Emission control in palm oil mills using artificial neural network and genetic algorithm

被引：36
作者：
Ahmad, AL
Azid, IA
Yusof, AR
Seetharamu, KN
机构：
[1] Univ Sains Malaysia, Sch Chem Engn, Nibong Tebal 14300, Pulau Pinang, Malaysia
[2] Univ Sains Malaysia, Sch Mech Engn, Nibong Tebal 14300, Pulau Pinang, Malaysia
来源：
COMPUTERS & CHEMICAL ENGINEERING | 2004年 / 28卷 / 12期
关键词：
emission control; neural networks; optimization; genetic algorithms;
D O I：
10.1016/j.compchemeng.2004.07.034
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
The present study utilized a combination of artificial neural network (ANN) and genetic algorithms (GA) to optimize the release of emission from the palm oil mill. A model based on ANN is developed from the actual data taken from the palm oil mill. The predicted data agree well with the actual data taken. GA is then employed to find the optimal operating conditions so that the overlimit release of emission is reduced to the allowable limit. (C) 2004 Elsevier Ltd. All rights reserved.
引用
收藏
页码：2709 / 2715
页数：7
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