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Neural network prediction for efficient waste management in Malaysia

Yusoff, Siti Hajar and Abdullah Din, Ummi Nur Kamilah and Mansor, Hasmah and Midi, Nur Shahida and Zaini, Syasya Azra (2018) Neural network prediction for efficient waste management in Malaysia. Indonesian Journal of Electrical Engineering and Computer Science, 12 (2). pp. 738-747. ISSN 2502-4752

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Maintaining current municipal solid waste management (MSWM) for the next ten years would not be efficient anymore as it has brought many environmental issues such as air pollution. This project has proposed Artificial Neural Network (ANN) based prediction algorithm that can forecast Solid Waste Generation (SWG) based on population growth factor. This study uses Malaysian population as sample size and the data for weight is acquired via authorized Malaysia statistics’ websites. All data will be normalized in the pre-processing stage before proceeding to the prediction using Visual Gene Developer. This project evaluated the performance using R2 value. Two hidden layers with ten and five nodes were used respectively. The result portrayed that there will be an increase of 29.03 percent of SWG in year 2031 compared to 2012. The limitation to this study is that the data was not based on real time as it was restricted by the government.

Item Type: Article (Journal)
Additional Information: 7329/66226
Uncontrolled Keywords: MSWM in Malaysia; prediction of SWG; ANN prediction algorithm; visual gene developer; R2 value
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK4001 Applications of electric power
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering
Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Depositing User: dr siti hajar yusoff
Date Deposited: 12 Sep 2018 10:01
Last Modified: 12 Sep 2018 10:01
URI: http://irep.iium.edu.my/id/eprint/66226

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