文献类型：期刊文献

中文题名：A Knowledge Base System for Operation Optimization: Design and Implementation Practice for the Polyethylene Process

作者：Weimin Zhong[1];Chaoyuan Li[1];Xin Peng[1];Feng Wan[1];Xufeng An[1];Zhou Tian[1]

机构：[1]Key Laboratory of Advanced Control and Optimization for Chemical Processes,Ministry of Education,East China University of Science and Technology,Shanghai 200237,China

年份：2019

卷号：5

期号：6

起止页码：1041

中文期刊名：Engineering

外文期刊名：工程（英文）

收录：CSTPCD;;Scopus;PubMed

语种：英文

中文关键词：Ontology;Operation optimization;Knowledge base system;Polyethylene process

摘要：Setting up a knowledge base is a helpful way to optimize the operation of the polyethylene process by improving the performance and the ef ciency of reuse of information and knowledge two critical ele- ments in polyethylene smart manufacturing. In this paper, we propose an overall structure for a knowl- edge base based on practical customer demand and the mechanism of the polyethylene process. First, an ontology of the polyethylene process constructed using the seven-step method is introduced as a carrier for knowledge representation and sharing. Next, a prediction method is presented for the molecular weight distribution (MWD) based on a back propagation (BP) neural network model, by analyzing the relationships between the operating conditions and the parameters of the MWD. Based on this network, a differential evolution algorithm is introduced to optimize the operating conditions by tuning the MWD. Finally, utilizing a MySQL database and the Java programming language, a knowledge base system for the operation optimization of the polyethylene process based on a browser/server framework is realized.