the annual passenger throughput of Beijing airport was only 1.03 million, but 60 years later, it exceeded 100 million, with an average annual growth rate of 12.1%. On December 28, 2018, Air China CA932 arrived in Beijing from Frankfurt andlandedsafelyat the capital airport. So far, the annual passenger throughput of Beijing Airport exceeded 100-million person timesforthe first time. It marks that Beijing Capital International Airport is the first airport with an annual passenger throughput of over 100 million in China, and also the second airport in the world with an annual passenger throughput of more than 100 million after Atlanta Airport in the United States. It can be seen that the development of the airport is closelyrelated to the development of the local economy. As an important indicator to measure the development of civil aviation transportation, it is very valuabletopredictthe passenger throughput scientifically and reasonably[1].Itcan not only promote the development of prediction theory, but also provide data suggestions for the subsequent management and construction of the airport. Therefore,this paper reviews the prediction methods of airport passenger throughput, hoping to do some research in this area [2]. 2. Research significance For the transportation industry, scientific and systematic decision-making is very meaningful for the effectiveness of planning and management [3], andscientificdecision-making is based on scientific prediction. Scientific prediction can minimize the uncertain risks in the future and provide the airport authorities with decision-making basis for construction, investment, reconstruction, and operation. At present, China's civil aviation industry is in a period of rapid development, how to make theexpansionoftheairport meet the overall needs of the society is a problem to be solved: whether the construction project has value, whether the corresponding timing is appropriate, must rely on accurate passenger throughput forecast[4].Ascientificandreasonable prediction method of airport passenger throughput can correctly estimate the economic costs and benefits of construction projects, and will not lead to decision-making mistakes. From the perspective of overall benefits, scientific passenger throughput forecast data can also promote the coordinated promotion of surrounding industries, comprehensive transportation industry and civil aviation airport industry, so as to ensure reasonable overall layout and orderly development of national economy [5]. Therefore, the scientificanalysisandpredictionoftheannual passenger throughput of the airport has a very far-reaching practical significance for the construction, planning, investment and operation of civil aviation airports and the results of the prediction can also be used for reference by other cities in China [6]. IJTSRD37911
  • 2. International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470 @ IJTSRD | Unique Paper ID – IJTSRD37911 | Volume – 5 | Issue – 1 | November-December 2020 Page 345 3. Literature review In recent years, many experts and scholars have devoted themselves to the prediction of airport passenger throughput. Some experts and scholars mainly study the main influencing factors of airport passenger throughput, and some experts and scholars mainly study the main prediction methods of airport passenger throughput. Their research results have great reference value. 3.1. Overview of influencing factors of airport passenger throughput Experts and scholars have done a lot of research on the influencing factors of passenger throughput of civil aviation airport. Pengpeng Jiao [7] used the PCA to analyze the main influencing factors of airport passenger throughput in "Research on the Influencing Mechanism and Prediction Method of Airport Passenger Throughput", and then established a multiple linear regression model. The results can accurately predict the future airport passenger throughput. Zidong Zhang and Jianhong Xu [8] also used the PCA to analyze the main influencing factors in the "Main Influencing Factors of Airport Passenger Throughput", and selected four domestic famous airports for empirical analysis, the results show that although the ranking of each influencing factor is different in different airports, the most important influencing factors are similar. Chongjun Xiong, Xuanxi Ning and Yingli Pan [9] and Cuiping Li [10] have used the time series data to conduct qualitative and quantitative analysis on the main influencing factors of the passenger throughput of civil aviation airports, and use the grey prediction method to carry out correlation analysis on various factors affecting China's civil aviation passenger transport system. The results show that the most important factors affecting airport passenger throughput are GNP, the average salary of employees and the total amount of foreign trade. Through the above literature on the main influencing factors of airport passenger throughput, we can know that any airport passenger throughput is the result of a varietyof factors. 3.2. Overview of airport passenger throughput forecasting methods According to the literature,thepredictionmethodsofairport passenger throughput can be roughly divided into qualitative prediction method and quantitative prediction method, and the quantitative prediction method can be divided into econometric method and time series prediction method. Time series forecasting method is based on the continuity of the development of things, using the past time series data for statistics and analysis to calculate the development trend of things, and then predict the future development and change ofa regressionforecastingmethod, which can be used for short-term, medium-term and long- term prediction. The common time series forecasting methods include moving average method, exponential smoothing method and trend forecasting method. Econometric method is based on the relationship between the object of study and other things to promote or restrict each other, so as to find its internal laws for data fitting. Some common econometric models include neural network model, multiple linear regression model and so on. 3.2.1. Qualitative prediction method Qualitative prediction method is also called empirical judgment method. The qualitative prediction method is based on people's experience, judgment and analysis ability to judge the nature of things, focusing on predicting the development trend, direction and major turning point of things. The common qualitative prediction methods mainly include market survey forecasting method, analogymethod, expert prediction method and Delphi method. Among them, Delphi method is a kind of expert investigation method, which is a method to judge and predict the research problems according to people's existing experience. 