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【国际讲堂】外教主讲的研究生全英文课程“飞机电系统故障预测与健康管理”开课通知
2018-04-27 14:11   审核人:   (点击: )

日本NEC中央研究院Jianquan Liu研究员,应航空学院邀请来我校从事教学和科研工作,计划于近期讲授“飞机电系统故障预测与健康管理”全英文课程,欢迎广大研究生和高年级本科生选修(旁听)学习。

人:航空学院 张超 老师

联系方式:88492344 caec_zc@nwpu.edu.cn

课程名称:Prognosis and Health Management of Aircraft Electronics System飞机电系统故障预测与健康管理

时间地点:见附件

课程介绍:

预测与健康管理(简称PHM)是近年来国内外电子系统领域重点发展的先进技术。本课程将主要讲授研究生全英文课程《飞行器电系统故障预测与健康管理》中的智能无监督学习算法(重点侧重于聚类方法)及其在PHM中的应用。具体包括:(1)聚类及基本原理;(2)K均值聚类及其扩展;(3)层次聚类算法;(4)DBSCAN聚类算法;(5)基于模型的聚类算法;(6)基于聚类的数据处理方法;(7)基于聚类的智能PHM应用。

Prognosis and Health Management (PHM) has been widely used in complex electronics system. And clustering involves a set of techniques and methods to extract novel knowledge from large databases in the way of unsupervised learning. This is a course that consists of special lectures on clustering techniques and the application in PHM. The course deals with the fundamentals of clustering, by focusing on the most important algorithms, such as K-Means and DBSCAN. Moreover, the course introduces the recent trends of clustering processing on massive datasets and PHM. Topics addressed include: (1) Introduction to clustering and basic concepts; (2) Partition-based clustering algorithms (K-Means and its variants); (3) Hierarchical clustering algorithms (e.g., CURE); (4) Density-based clustering algorithms (e.g., DBSCAN); (5) Grid-based and model-based clustering algorithms (e.g., CLIQUE, EM); (6) Cluster validity and clustering massive datasets; (7) Intelligent prognosis based on clustering.

外教简介:

Dr. Jianquan Liu received the B.E. degree from Shantou University, China, M.E. and Ph.D. degrees from the University of Tsukuba, Japan, in 2005, 2009, and 2012, respectively. He was a Development Engineer in Tencent Inc. from 2005 to 2006, and was a visiting research assistant at the Chinese University of Hong Kong from September to December in 2010. He is currently a researcher and an assistant manager at the Central Research Laboratories of NEC Corporation, working on the topics of large-scale data processing and cloud computing. He is also an adjunct assistant professor at Graduate School of Science and Engineering, Hosei University, teaching courses related to data mining and database. His research interests include high-dimensional similarity search, social network analysis, web data mining and information retrieval, cloud storage and computing, multimedia databases, artificial intelligent and fault-tolerance computing. Currently, he is serving as the Technical Program Co-chair of IEEE 2nd International Conference on Multimedia Big Data (BigMM 2016), the Workshop Co-chair of IEEE 10th International Conference on Semantic Computing (ICSC 2016). He is a member of ACM and the Database Society of Japan (DBSJ).

 

研究生院 航空学院

2018427

 

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