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| Abstract : Universiti Pendidikan Sultan Idris |
| The aim of this study is to model the temperature time series at Malaysian high population area during dry season through chaos theory. The selected high population area is Shah Alam located in Selangor state of Malaysia. Chaos theory modelling is categorized into two parts namely analysis and prediction. Analysis by the phase space plot showed that the nature of the observed temperature time series is chaos. Hence, the time series is predicted via the chaotic model. Results from the chaotic model showed that the temperature time series is well predicted with Pearson correlation coefficient near to 1. The result is compared with the traditional method of autoregressive linear model. Based on the computed values of average absolute error, root mean squared error and Pearson correlation coefficient, the chaotic model is found better in predicting temperature time series at Shah Alam area during dry season. This indicates that the chaos theory is applicable for temperature time series at Malaysian high population area. This finding is expected to facilitate stakeholders such as Malaysian Meteorological Department and Department of Environment Malaysia in managing temperature and climate change problem. ? 2021 by authors, all rights reserved. |
| References |
Abarbanel, H. D. I. (1996). Analysis of Observed Chaotic Data, Retrieved from www.scopus.com Abd Hamid, N. Z., Md Noorani, M. S., & Adenan, N. H. (2017). Chaotic analysis and short-term prediction of ozone pollution in malaysian urban area. Paper presented at the Journal of Physics: Conference Series, , 890(1) doi:10.1088/1742-6596/890/1/012157 Retrieved from www.scopus.com Abdullah, N., Shuhaimi, S., Toh, Y., Shafee, A., & Maznorizan, M. (2011). The study of seasonal variation of PM10 concentration in peninsular, sabah and sarawak. Malaysian Meteorological Department, 9, 1-28. Retrieved from www.scopus.com Adenan, N. H., Hamid, N. Z. A., Mohamed, Z., & Noorani, M. S. M. (2017). A pilot study of river flow prediction in urban area based on phase space reconstruction. Paper presented at the AIP Conference Proceedings, , 1870 doi:10.1063/1.4995843 Retrieved from www.scopus.com Adenan, N. H., & Noorani, M. S. M. (2014). Nonlinear prediction of river flow in different watershed acreage. KSCE Journal of Civil Engineering, 18(7), 2268-2274. doi:10.1007/s12205-014-0646-4 Adenan, N. H., & Noorani, M. S. M. (2015). Predicting time series data at floodplain area using chaos approach. [Peramalan data siri masa aliran sungai di dataran banjir dengan menggunakan pendekatan kalut] Sains Malaysiana, 44(3), 463-471. doi:10.17576/jsm-2015-4403-19 Adiwijaya, Wisesty, U. N., & Nhita, F. (2014). Study of line search techniques on the modified backpropagation for forecasting of weather data in indonesia. Far East Journal of Mathematical Sciences, 86(2), 139-148. Retrieved from www.scopus.com Berndtsson, R., Sivakumar, B., Olsson, J., & Graham, L. (2011). Dynamic characteristics of temperature, precipitation and runoff to the baltic sea. Vatten, 67, 185-192. Retrieved from www.scopus.com Dutta, P. N., Karlo, T., & Dutta, P. (2017). Some features of surface air temperature: A statistical viewpoint. Environ.Ecol.Res., 5(5), 367-376. Retrieved from www.scopus.com Echi, I. M., Tikyaa, E. V., & Isikwue, B. C. (2015). Dynamics of daily rainfall and temperature in makurdi. Int J Sci Res, 4(7), 493-499. Retrieved from www.scopus.com Gimeno, L., García, R., Pacheco, J. M., Hernández, E., & Ribera, P. (2001). Predictability of global surface temperature by means of nonlinear analysis. Earth and Planetary