Hybrid seasonal ARIMA and artificial neural network in forecasting southeast Asia City Air Pollutant Index

Nur Haizum Abd Rahman, Muhammad Hisyam Lee, Suhartono, Mohd Talib Latif

Research output: Contribution to journalArticle

Abstract

The rise of air pollution has received much attention globally. As an early warning system for air quality control and management, it is important to provide precise future concentrations pollutant information. Using time series forecasting methods, the forecast of daily Air Pollutant Index (API) is presented here. The hybrid method between seasonal autoregressive integrated moving average (SARIMA) and artificial neural network (ANN) are chosen. To verify, the accuracies are measured using error magnitude approach. However, evaluation of forecasting API is also in fluenced by the health classification based on the threshold value assigned in air quality guidelines. Thus, forecast accuracies based on index value, namely as true predicted rate (TPR), false positive rate (FPR), false alarm rate (FAR) and successful index (SI) are also used for forecast validation. As shown in the results, the hybrid model performs better in both model's evaluations group used. Hence, the hybrid method must be considered in the forecasting area due to the capability to analyze real data consisting of both linear and nonlinear patterns. Besides, using the appropriate measurement in accordance to the purpose of forecasting is important to produce an accurate forecast.

Original languageEnglish
Pages (from-to)215-226
Number of pages12
JournalASM Science Journal
Volume12
Issue numberSpecial Issue 1
Publication statusPublished - 1 Jan 2019

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artificial neural network
forecasting method
early warning system
air quality
atmospheric pollution
time series
index
air pollutant
city
forecast
Southeast Asia
rate
method
evaluation

Keywords

  • Air pollutant index (API)
  • Artificial neural network
  • Forecasting evaluation
  • Hybrid
  • SARIMA

ASJC Scopus subject areas

  • General

Cite this

Hybrid seasonal ARIMA and artificial neural network in forecasting southeast Asia City Air Pollutant Index. / Rahman, Nur Haizum Abd; Lee, Muhammad Hisyam; Suhartono, ; Latif, Mohd Talib.

In: ASM Science Journal, Vol. 12, No. Special Issue 1, 01.01.2019, p. 215-226.

Research output: Contribution to journalArticle

Rahman, Nur Haizum Abd ; Lee, Muhammad Hisyam ; Suhartono, ; Latif, Mohd Talib. / Hybrid seasonal ARIMA and artificial neural network in forecasting southeast Asia City Air Pollutant Index. In: ASM Science Journal. 2019 ; Vol. 12, No. Special Issue 1. pp. 215-226.
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