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《石油科学(英文版)》 2010-01
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Design of artificial neural networks using a genetic algorithm to predict saturates of vacuum gas oil

Dong Xiucheng1,Wang Shouchun1,Sun Renjin1 and Zhao Suoqi2 1 School of Business Administration,China University of Petroleum,Beijing 102249,China 2 School of Chemical Science and Engineering,China University of Petroleum,Beijing 102249,China  
Accurate prediction of chemical composition of vacuum gas oil(VGO) is essential for the routine operation of refi neries. In this work,a new approach for auto-design of artificial neural networks(ANN) based on a genetic algorithm(GA) is developed for predicting VGO saturates. The number of neurons in the hidden layer,the momentum and the learning rates are determined by using the genetic algorithm. The inputs for the artif icial neural networks model are f ive physical properties,namely,average boiling point,density,molecular weight,viscosity and refractive index. It is verified that the genetic algorithm could fi nd the optimal structural parameters and training parameters of ANN. In addition,an artificial neural networks model based on a genetic algorithm was tested and the results indicated that the VGO saturates can be effi ciently predicted. Compared with conventional artificial neural networks models,this approach can improve the prediction accuracy.
【CateGory Index】: TE622.1
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【Citations】
Chinese Journal Full-text Database 2 Hits
1 Sun Renjin Wang Shouchun Zhao Suoqi(China University of Petroleum,Beijing,102249,China);Study on prediction of sour vacuum gas oil (VGO) saturates by using artificial neural networks[J];Computers and Applied Chemistry;2008-11
2 Liu Sibin1,2,Tian Songbai1,Liu Yingrong1,Wang Jing1(1.Research Institute of Petroleum Processing,Beijing 100083;2.SINOPEC Jingmen Company);STUDY ON THE PREDICTION OF HYDROCARBON TYPE COMPOSITIONS OF VGO BASED ON ITS CONVENTIONAL CHARACTERISTICS[J];Petroleum Processing and Petrochemicals;2007-09
【Secondary Citations】
Chinese Journal Full-text Database 4 Hits
1 Wang Peipei Song Xiaofeng Yang Ping Department of Biomedical Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing,210016,Jiangsu,China;Modified internal recurrent neural network and its application in QSAR[J];Computers and Applied Chemistry;2007-02
2 Liu Aihong Yu Xinliang Wang Xueye (College of Chemistry,Xiangtan University,Xiangtan,411105,Hunan,China);Studies on rates of crystal growth for polyethylene by an artificial neural network method[J];Computers and Applied Chemistry;2007-03
3 Xing Bo,Chenzheng(Research Institute of Petroleum Processing,Beijing 100083);Studies on Prediction of Hydrocarbon Series Composition of VGO[J];Qilu Petrochemical Technology;2006-02
4 CHEN Wen yi and LIU Yong min (Fushun Petroleum Institute,Fushun Liaoning 113001);Prediction on the Structural Groups of Coker Gatch[J];PETROCHEMICAL TECHNOLOGY;1999-03
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