IFCEM based recognition method for target with interval-overlapped hybrid attributes

作     者：GUAN Xin LI Shuangming SUN Guidong WANG Haibin GUAN Xin;LI Shuangming;SUN Guidong;WANG Haibin

作者机构：Naval Aviation UniversityYantai 264001China Unit 92941 of PLAHuludao 125001China Unit 32801 of PLABeijing 100082China 

出 版 物：《Journal of Systems Engineering and Electronics》 (系统工程与电子技术（英文版）)

年 卷 期：2023年第34卷第2期

页      面：408-421页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the Youth Foundation of the National Science Foundation of China(62001503) the Excellent Youth Scholar of the National Defense Science and Technology Foundation of China(2017-JCJQ-ZQ-003) the Special Fund for Taishan Scholar Project(ts201712072). 

主　　题：intuitionistic fuzzy comprehensive evaluation model(IFCEM) interval overlapping cloud model area-based method inverse weighted kernel fuzzy c-means(IWK-FCM) 

摘      要：When the attributes of unknown targets are not just numerical attributes,but hybrid attributes containing linguistic attributes,the existing recognition methods are not effective.In addition,it is more difficult to identify the unknown targets densely distributed in the feature space,especially when there is interval overlap between attribute measurements of different target classes.To address these problems,a novel method based on intuitionistic fuzzy comprehensive evaluation model(IFCEM)is proposed.For numerical attributes,targets in the database are divided into individual classes and overlapping classes,and for linguistic attributes,continuous interval-valued linguistic term set(CIVLTS)is used to describe target characteristic.A cloud modelbased method and an area-based method are proposed to obtain intuitionistic fuzzy decision information of query target on numerical attributes and linguistic attributes respectively.An improved inverse weighted kernel fuzzy c-means(IWK-FCM)algorithm is proposed for solution of attribute weight vector.The possibility matrix is applied to determine the identity and category of query target.Finally,a case study composed of parameter sensitivity analysis,recognition accuracy analysis.and comparison with other methods,is taken to verify the superiority of the proposed method.