Sains Malaysiana 43(3)(2014):
475–481
Suatu
Kajian Perintis Menggunakan Pendekatan Kalut bagi Pengesanan Sifat
dan
Peramalan
Siri Masa Kepekatan PM
(A Pilot Study using Chaotic Approach to Determine Characteristics
and Forecasting of PM10 Concentration Time
Series)
NOR ZILA ABD HAMID1* & MOHD
SALMI
MD
NOORANI2
1Jabatan Matematik, Fakulti Sains dan Matematik,
Universiti Pendidikan Sultan Idris
35900 Tanjung Malim, Perak, Malaysia
2Pusat Pengajian Sains Matematik, Fakulti
Sains dan Teknologi
43600 Bangi, Selangor, Malaysia
Diserahkan: 16 Mei 2013/Diterima: 15 Julai 2013
ABSTRAK
Peramalan kepekatan PM10 adalah penting kerana menyedut udara
mengandungi PM10 boleh membawa kepada pelbagai penyakit kronik
seperti kanser dan bronkitis. Kajian ini merupakan kajian perintis
menggunakan pendekatan kalut bagi meramal PM10 di Malaysia. Data yang dikaji adalah siri masa
PM10 mengikut
jam yang dicerap di stesen penanda aras yang terletak dalam daerah
Jerantut di negeri Pahang. Pendekatan kalut mempunyai dua langkah
iaitu pembinaan semula ruang fasa dan proses peramalan. Melalui
langkah 1, ruang fasa pelbagai-matra dibina menggunakan parameter
masa tunda τ = 7 dan matra pembenaman m = 4 yang masing-masing
diperoleh daripada kaedah maklumat purata bersama dan kaedah Cao.
Hasil daripada gambarajah ruang fasa dan juga plot parameter kaedah
Cao mempamerkan bahawa data bersifat kalut. Melalui langkah 2, peramalan
satu jam ke hadapan selama sebulan siri masa PM10 dijalankan menggunakan
kaedah penghampiran setempat. Nilai pekali kolerasi antara data
ramalan dan data sebenar hanyalah 0.5692. Namun, graf perbandingan
menunjukkan bahawa data ramalan adalah hampir dengan data sebenar
dengan nilai ralat punca min kuasa dua peramalan adalah 7.6814.
Ini menunjukkan kesesuaian penggunaan kaedah penghampiran setempat
dalam meramal siri masa PM10 dan ia merupakan petanda positif bahawa pendekatan
kalut ini boleh diguna pakai ke atas siri masa bahan pencemar di
Malaysia.
Kata kunci: Kaedah penghampiran setempat; Malaysia; pendekatan
kalut; peramalan; PM10
ABSTRACT
Forecasting of PM10 concentration is important as breathing
air containing PM10 can lead to chronic diseases such as
cancer and bronchitis. This study is a pilot study using chaotic
approach to forecast PM10 in Malaysia. Studied data is a time series of
observed hourly PM10 at benchmark station located in the district
of Jerantut in Pahang state. Chaotic approach has two steps, namely
the phase space reconstruction and the forecasting process. Through
step 1, multi-dimensional phase space is reconstructed using the
parameters of the delay time τ = 7 and embedding dimension
m = 4, respectively, derived from the average mutual information
and Cao method. The results from the phase space diagram and parameter
plot of Cao method demonstrates that the data are chaotic. Through
step 2, 1 h ahead forecasting for a month PM10 time series is carried
out using the local approximation method. Correlation coefficient
value between the actual and forecasted data is only 0.5692. However,
comparison graphs show that forecasted data are close to the actual
data with root mean square error value 7.6814. This demonstrates
the suitability of the local approximation method to forecast the
time series of PM10 and it's a positive sign
that this chaotic approach is applicable to the time series of pollutants
in Malaysia.
Keywords: Chaotic approach; forecast; local
approximation method; Malaysia; PM10
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*Pengarang
untuk surat-menyurat; email: nor_zila@yahoo.com
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