华东理工大学学报（自然科学版）2017，Vol.43Issue(3)：383-388,396,7.DOI:10.14135/j.cnki.1006-3080.2017.03.014
基于偏最小二乘的Kriging代理模型在加氢裂化建模中的应用
Kriging Agent Model Based on Partial Least Squares in the Application of the Hydrocracking Modeling
摘要
Abstract
This paper proposes a modified agent modeling method,Kriging with partial least squares (KPLS).By means of Kriging model,we use the partial least squares method to establish a new Gaussian kernel function.Compared with the traditional Kriging model,the proposed KPLS model can effectively improve the accuracy of the fuel and diesel yield prediction.Besides,the GLAMP (global and local search strategy) search algorithm is used to optimize the KPLS model.The simulation results show that the yield of diesel and fuel is significantly improved.关键词
加氢裂化/Kriging代理模型/偏最小二乘/收率预测/GLAMP优化算法Key words
hydrocracking/Kriging surrogate model/partial least squares/yield prediction/GLAMP optimization algorithm分类
化学化工引用本文复制引用
乔成,钟伟民,范琛..基于偏最小二乘的Kriging代理模型在加氢裂化建模中的应用[J].华东理工大学学报（自然科学版）,2017,43(3):383-388,396,7.基金项目
国家自然科学基金(61422303,21376077) （61422303,21376077）
上海市人才发展资金 （）
中央高校基本业务费专项资金 （）
