Forecasting Through the Chaotic Approach on Carbon Monoxide Time Series in Industrial Area

Peramalan Melalui Pendekatan Kalut ke atas Siri Masa Karbon Monoksida di Kawasan Perindustrian

  • Khairunnisa Che Jusoh Jabatan Matematik, Fakulti Sains dan Matematik, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
  • Nor Zila Abd Hamid Jabatan Matematik, Fakulti Sains dan Matematik, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
  • Syafruddin Side Jabatan Matematik, Universitas Negeri Makassar, Makassar, Indonesia
Keywords: Forecasting, industrial area, Cao method, carbon monoxide, local linear approximation method

Abstract

This study focuses on forecasting and analyzing the concentration of carbon monoxide (CO) in one of the Malaysian Industrial area namely Seberang Perai using a chaotic approach. Before forecasting process, the time series are tested in advance to determine whether or not the nature is chaotic. Through the Cao method, chaotic dynamic present in the CO times series. Therefore, the forecasting model through the local linear approximation is constructed for forecasting purpose. The result shows that the correlation value is 0.9032 which is near to one. This excellent forecasting result shows that the local linear approximation method can be used to forecast the concentration of CO. In conclusion, the chaotic approach has successfully analyzed and forecasted the CO time series in the Seberang Perai industrial area. These findings are expected to help stakeholder to manage CO pollution in Malaysian Industrial area.

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Published
2021-02-20
How to Cite
Che Jusoh, K., Abd Hamid, N. Z., & Side, S. (2021). Forecasting Through the Chaotic Approach on Carbon Monoxide Time Series in Industrial Area. Journal of Science and Mathematics Letters, 9, 55-62. https://doi.org/10.37134/jsml.vol9.sp.7.2021