Science Letters, 184(3-4), 561-565. doi:10.1016/S0012-821X(00)00329-0 Hamid, N. Z. A., & Md Noorani, M. S. (2017). New improved chaotic approach model application on forecasting ozone concentration time series. [Aplikasi model baharu penambahbaikan pendekatan kalut ke atas peramalan siri masa kepekatan ozon] Sains Malaysiana, 46(8), 1333-1339. doi:10.17576/jsm-2017-4608-20 Hamid, N. Z. A., & Noorani, M. S. M. (2014). A pilot study using chaotic approach to determine characteristics and forecasting of PM10 concentration time series. [Suatu kajian perintis menggunakan pendekatan kalut bagi pengesanan sifat dan peramalan siri masa kepekatan PM10] Sains Malaysiana, 43(3), 475-481. Retrieved from www.scopus.com Hamid, N. Z. A., & Noorani, M. S. M. (2013). An improved prediction model of ozone concentration time series based on chaotic approach. Int.J.Math.Comput.Sci.Eng., 7(11), 206-211. Retrieved from www.scopus.com Hashim, N. M. (2010). The impact of global warming trends on urban livability in malaysia: An analysis. Malaysian Journal of Society and Space, 6(2), 72-88. Retrieved from www.scopus.com Indira, P., Stephen Rajkumar Inbanathan, S., Samuel Selvaraj, R., & Antony Suresh, A. (2016). Forecasting daily maximum temperature of chennai using nonlinear prediction approach. Indian Journal of Science and Technology, 9(39) doi:10.17485/ijst/2016/v9i39/100776 Jayawardena, A. W. (1997). Runoff forecasting using a local approximation method. IAHS-AISH Publication, (239), 167-171. Retrieved from www.scopus.com Keywood, M. D., Ayers, G. P., Gras, J. L., Boers, R., & Leong, C. P. (2003). Haze in the klang valley of malaysia. Atmospheric Chemistry and Physics, 3(3), 591-605. doi:10.5194/acp-3-591-2003 Lorenz, E. N. (1963). Deterministic nonperiodic flow. J.Atmos.Sci., 20, 130-141. Retrieved from www.scopus.com Maji, S., Ahmed, S., Siddiqui, W. A., & Ghosh, S. (2017). Short term effects of criteria air pollutants on daily mortality in delhi, india. Atmospheric Environment, 150, 210-219. doi:10.1016/j.atmosenv.2016.11.044 Millán, H., Ghanbarian-Alavijeh, B., & García-Fornaris, I. (2010). Nonlinear dynamics of mean daily temperature and dewpoint time series at babolsar, iran, 1961-2005. Atmospheric Research, 98(1), 89-101. doi:10.1016/j.atmosres.2010.06.001 Norela, S., Saidah, M. S., & Mahmud, M. (2013). Chemical composition of the haze in malaysia 2005. Atmospheric Environment, 77, 1005-1010. doi:10.1016/j.atmosenv.2013.05.024 Payus, C., Abdullah, N., & Sulaiman, N. (2013). Airborne particulate matter and meteorological interactions during the haze period in malaysia. International Journal of Environmental Science and Development, 4(4), 398-402. Retrieved from www.scopus.com Samuel, O., Dominic, N., & Patrick, O. (2020). Effects of seasonal variation on the physicochemical characteristics of iyifeyi stream in ugwobi abbi, enugu state nigeria. Environment and Ecology Research, 8(3), 76-84. doi:10.13189/eer.2020.080303 Sivakumar, B. (2002). A phase-space reconstruction approach to prediction of suspended sediment concentration in rivers. Journal of Hydrology, 258(1-4), 149-162. doi:10.1016/S0022-1694(01)00573-X Sprott, J. C. (2003). Chaos and Time-Series Analysis, Retrieved from www.scopus.com Suresh Antony, A., & Selvaraj, R. S. (2017). A complete chaotic analysis on daily mean surface air temperature and humidity data of chennai. J.Ind.Geophys.Union, 21(4), 277-284. Retrieved from www.scopus.com Viola, F. M., Paiva, S. L. D., & Savi, M. A. (2010). Analysis of the global warming dynamics from temperature time series. Ecological Modelling, 221(16), 1964-1978. doi:10.1016/j.ecolmodel.2010.05.001 |
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