Peramalan Bahan Pencemar Ozon (O3) di Universiti Pendidikan Sultan Idris, Tanjung Malim Perak, Malaysia Mengikut Monsun dengan Menggunakan Pendekatan Kalut

Zaim, Wan Nur Afateen Binti Wan Mohd; Hamid, Nor Zila Abd

doi:10.17576/jsm-2017-4612-30

Cited by 3 publications

(4 citation statements)

References 7 publications

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“…The main reason for detecting chaotic behaviour is to develop short term prediction model [18]. There are several methods used to determine the existence of chaotic behaviour on various time series data such as phase space plot [19], correlation dimension [20] and Cao method [10]. However, this study used phase space plot in order to determine the existence of chaotic behaviour in traffic flow time series data that were observed hourly.…”

Section: Chaotic Behaviour Determination Using Phase Space Plotmentioning

confidence: 99%

Traffic Flow Prediction in Urban Area Using Inverse Approach of Chaos Theory

Adenan¹,

Karim²,

Mashuri³

et al. 2021

cea

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Traffic congestions problem could affect everyday life especially in urban area. In order to solve the issue, an excellent traffic flow prediction needs to be developed for a better traffic management. Hence, this study was conducted in order to predict traffic flow by using the data of total volume of vehicles per hour at two main roads located in urban areas namely Selangor and Kuala Lumpur, Malaysia by using application of chaos theory. Phase space reconstruction was used to determine the chaotic behaviour of the total volume of vehicles per hour data. The reconstruction of phase space involves a single variable of the total volume of vehicles per hour data to m-dimensional phase space. Meanwhile, the inverse approach as well as local linear approximation method was used to develop prediction model of the traffic flow time series data. This study found that (i) the time series data were chaotic behaviour based on the phase space plot and (ii) inverse approach can provide prediction on the traffic flow time series data besides give excellent prediction with the value of correlation coefficient more than 0.7500. Hence, inverse approach of chaos theory can develop to prediction model towards the traffic flow in urban area; thus may help the local authorities to provide good traffic management.

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Section: Chaotic Behaviour Determination Using Phase Space Plotmentioning

confidence: 99%

Traffic Flow Prediction in Urban Area Using Inverse Approach of Chaos Theory

Adenan¹,

Karim²,

Mashuri³

et al. 2021

cea

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“…Dalam kajian ini, kaedah Cao dan plot ruang fasa telah dipilih. Berdasarkan kajian-kajian lepas, kedua-dua kaedah ini sering diguna pakai dan telah berjaya membuktikan kehadiran dinamik kalut (Ruslan & Hamid 2019;Zaim & Hamid 2017& Adenan & Noorani 2015. Sekiranya siri masa bahan pencemar itu kalut, proses peramalan akan dijalankan.…”

Section: Pengenalanunclassified

Predicting Carbon Monoxide Time Series Between Different Settlements Area in Malaysia Through Chaotic Approach

Alias,

Abd Hamid,

Muhad Saleh

et al. 2021

JSML

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This research is designed to analysing and predicting the time series of Carbon Monoxide (CO) at two stations located in Petaling Jaya and Jerantut through chaotic approach. Both stations were selected to represent CO time series in the urban and rural settlements. Chaotic approach has two steps, which are to (i) detect the presence of chaotic dynamics through phase space plot and Cao method and (ii) predict the time series which is done using local linear approximation method (LLAM). Through step (i), the result from phase space plot and parameter of Cao method shown that the presence of chaotic dynamics has been detected. Therefore, the chaotic approach is used to predict the time series. While in step (ii), the results shown that the correlation coefficient value of LLAM are 0.7536 for Petaling Jaya (τ=1, =4) and 0.6946 for Jerantut (τ=1, =5) which are close to one. This shows a positive sign that chaotic approach is applicable in both types of urban and rural settlements areas. These finding are expected to help stakeholders such as Ministry of Education and Department of Environment to having a better air pollution management.

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“…Terdapat lima bahan pencemar udara utama yang dipantau oleh Jabatan Alam Sekitar Malaysia (JASM) iaitu zarah terampai (PM10), sulfur dioksida (SO2), nitrogen dioksida (NO2), ozon (O3) dan karbon monoksida (CO). Kajian sebelum ini telah dilakukan ke atas siri masa bahan pencemar O3 (Zaim & Hamid 2017;Hamid & Nooraini 2017), PM10 (Hamid & Noorani 2014) dan NO2 (Jusoh & Hamid 2019). Oleh kerana hasil peramalan ke atas siri masa O3, PM10 dan NO2 tersebut memberangsangkan, maka kajian diteruskan ke atas bahan pencemar udara CO. Menurut Yusup et.…”

Section: Pengenalanunclassified

“…Analisis dan peramalan hasil daripada aplikasi pendekatan kalut semakin berkembang dan diguna pakai dalam pelbagai bidang seperti perubatan (Kantz & Schreiber 2004), hujan (Hamid & Noorani, 2012), hidrologi (Domenico et. al, 2013;Adenan & Noorani 2015), suhu (Bahari & Hamid 2019) serta peramalan ke atas siri masa bahan pencemar O3 (Zaim & Hamid 2017;Hamid & Nooraini 2017) dan PM10 (Hamid & Noorani 2014). Pendekatan kalut ini telah membawa kejayaan dalam pemodelan pelbagai siri masa di dalam dan luar negara.…”

Section: Pengenalanunclassified

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

Che Jusoh,

Abd Hamid,

Side

2021

JSML

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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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Peramalan Bahan Pencemar Ozon (O3) di Universiti Pendidikan Sultan Idris, Tanjung Malim Perak, Malaysia Mengikut Monsun dengan Menggunakan Pendekatan Kalut

Cited by 3 publications

References 7 publications

Traffic Flow Prediction in Urban Area Using Inverse Approach of Chaos Theory

Traffic Flow Prediction in Urban Area Using Inverse Approach of Chaos Theory

Predicting Carbon Monoxide Time Series Between Different Settlements Area in Malaysia Through Chaotic Approach

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

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