文献类型：期刊文献

英文题名：Designing neurofuzzy system based on ICART algorithm and its application for modeling jet fuel endpoint of hydrocracking process

作者：Jia, Li[1]; Li, Erguo[1]; Yu, Jinshou[1]

机构：[1]E China Univ Sci & Technol, Res Inst Automat, Shanghai 200237, Peoples R China

年份：2003

卷号：16

期号：1

起止页码：11

外文期刊名：ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

收录：;EI(收录号：2003227490039);WOS:【SCI-EXPANDED(收录号:WOS:000183166100002)】；

语种：英文

外文关键词：decision trees; CART algorithm; ICART algorithm; neurofuzzy system; hydrocracking processing

摘要：In this paper, a neuro-fuzzy system based on improved CART algorithm (ICART) is presented, in which the ICART algorithm is used to design neuro-fuzzy system. It is worth noting that ICART algorithm partitions the input space into tree structure adaptively, which avoids the curse of dimensionality (number of rules goes up exponentially with number of input variables). Moreover, it adopts density function to construct the local model for every node in order to overcome the discontinuous boundaries existed in CART algorithm. In addition, a supervised scheme is used to adjust parameters to minimize the network output error and construct more accurate fuzzy model on the basis of the ICART algorithm. Finally, to illustrate the validity of the proposed method, a simulation research and a practical application are done. The results show that the proposed method can provide optimal model structure and parameters for fuzzy modeling, possesses high learning efficiency, and is smoother than CART algorithm. It call be successfully applied to modeling jet fuel endpoint of hydrocracking processing. (C) 2003 Elsevier Science Ltd. All rights reserved.