STUDY ON PREDICTION OF SATURATES OF VACUUM GAS OIL (VGO) BY USING ARTIFICIAL NEURAL NETWORKS

被引：0
|
作者：
Sun, Renjin [1 ]
Wang, Shouchun [1 ]
Zhao, Suoqi [1 ]
机构：
[1] China Univ Petr, Beijing 102249, Peoples R China
来源：
ICIM 2008: PROCEEDINGS OF THE NINTH INTERNATIONAL CONFERENCE ON INDUSTRIAL MANAGEMENT | 2008年
关键词：
VGO saturates; base physical property; artificial neural network; prediction;
D O I：
暂无
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
Prediction on saturates of vacuum gas oil with 5 properties, average boiling point, density at 20 degrees C, carbon residue, molecular weight and refractive index at 70 degrees C, using neural network was developed. Comparing the calculating data with the experimental data, the average relative deviations. of VGO saturates were 4.97%. Six testing samples which have been trained were predicted by using this model and the average relative deviation of the prediction were 3.91 %. The accuracy of the prediction model was promising and it is available in preliminary prediction of basic physical properties of crude oil.
引用
收藏
页码：805 / 811
页数：7
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