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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

Air passengers, DES model, Hybrid model, Rough set theory, Time series forecasting.

Cite This Article

. , "Short-term forecasting of air passengers based on the hybrid rough set and the double exponential smoothing model," Intelligent Automation & Soft Computing, vol. 25, no.1, pp. 1–14, 2019.



This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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