Predicting Smoke Emission From Palm Oil Mill Using Artificial Neural Networks

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 boil...

詳細記述

書誌詳細
第一著者: Yusoff, Ahmad Razlan
フォーマット: 学位論文
言語:英語
出版事項: 2002
主題:
オンライン・アクセス:http://eprints.usm.my/60756/
その他の書誌記述
要約: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.