Irrigation & Drainage Systems Engineering

ISSN: 2168-9768

Open Access

Mohamed Hamed

Canadian International College,

  • Research Article
    Application of Surface Water Quality Classification Models Using Principal Components Analysis and Cluster Analysis
    Author(s): Mohamed HamedMohamed Hamed

    Water quality monitoring has one of the highest priorities in surface water protection policy. Many techniques and methods focus in analyzing the concealing parameters that determine the variance of observed water quality of various source points. A considerable proportion of them mainly depend on statistical methods, multivariate statistical techniques in particular. In the present study, the use of multivariate techniques is required to reduce the large variables number of Nile River water quality upstream Cairo Drinking Water Plants (CDWPs) and determination of relationships among them for easy and robust evaluation. By means of multivariate statistics of principal components analysis (PCA), Fuzzy C-Means (FCM) and K-means algorithm for clustering analysis, this study attempted to determine the major dominant factors responsible for the variations of Nile River water quality.. Read More»

    Abstract PDF

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