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Title: The behaviour of PM10 and ozone in Malaysia through non-linear dynamical systems

Prediction of ozone (O3) and PM10 is very important as both these air pollutants affect human health, human activities and more. Short-term forecasting of air quality is needed as preventive measures and effective action can be taken. Therefore, if it is detected that the ozone data is of a chaotic dynamical systems, a model using the nonlinear dynamic from chaos theory data can be made and thus forecasts for the short term would be more accurate. This study uses two methods, namely the 0-1 Test and Lyapunov Exponent. In addition, the effect of noise reduction on the analysis of time series data will be seen by using two smoothing methods: Rectangular methods and Triangle methods. At the end of the study, recommendations were made to get better results in the future.
Authors:
 [1] ;  [2] ;  [3]
  1. Pusat Pengajian Matematik, Fakulti Sains Komputer & Matematik Universiti Teknologi MARA Kampus Seremban, 70300 Negeri Sembilan (Malaysia)
  2. Pengajian Matematik, Fakulti Sains Komputer & Matematik Universiti Teknologi MARA Kampus Jasin, 77000 Melaka (Malaysia)
  3. Pusat Pengajian Sains Matematik, Fakulti Sains & Teknologi Universiti Kebangsaan Malaysia, 43650 Selangor (Malaysia)
Publication Date:
OSTI Identifier:
22492498
Resource Type:
Journal Article
Resource Relation:
Journal Name: AIP Conference Proceedings; Journal Volume: 1682; Journal Issue: 1; Conference: SKSM22: 22. National symposium on mathematical sciences - Strengthening research and collaboration of mathematical sciences in Malaysia, Selangor (Malaysia), 24-26 Nov 2014; Other Information: (c) 2015 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; 54 ENVIRONMENTAL SCIENCES; AIR POLLUTION; AIR QUALITY; CHAOS THEORY; FORECASTING; LYAPUNOV METHOD; MALAYSIA; NOISE; NONLINEAR PROBLEMS; OZONE; PUBLIC HEALTH; TIME-SERIES ANALYSIS