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

文献类型：期刊论文

作者Shi, Guang1; Zhao, Bo2; Li, Chao1; Wei, Qinglai2; Liu, Derong3
刊名NEUROCOMPUTING
出版日期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
DOI10.1016/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.
WOS关键词PARTICLE SWARM OPTIMIZATION ; ENERGY-CONSUMPTION ; NEURAL-NETWORKS ; PREDICTION ; ALGORITHMS ; MODEL
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研究方向Computer Science
语种英语
WOS记录号WOS:000456834100029
出版者ELSEVIER SCIENCE BV
资助机构National Natural Science Foundation of China ; National Key Research and Development Program of China
源URL[http://ir.ia.ac.cn/handle/173211/25347]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_智能化团队
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.

入库方式： OAI收割

来源：自动化研究所

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