Artificial Neural Network-Based Model for Quality Estimation of Refined Palm Oil

被引：0
|
作者：
Sulaiman, Nurul Sulaiha [2 ]
Yusof, Khairiyah Mohd [1 ]
机构：
[1] Univ Teknol Malaysia, Ctr Engn Educ, Johor Baharu 81310, Malaysia
[2] Univ Teknol Malaysia, Fac Chem Engn, Dept Chem Engn, Johor Baharu 81310, Malaysia
来源：
2015 15TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS (ICCAS) | 2015年
关键词：
Artificial Neural Network; Prediction Model; Product Quality System; Palm Oil;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The goal of this study is to develop an accurate artificial neural network ( ANN)-based model to predict significant quality of refined palm oil which is Free Fatty Acid ( FFA) content. The variables; FFA content, Iodine Value ( IV), moisture content, bleaching earth and citric acid dosage as well as the pressure and temperature of the deodorizer is used to build the ANN prediction model. A feed forward neural network was designed using a back-propagation training algorithm. Comparison of ANN predicted result with industrial data was made. It is proven in this study that ANN can be used to estimate the quality of refined palm oil. Therefore, the model can be further implemented in palm oil refinery plant as the prediction system of the refined oil quality.
引用
收藏
页码：1324 / 1328
页数：5
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