Discovering multi‐dimensional motifs from multi‐dimensional time series for air pollution control-Reference-Cited by-同舟云学术

Discovering multi‐dimensional motifs from multi‐dimensional time series for air pollution control

Published:2019-12-14 Issue:11 Volume:32 Page:
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency Computat Pract Exper

Author:

Liu Bo¹,Zhao Huaipu¹^ORCID,Liu Yinxing¹^ORCID,Wang Suyu¹,Li Jianqiang¹,Li Yong¹,Lang Jianlei²,Gu Rentao³

Affiliation:

1. School of Software Engineering, Faculty of Information TechnologyBeijing University of Technology Beijing China

2. Key Laboratory of Beijing on Regional Air Pollution Control, College of Environmental and Energy EngineeringBeijing University of Technology Beijing China

3. Beijing Laboratory of Advanced Information Networks, School of Information and Communication EngineeringBeijing University of Posts and Telecommunications Beijing China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Beijing Municipality

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.5645

Reference38 articles.

1. PM10 and PM2.5 source apportionment in the Barcelona Metropolitan area, Catalonia, Spain

2. The water-soluble ionic composition of PM2.5 in Shanghai and Beijing, China

3. Internet of Things (IoT): A vision, architectural elements, and future directions

4. A Gaussian error correction multi‐objective positioning model with NSGA‐II;Wang P;Concurrency Computat Pract Exper,2019

5. A Multi-Objective DV-Hop Localization Algorithm Based on NSGA-II in Internet of Things

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