Normal view MARC view ISBD view

Prediction of grey water footprint of Sungai Lembing, Bukit Sagu and Bukit Ubi water treatment plants / Siti Fazlina Mohd Suhaimi

By:

Siti Fazlina Mohd Suhaimi [author.]

Material type: Text

text
text

Media type:

unmediated
computer

Carrier type:

volume
computer disc

ISBN:

THE0008729(Local)

Subject(s):

Dissertation note: Project Paper (Bachelors of Civil Engineering) -- Universiti Malaysia Pahang – 2019 Abstract: The most important factors affecting water scarcity in local and global and the availability of fresh water resources are not only a growing world population but also an increasing water demand. From this study, the level pollution of water in Kuantan river basin is recorded according to each water treatment plant (WTP) and grey water footprint assessment was used as an approach to account the total amount of freshwater used to assimilate the pollutant‟s concentration. Hence, this study is aimed to calculate the total grey water footprint, to predict the trend of total grey water footprint and to compare the best algorithm between Artificial Neural Network (ANN) and Bayesian Networks (BN) in grey water footprint prediction at Sungai Lembing WTP, Bukit Sagu WTP and Bukit Ubi WTP in 2015 until 2017. As the end result of this study, the total grey water footprint in Sungai Lembing, Bukit Sagu and Bukit Ubi water treatment plant in Kuantan river basin is calculated. Prediction trend of total grey water footprint in three water treatment plants has able to be produced. Artificial Neural Network (ANN) algorithm is also be chosen as the best algorithm.

Tags from this library: No tags from this library for this title. Log in to add tags.

Average rating: 0.0 (0 votes)

Holdings ( 2 )
Title notes ( 4 )

Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Final Year Report	UMPLIB GAMBANG Reference	Reference	FKASA .F395 2019 r Bc. (Browse shelf(Opens below))	1	Not for loan		T000000747
Final Year Report	UMPLIB GAMBANG	Reference	CD12601 (Browse shelf(Opens below))	1	Not for loan		T000000748

Faculty of Civil Engineering and Earth Resources

Project Paper (Bachelors of Civil Engineering) -- Universiti Malaysia Pahang – 2019

Includes bibliographical references

The most important factors affecting water scarcity in local and global and the availability of fresh water resources are not only a growing world population but also an increasing water demand. From this study, the level pollution of water in Kuantan river basin is recorded according to each water treatment plant (WTP) and grey water footprint assessment was used as an approach to account the total amount of freshwater used to assimilate the pollutant‟s concentration. Hence, this study is aimed to calculate the total grey water footprint, to predict the trend of total grey water footprint and to compare the best algorithm between Artificial Neural Network (ANN) and Bayesian Networks (BN) in grey water footprint prediction at Sungai Lembing WTP, Bukit Sagu WTP and Bukit Ubi WTP in 2015 until 2017. As the end result of this study, the total grey water footprint in Sungai Lembing, Bukit Sagu and Bukit Ubi water treatment plant in Kuantan river basin is calculated. Prediction trend of total grey water footprint in three water treatment plants has able to be produced. Artificial Neural Network (ANN) algorithm is also be chosen as the best algorithm.