Using grey Holt–Winters model to predict the air quality index for cities in China

Lifeng Wu, Xiaohui Gao, Yanli Xiao (), Sifeng Liu and Yingjie Yang
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Lifeng Wu: Hebei University of Engineering
Xiaohui Gao: Hebei University of Engineering
Yanli Xiao: Hebei University of Engineering
Sifeng Liu: De Montfort University
Yingjie Yang: De Montfort University

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2017, vol. 88, issue 2, No 18, 1003-1012

Abstract: Abstract The randomness, non-stationarity and irregularity of air quality index series bring the difficulty of air quality index forecasting. To enhance forecast accuracy, a novel model combining grey accumulated generating technique and Holt–Winters method is developed for air quality index forecasting in this paper. The grey accumulated generating technique is utilized to handle non-stationarity of random and irregular data series and Holt–Winters method is employed to deal with the seasonal effects. To verify and validate the proposed model, two monthly air quality index series from January in 2014 to December in 2016 collected from Shijiazhuang and Handan in China are taken as the test cases. The experimental results show that the proposed model is remarkably superior to conventional Holt–Winters method for its higher forecast accuracy.

Keywords: Air quality index forecasting; Holt–Winters method; Grey accumulated generating technique; Handan; Shijiazhuang (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (7)

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DOI: 10.1007/s11069-017-2901-8

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