This book addresses the prediction of the Water Quality Index (WQI) at Perak River, State of Perak, Malaysia, using a fuzzy multiple linear regression model to tackle the uncertainty in the measurements of six key parameters – dissolved oxygen (DO), biological oxygen demand (BOD), chemical oxygen demand (COD), suspended solids (SS), p H value (p H) and ammoniacal nitrogen (NH3-NL). Given its scope, the book is suitable for graduate students, researchers and water quality scientists.
Table of Content
Introduction.- Fuzzy Multiple Linear Regression.- Water Quality Index (WQI).- Data Collection and Study Sites.- Water Quality Index Using Fuzzy Regression.
About the author
Samsul Ariffin Abdul Karim has been a Senior Lecturer at the Fundamental and Applied Sciences Department, Universiti Teknologi PETRONAS (UTP), Malaysia for the past eleven years. Holding a B.App.Sc., M.Sc. and Ph.D. in Computational Mathematics & Computer Aided Geometric Design (CAGD) from the Universiti Sains Malaysia (USM), he has 20 years of teaching and research experience with Mathematica and MATLAB software. His research interests include curve and surface design, geometric modeling, and wavelet applications in image compression and statistics. He has published more than 120 papers in journals and conference proceedings, as well as seven books, including two research monographs. He was the recipient of the Effective Education Delivery Award, Publication Award (Journal & Conference Paper), and UTP Quality Day Award in 2010, 2011 and 2012, respectively. He is a Certified WOLFRAM Technology Associate, Mathematica Student Level. He has published three books with Springer, including Sustaining Electrical Power Resources through Energy Optimization and Future Engineering.
Nur Fatonah Kamsani holds a Bachelor of Science (Hons.) in Computational Mathematics from the Universiti Teknologi MARA (Ui TM), Malaysia and is currently working as a Research Assistant at the Universiti Teknologi PETRONAS (UTP). Her main research interests are in modeling and data analysis.
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