3.2.2. Quantitative prediction method Quantitative prediction method is a kindofmethodthatuses some specific historical data or factor variable values, uses certain mathematical methodsormodelstoscientificallyand thoroughly analyze and process the obtained data, find out the potential laws in the data or the regular relations with other factors, so as to realize the prediction. With the development of the times and the progress of science and technology, there are many effective airport passenger throughput predictionmethods,someofthemore common quantitative prediction methods are: time series prediction method, trend extrapolation prediction method, regression analysis prediction method, econometric prediction method, neural network prediction method and grey prediction method [11]. 3.2.3. Comparative analysis of the two methods Table 1 Comparative analysis of advantages and disadvantages Advantage Disadvantage Suitable situation Time series (1) Simple operation (2) Only needs the passenger throughput data over the years. (3) Small non-system error. (1) The prediction value is easy to lag behind. (2) It is not suitable for long- term prediction. Short-term forecast Trend extrapolation (1) The process is simple and fast. (2) The data processing is easy to operate. (1) It can only predict stable and continuous trend in time and space. (2) requires high data timing. Airports with relatively stable social and economic environment Regression analysis (1) The preliminary data is easy to obtain. (2) The model is easy to establish and the calculation is simple. (1) Univariate regression model is simple, but its accuracy is low. (2) Multiple regression model data collection is difficult. Airports with early navigable years
  • 3. International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470 @ IJTSRD | Unique Paper ID – IJTSRD37911 | Volume – 5 | Issue – 1 | November-December 2020 Page 346 Econometric prediction method (1) The economic meaning of the model is clear and the calculation is simple. (2) If exogenous variables and throughput trend are correctly judged, the prediction accuracy is higher. (1)The workload of data collection is heavy. (2)Exogenous variable selection is easy to vary from person to person. Airports in the period of investment and growth Neural network (1) The prediction model can be modified continuously. (2) The calculation is very fast after the correction. (1) It is easy to over fit in training. (2) The actual prediction error is large. Large airports Grey prediction method (1) Less data is required and the principle is simple. (2) The accuracy of short-term prediction is high and the model can be tested. (1) It involves more advanced mathematical methods. (2) The calculations are cumbersome. Short-term forecast or new airport In recent years, with the rapid development of China's air transport industry, experts and scholars have developed many main prediction methods of airport passenger throughput. Guoyan Li, Nan Li and Zhiqing Wang [12] introduced the main prediction methods of China's airport passenger throughput and some shortcomings and deficiencies in "Prediction Method and Current Situation of China's Airport Passenger Throughput". Shanlin Hui [13] made a discussion on the shortcomings of the prediction model of China's civil aviation airport passengerthroughput in "Discussion on the Prediction Method of Passenger Throughput of Civil Airport", it is proposed that the most appropriate prediction methodshouldbeselectedaccording to the actual situation for targeted prediction, and a more accurate prediction result is finally obtained by combining the qualitative prediction method with the quantitative prediction method. Hui Zhang and Zhe Wang [14] compared and analyzed the prediction methods of various airport passenger throughput in "DiscussiononAirportThroughput Prediction Methods", and elaborated in detail each advantages and disadvantages of the two methods, the applicable airport types and so on. This paper mainly compares the advantages and disadvantages of some common quantitative prediction methods (see Table 1). From table 1, we can draw a conclusion that each forecasting method has its own advantages and disadvantages, as well as its applicable situation. When we predict the passenger traffic volume of the airport, we need to consider not only the airport's own factors, but also the applicability of each prediction method, and make appropriate use of it according to the local conditions. Fund: The study was supported by BeijingSocial Science Foundation (18GLB022), Beijing Municipal Education Commission “shipei” Project in 2019, Beijing Wuzi University Major Research Projects (2019XJZD12). References [1] Zidong Zhang, Jianhong Xu. Main influencing factors of airport passenger throughput [J].Urban Transport, 2007(06):54-57. [2] Yanjiao Shu. Study on prediction method of airport passenger throughput [D]. Nanjing University of Aeronautics and Astronautics, 2008. [3] Tao Xin. Research on the application of grey correlation theory in passenger throughput prediction of tourist airport[D].ShandongUniversity, 2012. [4] Wenhao Xu. Influencing factors and trend prediction of passenger throughput of Shanghai civil aviation airport [D]. Shanghai Academy of Social Sciences, 2019. [5] Bangju Huang, Junsong Lin, Xiaoyu Zheng, Xuedong Fang. Passenger throughput forecastofcivil transport airport based on multiple linear regression analysis [J]. Mathematics in Practice and Theory, 2013, 43(04):172-178. [6] Hong LU. Shanghai Hongqiao Airport passenger throughput forecast research [J]. Modern Business, 2017(26):185-186. [7] Pengpeng Jiao. Study on influence mechanism and prediction method of airport passenger throughput [J]. Journal of Transportation Systems Engineering and Information Technology, 2005(01):107-110. [8] Zidong Zhang, Jianhong Xu. Main influencing factors of airport passenger throughput [J].Urban Transport, 2007, 1l(6): 54-57. [9] Chongjun Xiong, Xuanxi Ning, Yingli Pan. Researchon Influencing Factors of civil aviation passenger transport based on grey correlation theory [J]. Decision-making Reference, 2006, 1:52-53. [10] Cuiping Li. Analysis on Influencing Factors of China's civil aviation passenger traffic volume[J].Technology and Industry, 2011, 1(1): 59-61. [11] Hongjun Xu, Jungai Tian, Huitao Ma. New Regional Airport Passenger Throughput Forecast Model Based on Airport Groups [P]. Management and Service Science (MASS), 2011 International Conference on, 2011. [12] Guoyan Li, Nan Li, Zhiqing Wang. Prediction methods and status quo of airport passenger throughput in China [J]. China Civil Aviation, 2004 (05): 26-28. [13] Shanlin Hui. Discussion on prediction method of passenger throughput of civil airport [J]. Science and Technology Association Forum, 2010, 1:142-143. [14] Hui Zhang, Zhe Wang. Discussion on prediction method of airport throughput [J].China Civil Aviation, 2008, 10 (94):67-68.