Browsing by Author "Azami Zaharim"

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    Analisis Data Rawak terikan-Lesu Menggunakan Kaedah Statistik Purata-Tergerak
    (Penerbit UKM) Azami Zaharim; Mohammad Darahim Ibrahim; Shahrum Abdullah
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    Analyzing the East Coast Malaysia Wind Speed Data
    (International Energy and Environment Foundation (IEEF), 2009) Siti Khadijah Najid; Azami Zaharim; Ahmad Mahir Razali; Mohd Said Zainol; Kamarulzaman Ibrahim; Kamaruzzaman Sopian
    Recently, wind energy conversion is also given a serious consideration in Malaysia. Since Malaysia lies in the equatorial region and its climate is governed by the monsoons, the potential for wind energy generation in Malaysia is very much depends on the availability of the wind resource that varies with specific location. In the present study, the wind energy potential of the location is statistically analyzed based on wind speed data, measured over two years period. The probability distributions are derived from the wind speed data and their distributional parameters are identified. Three types of probability distributions have been used to estimate the wind energy potential in Kuala Terengganu, east Malaysia.
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    Structure of the atmospheric surface layer over an industrialized equatorial area
    (Elsevier, 2008) Yusri Bin Yusup; Wan Ramli Wan Daud; Azami Zaharim; Meor Zainal Meor Talib
    This paper is written to report observations of the structure of the atmospheric surface layer over a coastal industrialized equatorial area. The observations were recorded at Prai Industrial Park, Penang (5° 22'N, 100° 23'E) a relatively simple terrain area during the south-west monsoon season in the period of three months using slow response systems.
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    Water level data modeling with bilinear time series analysis
    (Universiti Malaya, 2006) Mohd. Sahar Yahya; Ibrahim Mohamed; Azami Zaharim; Mohammad Said Zainol
    In the literature, many time series data, such as the economic and hydrological data, show various nonlinearity characteristics. The Keenan's test and F-test are employed in identifying a nonlinear data set. This article looks at the modeling of nonlinear time series data using bilinear time series model. The model is an extension of autoregressive model such that an extra term representing the bilinear characteristic is introduced. The estimation of bilinear models is obtained using nonlinear least squares method. As an illustration, analysis on water level of Sungai Kelantan using the above method is presented.