Plug-and-Play Based Optimization Algorithm for New Crime Density Estimation

doi:10.1007/s11390-019-1920-1

CASIA OpenIR > 智能制造技术与系统研究中心 > 多维数据分析（彭思龙）-技术团队

	Plug-and-Play Based Optimization Algorithm for New Crime Density Estimation
	Feng, Xiang-Chu 1; Zhao, Chen-Ping 1,2; Peng, Si-Long3,4 ; Hu, Xi-Yuan3,4,5 ; Ouyang, Zhao-Wei 1
发表期刊	JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY
ISSN	1000-9000
	2019-04-01
卷号	34 期号:2 页码:476-493
通讯作者	Zhao, Chen-Ping(zcp0378@163.com)
摘要	Different from a general density estimation, the crime density estimation usually has one important factor: the geographical constraint. In this paper, a new crime density estimation model is formulated, in which the regions where crime is impossible to happen, such as mountains and lakes, are excluded. To further optimize the estimation method, a learning-based algorithm, named Plug-and-Play, is implanted into the augmented Lagrangian scheme, which involves an off-the-shelf filtering operator. Different selections of the filtering operator make the algorithm correspond to several classical estimation models. Therefore, the proposed Plug-and-Play optimization based estimation algorithm can be regarded as the extended version and general form of several classical methods. In the experiment part, synthetic examples with different invalid regions and samples of various distributions are first tested. Then under complex geographic constraints, we apply the proposed method with a real crime dataset to recover the density estimation. The state-of-the-art results show the feasibility of the proposed model.
关键词	crime density estimation augmented Lagrangian strategy Plug-and-Play filtering operator
DOI	10.1007/s11390-019-1920-1
关键词[WOS]	IMAGE DECOMPOSITION
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61772389] ; National Natural Science Foundation of China[61871260] ; Open Project of National Engineering Laboratory for Forensic Science of China[2017NELKFKT02] ; Key Scientific Research Projects in Henan Colleges and Universities of China[19A110015] ; National Natural Science Foundation of China[61772389] ; National Natural Science Foundation of China[61871260] ; Open Project of National Engineering Laboratory for Forensic Science of China[2017NELKFKT02] ; Key Scientific Research Projects in Henan Colleges and Universities of China[19A110015]
项目资助者	National Natural Science Foundation of China ; Open Project of National Engineering Laboratory for Forensic Science of China ; Key Scientific Research Projects in Henan Colleges and Universities of China
WOS研究方向	Computer Science
WOS类目	Computer Science, Hardware & Architecture ; Computer Science, Software Engineering
WOS记录号	WOS:000462960800014
出版者	SCIENCE PRESS
引用统计	被引频次：1[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/24951
专题	智能制造技术与系统研究中心_多维数据分析（彭思龙）-技术团队
通讯作者	Zhao, Chen-Ping
作者单位	1.Xidian Univ, Sch Math & Stat, Xian 710126, Shaanxi, Peoples R China 2.Henan Inst Sci & Technol, Sch Math Sci, Xinxiang 453003, Peoples R China 3.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 4.Univ Chinese Acad Sci, Sch Comp & Control Engn, Beijing 100190, Peoples R China 5.Beijing Visyst Co Ltd, Res Ctr, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Feng, Xiang-Chu,Zhao, Chen-Ping,Peng, Si-Long,et al. Plug-and-Play Based Optimization Algorithm for New Crime Density Estimation[J]. JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,2019,34(2):476-493.
APA	Feng, Xiang-Chu,Zhao, Chen-Ping,Peng, Si-Long,Hu, Xi-Yuan,&Ouyang, Zhao-Wei.(2019).Plug-and-Play Based Optimization Algorithm for New Crime Density Estimation.JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,34(2),476-493.
MLA	Feng, Xiang-Chu,et al."Plug-and-Play Based Optimization Algorithm for New Crime Density Estimation".JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY 34.2(2019):476-493.