JOURNAL BROWSE
Search
Advanced SearchSearch Tips
A Study on Air Demand Forecasting Using Multivariate Time Series Models
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
A Study on Air Demand Forecasting Using Multivariate Time Series Models
Hur, Nam-Kyun; Jung, Jae-Yoon; Kim, Sahm;
  PDF(new window)
 Abstract
Forecasting for air demand such as passengers and freight has been one of the main interests for air industries. This research has mainly focus on the comparison the performance between the univariate seasonal ARIMA models and the multivariate time series models. In this paper, we used real data to predict demand on international passenger and freight. And multivariate time series models are better than the univariate models based on the accuracy criteria.
 Keywords
Seasonal ARIMA model;VAR model;forecasting;air demand;
 Language
Korean
 Cited by
1.
시계열 분석을 이용한 게임 접속시간 예측 연구,강기호;김병기;

한국산업정보학회논문지, 2010. vol.15. 5, pp.63-69
2.
계절형 다변량 시계열 모형을 이용한 국제항공 여객 및 화물 수요예측에 관한 연구,윤지성;허남균;김삼용;허희영;

Communications for Statistical Applications and Methods, 2010. vol.17. 3, pp.473-481 crossref(new window)
3.
관광 수요 예측 모형의 계절효과에 대한 연구,김삼용;이주형;

응용통계연구, 2011. vol.24. 1, pp.93-102 crossref(new window)
4.
관광 수요를 위한 결합 예측 모형에 대한 연구,손흥구;하명호;김삼용;

응용통계연구, 2012. vol.25. 2, pp.251-259 crossref(new window)
5.
Performance Evaluation of Time Series Models using Short-Term Air Passenger Data,;;

응용통계연구, 2012. vol.25. 6, pp.917-923 crossref(new window)
6.
계절 ARIMA 모형을 이용한 여객수송수요 예측: 중앙선을 중심으로,김범승;

한국철도학회논문집, 2014. vol.17. 4, pp.307-312 crossref(new window)
7.
경제적 투자효과의 예측 정확도 향상을 위한 실질할인율 분석,이치주;이을범;

한국건설관리학회논문집, 2015. vol.16. 1, pp.101-109 crossref(new window)
8.
ARMA(p, q) 모형에서 멱변환의 재변환에 관한 연구 - 모의실험을 중심으로,강전훈;신기일;

응용통계연구, 2015. vol.28. 3, pp.511-527 crossref(new window)
1.
A Study on the Tourism Combining Demand Forecasting Models for the Tourism in Korea, Korean Journal of Applied Statistics, 2012, 25, 2, 251  crossref(new windwow)
2.
Forecasting Passenger Transport Demand Using Seasonal ARIMA Model - Focused on Joongang Line, Journal of the Korean society for railway, 2014, 17, 4, 307  crossref(new windwow)
3.
A Study on the Seasonal Effects of the Tourism Demand Forecasting Models, Korean Journal of Applied Statistics, 2011, 24, 1, 93  crossref(new windwow)
4.
Re-Transformation of Power Transformation for ARMA(p, q) Model - Simulation Study, Korean Journal of Applied Statistics, 2015, 28, 3, 511  crossref(new windwow)
5.
Analysis on Real Discount Rate for Prediction Accuracy Improvement of Economic Investment Effect, Korean Journal of Construction Engineering and Management, 2015, 16, 1, 101  crossref(new windwow)
6.
Performance Evaluation of Time Series Models using Short-Term Air Passenger Data, Korean Journal of Applied Statistics, 2012, 25, 6, 917  crossref(new windwow)
 References
1.
곽우심 (2006). <수요예측 이론에 의한 여객운송수요 적용사례 연구>, 한국항공대학교 경영대학원 석사학위논문

2.
백승한, 김성수 (2008). 제주-내륙간 국내선 항공여객 수요 모형 및 탄력성의 추정, <대한교통학회지>, 26, 51-63

3.
서진철 (2008). <공적분모형과 벡터자기회귀모형에서의 차분에 대한 비교연구>, 중앙대학교 대학원 석사학위논문

4.
진학기 (2002). <시계열자료를 이용한 국제 항공화물 수요예측>, 한양대학교 대학원 석사학위논문

5.
허희영 (1995). 항공기 수요예측 사례연구;100인승급 항공기의 국내수요를 중심으로, <한국항공운항학회지>, 3, 49-79

6.
Box, G. E. P. and Jenkins, G. M. (1976). Time Series Analysis Forecasting and Control, 1st, Holden-Day Inc, San Fransisco

7.
Johansen, S. (1988). Statistical analysis of co-integration vectors, Journal of Economic Dynamics and Control, 12, 231-254 crossref(new window)

8.
Tiao, G. C. and Box, G. E. P. (1981). Modeling multiple times series with applications, Journal of the American Statistical Association, 76, 802-816 crossref(new window)