The prediction of blue water footprint at Semambu water treatment plant by means of Artificial Neural Networks (ANN) and Support Vector Machine (SVM) models Machine (SVM) models.

• Main Authors: Syazwan Nizam, Moni, Edriyana, Abd Aziz, Anwar P. P., Abdul Majeed, Marlinda, Malek
• Format: Article
• Language: English; English
• Published: Elsevier Ltd. 2021
• Subjects: TA Engineering (General). Civil engineering (General); TJ Mechanical engineering and machinery
• Online Access: http://umpir.ump.edu.my/id/eprint/32928/1/The%20prediction%20of%20blue%20water%20footprint%20at%20Semambu%20water%20treatment%20plant%20.pdf; http://umpir.ump.edu.my/id/eprint/32928/2/The%20prediction%20of%20blue%20water%20footprint%20at%20Semambu%20water%20treatment%20plant.pdf; http://umpir.ump.edu.my/id/eprint/32928/; https://doi.org/10.1016/j.pce.2021.103052; https://doi.org/10.1016/j.pce.2021.103052

The prediction of the blue water footprint in water services such as in water treatment plants (WTPs) is non-trivial to water resource management. Currently, the sustainability of water resources is of great concern globally, particularly in addressing the 6th goal of the United Nation's Sustai...