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...
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| Format: | Thesis |
| Language: | English |
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2002
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| Online Access: | http://eprints.usm.my/60756/ http://eprints.usm.my/60756/1/Pages%20from%20Ahmad%20Razlan.pdf |
| _version_ | 1848884531172474880 |
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| author | Yusoff, Ahmad Razlan |
| author_facet | Yusoff, Ahmad Razlan |
| author_sort | Yusoff, Ahmad Razlan |
| building | USM Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-15T19:08:11Z |
| format | Thesis |
| id | usm-60756 |
| institution | Universiti Sains Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T19:08:11Z |
| publishDate | 2002 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | usm-607562025-03-22T00:12:35Z http://eprints.usm.my/60756/ Predicting Smoke Emission From Palm Oil Mill Using Artificial Neural Networks Yusoff, Ahmad Razlan TJ1-1570 Mechanical engineering and machinery 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. 2002-11 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/60756/1/Pages%20from%20Ahmad%20Razlan.pdf Yusoff, Ahmad Razlan (2002) Predicting Smoke Emission From Palm Oil Mill Using Artificial Neural Networks. Masters thesis, Universiti Sains Malaysia. |
| spellingShingle | TJ1-1570 Mechanical engineering and machinery Yusoff, Ahmad Razlan Predicting Smoke Emission From Palm Oil Mill Using Artificial Neural Networks |
| title | Predicting Smoke Emission From Palm Oil Mill Using Artificial
Neural Networks |
| title_full | Predicting Smoke Emission From Palm Oil Mill Using Artificial
Neural Networks |
| title_fullStr | Predicting Smoke Emission From Palm Oil Mill Using Artificial
Neural Networks |
| title_full_unstemmed | Predicting Smoke Emission From Palm Oil Mill Using Artificial
Neural Networks |
| title_short | Predicting Smoke Emission From Palm Oil Mill Using Artificial
Neural Networks |
| title_sort | predicting smoke emission from palm oil mill using artificial
neural networks |
| topic | TJ1-1570 Mechanical engineering and machinery |
| url | http://eprints.usm.my/60756/ http://eprints.usm.my/60756/1/Pages%20from%20Ahmad%20Razlan.pdf |