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Water quality index prediction using...

Kamsani, Nur Fatonah.

Water quality index prediction using multiple linear fuzzy regression modelcase study in Perak River, Malaysia /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Water quality index prediction using multiple linear fuzzy regression modelby Samsul Ariffin Abdul Karim, Nur Fatonah Kamsani.
其他題名:	case study in Perak River, Malaysia /
作者:	Karim, Samsul Ariffin Abdul.
其他作者:	Kamsani, Nur Fatonah.
出版者:	Singapore :Springer Singapore :2020.
面頁冊數:	xii, 55 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Water qualityCase studies.Statistical methodsMalaysia
電子資源:	https://doi.org/10.1007/978-981-15-3485-0
ISBN:	9789811534850$q(electronic bk.)

Water quality index prediction using multiple linear fuzzy regression modelcase study in Perak River, Malaysia /
Karim, Samsul Ariffin Abdul.

Water quality index prediction using multiple linear fuzzy regression modelcase study in Perak River, Malaysia /[electronic resource] :by Samsul Ariffin Abdul Karim, Nur Fatonah Kamsani. - Singapore :Springer Singapore :2020. - xii, 55 p. :ill., digital ;24 cm. - SpringerBriefs in water science and technology,2194-7244. - SpringerBriefs in water science and technology..

Introduction -- Fuzzy Multiple Linear Regression -- Water Quality Index (WQI) -- Data Collection and Study Sites -- Water Quality Index Using Fuzzy Regression.

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), pH value (pH) and ammoniacal nitrogen (NH3-NL) Given its scope, the book is suitable for graduate students, researchers and water quality scientists.

ISBN: 9789811534850$q(electronic bk.)

Standard No.: 10.1007/978-981-15-3485-0doiSubjects--Topical Terms:

862506
Water quality
--Statistical methods--Malaysia--Case studies.

LC Class. No.: TD370 / .K375 2020

Dewey Class. No.: 363.61

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