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Study on Residual Oil HDS Process with Mechanism Model and ANN Model

Study on Residual Oil HDS Process with Mechanism Model and ANN Model
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摘要 Based on the Residual Oil Hydrodesulfurization Treatment Unit (S-RHT), the n-order reaction kinetic model for residual oil HDS reactions and artificial neural network (ANN) model were developed to determine the sulfur content of hydrogenated residual oil. The established ANN model covered 4 input variables, 1 output variable and 1 hidden layer with 15 neurons. The comparison between the results of two models was listed. The results showed that the predicted mean relative errors of the two models with three different sample data were less than 5% and both the two models had good predictive precision and extrapolative feature for the HDS process. The mean relative error of 5 sets of testing data of the ANN model was 1.62%—3.23%, all of which were smaller than that of the common mechanism model (3.47%— 4.13%). It showed that the ANN model was better than the mechanism model both in terms of fitting results and fitting difficulty. The models could be easily applied in practice and could also provide a reference for the further research of residual oil HDS process. Based on the Residual Oil Hydrodesulfurization Treatment Unit (S-RHT), the n-order reaction kinetic model for residual oil HDS reactions and artificial neural network (ANN) model were developed to determine the sulfur content of hydrogenated residual oil. The established ANN model covered 4 input variables, 1 output variable and 1 hidden layer with 15 neurons. The comparison between the results of two models was listed. The results showed that the predicted mean relative errors of the two models with three different sample data were less than 5% and both the two models had good predictive precision and extrapolative feature for the HDS process. The mean relative error of 5 sets of testing data of the ANN model was 1.62%--3.23%, all of which were smaller than that of the common mechanism model (3.47%-- 4.13%). It showed that the ANN model was better than the mechanism model both in terms of fitting results and fitting difficulty. The models could be easily applied in practice and could also provide a reference for the further research of residual oil HDS process.
出处 《China Petroleum Processing & Petrochemical Technology》 SCIE CAS 2009年第1期39-43,共5页 中国炼油与石油化工(英文版)
关键词 residual oil hydrodesulfurization (HDS) mechanism model artificial neural network (ANN) model 人工神经网络模型 加氢脱硫过程 机理模型 加氢处理装置 平均相对误差 反应动力学模型 渣油 预测精度
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