An echo state network based approach to room classification of office buildings

doi:10.1016/j.neucom.2018.12.033

	An echo state network based approach to room classification of office buildings
	Shi, Guang 1; Zhao, Bo2 ; Li, Chao 1; Wei, Qinglai2 ; Liu, Derong 3
刊名	NEUROCOMPUTING
	2019-03-14
卷号	333 页码:319-328
关键词	Power consumption Room classification Echo state networks Neural networks
ISSN号	0925-2312
DOI	10.1016/j.neucom.2018.12.033
通讯作者	Wei, Qinglai(qinglai.wei@ia.ac.cn)
英文摘要	Office buildings commonly contain such room types as office rooms, server rooms, storage rooms, meeting rooms, etc., while the power consumption inside the rooms generally comes from appliances, lights and air-conditioners. Based on the features of power consumption in different rooms, the aim of this study is to classify the rooms into different types by proposing an echo state network (ESN) based approach. Given the data on power consumption, the proposed approach is divided into two steps, where the first step is to establish three ESNs to model the three categories of power consumption, and the second step is to establish a fourth ESN to determine the type of a room by using the outputs of the first three ESNs. The practical performance of the proposed approach is displayed by a detailed experimental study, where the proposed approach achieves high classification accuracies and shows great superiority to several classical algorithms. (C) 2019 Elsevier B.V. All rights reserved.
资助项目	National Natural Science Foundation of China[61533017] ; National Natural Science Foundation of China[61603387] ; National Natural Science Foundation of China[61722312] ; National Natural Science Foundation of China[61773075] ; National Natural Science Foundation of China[61601458] ; National Key Research and Development Program of China[2016QY01W0103]
WOS关键词	PARTICLE SWARM OPTIMIZATION ; ENERGY-CONSUMPTION ; NEURAL-NETWORKS ; PREDICTION ; ALGORITHMS ; MODEL
WOS研究方向	Computer Science
语种	英语
出版者	ELSEVIER SCIENCE BV
WOS记录号	WOS:000456834100029
资助机构	National Natural Science Foundation of China ; National Key Research and Development Program of China
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/25347]
专题	中国科学院自动化研究所
通讯作者	Wei, Qinglai
作者单位	1.Coordinat Ctr China, Natl Comp Network Emergency Response Tech Team, Beijing 100029, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 3.Guangdong Univ Technol, Sch Automat, Guangzhou 510006, Guangdong, Peoples R China
推荐引用方式 GB/T 7714	Shi, Guang,Zhao, Bo,Li, Chao,et al. An echo state network based approach to room classification of office buildings[J]. NEUROCOMPUTING,2019,333:319-328.
APA	Shi, Guang,Zhao, Bo,Li, Chao,Wei, Qinglai,&Liu, Derong.(2019).An echo state network based approach to room classification of office buildings.NEUROCOMPUTING,333,319-328.
MLA	Shi, Guang,et al."An echo state network based approach to room classification of office buildings".NEUROCOMPUTING 333(2019):319-328.