Browsing by Author "Ibrahim Mohamed"

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    Assessment of water quality parameters using multivariate analysis for Klang River basin, Malaysia
    (Springer, 2015) Ibrahim Mohamed; Faridah Othman; Adriana I. N. Ibrahim; M. E. Alaa-Eldin; Rossita M. Yunus
    This case study uses several univariate and multivariate statistical techniques to evaluate and interpret a water quality data set obtained from the Klang River basin located within the state of Selangor and the Federal Territory of Kuala Lumpur, Malaysia. The river drains an area of 1,288 km2, from the steep mountain rainforests of the main Central Range along Peninsular Malaysia to the river mouth in Port Klang, into the Straits of Malacca. Water quality was monitored at 20 stations, nine of which are situated along the main river and 11 along six tributaries.
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    Comparing Linear and Bilinear Models on Water Level for the Kelantan River in Malaysia
    (Penerbit UKM) Azami Zahrim; Ibrahim Mohamed; Mohd Sahar Yahya
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    Multivariate statistical analysis for identifying water quality and hydrogeochemical evolution of shallow groundwater in Quaternary deposits in the Lower Kelantan River Basin, Malaysian Peninsula
    (Springer, 2016) Nur Hayati Hussin; Ismail Yusoff; Wan Zakaria Wan Muhd Tahir; Ibrahim Mohamed; Adriana Irawati Nur Ibrahim; Adzhar Rambli
    A long-term hydrogeochemical data set is used in this study to evaluate the water quality and hydrogeochemical evolution of shallow groundwater in a Quaternary deposit. A multivariate statistical method, hierarchical cluster analysis (HCA), is applied to overcome the problem of a large number of data points in the integration, interpretation and representation of the results. HCA is applied to a subgroup of the hydrogeochemical data set to evaluate their usefulness to classify the groundwater bodies.
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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.