Review of Clustering Technology and Its Application in Coordinating Vehicle Subsystems

作     者：Caizhi Zhang Weifeng Huang Tong Niu Zhitao Liu Guofa Li Dongpu Cao 

作者机构：Chongqing Automotive Collaborative Innovation CentreThe State Key Laboratory of Mechanical TransmissionsChongqing UniversityChongqing 400044China State Key Laboratory of Industrial Control TechnologyInstitute of Cyber‑Systems and ControlZhejiang UniversityHangzhou 310027China School of Vehicle and MobilityTsinghua UniversityBeijingChina 

出 版 物：《Automotive Innovation》 (汽车创新工程（英文）)

年 卷 期：2023年第6卷第1期

页      面：89-115页

核心收录：

学科分类：08[工学] 080204[工学-车辆工程] 0802[工学-机械工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported in part by the founding of the State Key Laboratory of Industrial Control Technology,Zhejiang University(ICT2021B19) the Technological Innovation and Application Demonstration in Chongqing(Major Themes of Industry:cstc2019jscx-zdztzxX0033,cstc2019jscx-fxyd0158). 

主　　题：Unsupervised learning Clustering Similarity measures Vehicle 

摘      要：Clustering is an unsupervised learning technology,and it groups information(observations or datasets)according to similarity measures.Developing clustering algorithms is a hot topic in recent years,and this area develops rapidly with the increasing complexity of data and the volume of datasets.In this paper,the concept of clustering is introduced,and the clustering technologies are analyzed from traditional and modern perspectives.First,this paper summarizes the principles,advantages,and disadvantages of 20 traditional clustering algorithms and 4 modern algorithms.Then,the core elements of clustering are presented,such as similarity measures and evaluation index.Considering that data processing is often applied in vehicle engineering,finally,some specific applications of clustering algorithms in vehicles are listed and the future development of clustering in the era of big data is highlighted.The purpose of this review is to make a comprehensive survey that helps readers learn various clustering algorithms and choose the appropriate methods to use,especially in vehicles.