Open Access
ARTICLE
Short-term Forecasting of Air Passengers Based on the Hybrid Rough Set and the Double Exponential Smoothing Model
Haresh Kumar Sharma, Kriti Kumari, Samarjit Kar
1 Department of Mathematics, National Institute of Technology Durgapur, West Bengal 713 209, India
2 Department of Mathematics and Statistics, Banasthali Vidyapith, Jaipur, Rajasthan, 304022, India
2 kriti.kri89@gmail.com, 1 kar_s_k@yahoo.com
* Corresponding Author: Haresh Kumar Sharma,
Intelligent Automation & Soft Computing 2019, 25(1), 1-14. https://doi.org/10.31209/2018.100000036
Abstract
This article focuses on the use of the rough set theory in modeling of time series
forecasting. In this paper, we have used the double exponential smoothing (DES)
model for forecasting. The classical DES model has been improved by using the
rough set technique. The improved double exponential smoothing (IDES) method can
be used for the time series data without any statistical assumptions. The proposed
method is applied on tourism demand of the air transportation passenger data set in
Australia and the results are compared with the classical DES model. It has been
observed that the forecasting accuracy of the proposed model is better than that of the
classical DES model.
Keywords
Cite This Article
APA Style
Sharma, H.K., Kumari, K., Kar, S. (2019). Short-term forecasting of air passengers based on the hybrid rough set and the double exponential smoothing model. Intelligent Automation & Soft Computing, 25(1), 1-14. https://doi.org/10.31209/2018.100000036
Vancouver Style
Sharma HK, Kumari K, Kar S. Short-term forecasting of air passengers based on the hybrid rough set and the double exponential smoothing model. Intell Automat Soft Comput . 2019;25(1):1-14 https://doi.org/10.31209/2018.100000036
IEEE Style
H.K. Sharma, K. Kumari, and S. Kar "Short-term Forecasting of Air Passengers Based on the Hybrid Rough Set and the Double Exponential Smoothing Model," Intell. Automat. Soft Comput. , vol. 25, no. 1, pp. 1-14. 2019. https://doi.org/10.31209/2018.100000036