化工学报2017，Vol.68Issue(2)：739-745,7.DOI:10.11949/j.issn.0438-1157.20161069
直觉模糊多核聚类算法及其在乙烯原料属性聚类中的应用
Intuitionistic set theory based multiple kernel fuzzy clustering and its application of ethylene raw material properties
摘要
Abstract
Along with the increasing types of ethylene cracking materials and expensive feed analyzer, clustering of ethylene cracking materials which is to improve ethylene yield modeling, ethylene yield and energy consumption has very important practical significance. In order to improve the accuracy of online identification of raw materials, an intuitionistic fuzzy kernel clustering algorithm based on the theory of intuitionistic fuzzy sets is presented. In the definition of membership, membership considers uncertain information which is the hesitation degree. At the same time, intuitionistic fuzzy entropy is incorporated in the loss function of multiple kernel clustering algorithm. That is to optimize the data points in the class. Further, the cracking material attribute feature selection using random forest, based on the main attributes of contribution of ethylene yield. Finally, the actual ethylene cracking naphtha data of industry is used to verify the effectiveness and superiority of the algorithm.关键词
算法/熵/优化/直觉模糊/乙烯裂解Key words
algorithm/entropy/optimization/intuitionistic fuzzy/ethylene cracking分类
信息技术与安全科学引用本文复制引用
崔兴华,杜文莉,赵亮,李江利,池亮..直觉模糊多核聚类算法及其在乙烯原料属性聚类中的应用[J].化工学报,2017,68(2):739-745,7.基金项目
国家自然科学基金重点项目（61590923）；国家自然科学基金优秀青年基金项目；国家自然科学基金青年科学基金项目（61422303，61403141）；上海市教育委员会和上海市教育发展基金会“曙光计划”资助项目。 （）
