文献类型：期刊文献

中文题名：采用支持向量机实现烯烃裂解料优化选择

英文题名：Using Support Vector Machine to Optimize Selection of Olefin Cracking Feedstock

作者：王清江[1];凌泽济[2];雷向欣[3]

机构：[1]中国石化天津石油化工有限公司,天津300163;[2]中国石化扬子石油化工有限公司研究院,江苏南京210048;[3]华东理工大学信息学院,上海200137

年份：2012

卷号：37

期号：11

起止页码：13

中文期刊名：上海化工

外文期刊名：Shanghai Chemical Industry

语种：中文

中文关键词：乙烯;裂解;支持向量机;计划;优化

外文关键词：Ethylene; Cracking; Support vector machine; Plan; Opimization

摘要：采用支持向量机(SVM)、粒子群搜索最优算法实现烯烃裂解原料结构的优化选择,相比以往原料优选方法,该方法建模与维护便捷、计算精度高,达到根据市场价格变化及时调整生产运行过程中烯烃裂解原料结构的目的,在竞争日益激烈的市场环境下,能提升烯烃裂解生产过程的产出效益。
Support vector machine and particle swarm search optimal algorithm are used to achieve the optimal selection of olefin cracking feedstock. In contrast with the previous methods of optimizing the composition of feedstock, the method presented in this paper provides a easy way for modeling and convenient maintenance with high accuracy, and it could obtains the goal to adjust the composition of feedstock according to market price changes timely during the production process. Accordingly, it also could enhances the output efficiency of the olefin cracking process in the increasingly competitive market environment.