Predicting Smoke Emission From Palm Oil Mill Using Artificial Neural Networks

Yusoff, Ahmad Razlan (2002) Predicting Smoke Emission From Palm Oil Mill Using Artificial Neural Networks. Masters thesis, Universiti Sains Malaysia.

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Abstract

Malaysia produces 50 % of the total quantity of palm oil produced in the world and this makes it the largest palm oil producer in the world. Palm oil is produced in palm oil mills, which have their captive steam power plants and these plants use palm oil waste (shell and fibre) as fuel for the boilers. Unfortunately, the combustion products of these materials cause severe atmospheric pollutions. According to a survey in 1999, only 76% of the palm oil mills in Malaysia meet the regulation of Department of Environment (DOE) regarding the emission. The emission released through the chimney can be monitored by modeling its process of input (in fuel, turbine, boiler) and output of the pollutants. Modeling the emission from the palm oil mill boiler based on Artificial Neural Networks (ANN) is used in this research.

Item Type:	Thesis (Masters)
Subjects:	T Technology > TJ Mechanical engineering and machinery > TJ1-1570 Mechanical engineering and machinery
Divisions:	Bahagian Hal Ehwal Pembangunan Pelajar & Alumni (Student Development Affairs & Alumni Division) > Majlis Penghuni Desasiswa Tekun
Depositing User:	Mr Aizat Asmawi Abdul Rahim
Date Deposited:	26 Jun 2024 00:48
Last Modified:	26 Jun 2024 00:48
URI:	http://eprints.usm.my/id/eprint/60756

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