An Automatically Learning and Discovering Human Fishing Behaviors Scheme for CPSCN

doi:10.1109/ACCESS.2018.2817486

	An Automatically Learning and Discovering Human Fishing Behaviors Scheme for CPSCN
	Zhang, Jilin 1,2,3; Geng, Jiali 1,2; Wan, Jian 1,2; Zhang, Yifan 1,2; Li, Mingwei 1,2; Wang, Jue 4; Xiong, Neal N.5
	2018
发表期刊	IEEE ACCESS
ISSN	2169-3536
卷号	6 页码:19844-19858
摘要	The cyber-physical-social (CPS) computing and networking is a human centric and holistic computing framework which needs to convert the low-level data of physical, cyber, and social worlds into higher level information which can provide insights and help humans make complex decisions. Here, we focus on human fishing behavior recognition for vessel monitoring systems (VMS), an application of CPS. And the recognition of fishing behavior is the key task for studying human fishing activities, monitoring illegal fishing, and protecting fishery resources. However, VMS data basically consist of sequentially recorded position information and do not directly indicate whether a fisherman is fishing or not; thus, converting these low-level CPS data into intuitive information to humans is the primary task. In this paper, an identification model based on multi-step clustering algorithm (MSC-FBI) is proposed to automatically learn and discover fishingbehaviors at sea. First, a temporal-spatial distance model is established; then, an improved multi -step clustering algorithm is used to identify human fishing behaviors, and finally, the patterns of different behaviors are extracted from the trajectory, and the unsupervised behavior learning model is established. Using this method, many experiments on different fishing trajectory data were implemented and compared with a traditional identification method based on the Gaussian mixture model (GMM-FBI). The experimental results illustrate the proposed model's superior performance.
关键词	Human fishing behavior multi-step clustering algorithm CPSCN trajectory vessel monitoring systems
DOI	10.1109/ACCESS.2018.2817486
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61672200] ; National Natural Science Foundation of China[61572163] ; National Natural Science Foundation of China[61472109] ; National Key Technology Research and Development Program[2015BAH17F02] ; Zhejiang Natural Science Funds[LY16F020018] ; Zhejiang Natural Science Funds[LY17F020029] ; National High Technology Research and Development Program of China[2015AA01A303] ; Zhejiang Key Research and Development Program[2017C03024] ; Opening Foundation of Institute of Computing Technology, Chinese Academy of Sciences[CARCH201712] ; Postgraduate Cultivation Project[hxkc2016004]
WOS研究方向	Computer Science ; Engineering ; Telecommunications
WOS类目	Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS记录号	WOS:000430793300007
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：12[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/5347
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Wan, Jian; Xiong, Neal N.
作者单位	1.Hangzhou Dianzi Univ, Sch Comp Sci & Technol, Hangzhou 310018, Zhejiang, Peoples R China 2.Minist Educ, Key Lab Complex Syst Modeling & Simulat, Hangzhou 310018, Zhejiang, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, State Key Lab Comp Architecture, Beijing 100190, Peoples R China 4.Chinese Acad Sci, Comp Network Informat Ctr, Supercomp Ctr, Beijing 100190, Peoples R China 5.Northeastern State Univ, Dept Math & Comp Sci, Tahlequah, OK 74464 USA
推荐引用方式 GB/T 7714	Zhang, Jilin,Geng, Jiali,Wan, Jian,et al. An Automatically Learning and Discovering Human Fishing Behaviors Scheme for CPSCN[J]. IEEE ACCESS,2018,6:19844-19858.
APA	Zhang, Jilin.,Geng, Jiali.,Wan, Jian.,Zhang, Yifan.,Li, Mingwei.,...&Xiong, Neal N..(2018).An Automatically Learning and Discovering Human Fishing Behaviors Scheme for CPSCN.IEEE ACCESS,6,19844-19858.
MLA	Zhang, Jilin,et al."An Automatically Learning and Discovering Human Fishing Behaviors Scheme for CPSCN".IEEE ACCESS 6(2018):19844-19858.