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Conference Paper: Sensor deployment for air pollution monitoring using public transportation system
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TitleSensor deployment for air pollution monitoring using public transportation system
 
AuthorsYu, JJQ1
Li, VOK1
Lam, AYS2
 
KeywordsAir pollution
Public transportation
Evolutionary algorithm
Chemical reaction optimization
Air pollution monitoring
 
Issue Date2012
 
PublisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000284
 
CitationThe 2012 IEEE Congress on Evolutionary Computation (CEC 2012), Brisbane, Australia, 10-15 June 2012. In IEEE CEC Proceedings, 2012, p. 1-7 [How to Cite?]
 
AbstractAir pollution monitoring is a very popular research topic and many monitoring systems have been developed. In this paper, we formulate the Bus Sensor Deployment Problem (BSDP) to select the bus routes on which sensors are deployed, and we use Chemical Reaction Optimization (CRO) to solve BSDP. CRO is a recently proposed metaheuristic designed to solve a wide range of optimization problems. Using the real world data, namely Hong Kong Island bus route data, we perform a series of simulations and the results show that CRO is capable of solving this optimization problem efficiently. © 2012 IEEE.
 
DescriptionIEEE World Congress on Computational Intelligence (WCCI 2012), Brisbane, Australia, 10-15 June 2012 hosted three conferences: the 2012 International Joint Conference on Neural Networks (IJCNN 2012), the 2012 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2012), and the 2012 IEEE Congress on Evolutionary Computation (IEEE CEC 2012)
 
ISBN978-1-4673-1509-8
 
DC FieldValue
dc.contributor.authorYu, JJQ
 
dc.contributor.authorLi, VOK
 
dc.contributor.authorLam, AYS
 
dc.date.accessioned2012-09-20T08:16:52Z
 
dc.date.available2012-09-20T08:16:52Z
 
dc.date.issued2012
 
dc.description.abstractAir pollution monitoring is a very popular research topic and many monitoring systems have been developed. In this paper, we formulate the Bus Sensor Deployment Problem (BSDP) to select the bus routes on which sensors are deployed, and we use Chemical Reaction Optimization (CRO) to solve BSDP. CRO is a recently proposed metaheuristic designed to solve a wide range of optimization problems. Using the real world data, namely Hong Kong Island bus route data, we perform a series of simulations and the results show that CRO is capable of solving this optimization problem efficiently. © 2012 IEEE.
 
dc.description.naturepublished_or_final_version
 
dc.descriptionIEEE World Congress on Computational Intelligence (WCCI 2012), Brisbane, Australia, 10-15 June 2012 hosted three conferences: the 2012 International Joint Conference on Neural Networks (IJCNN 2012), the 2012 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2012), and the 2012 IEEE Congress on Evolutionary Computation (IEEE CEC 2012)
 
dc.identifier.citationThe 2012 IEEE Congress on Evolutionary Computation (CEC 2012), Brisbane, Australia, 10-15 June 2012. In IEEE CEC Proceedings, 2012, p. 1-7 [How to Cite?]
 
dc.identifier.epage7
 
dc.identifier.hkuros210467
 
dc.identifier.isbn978-1-4673-1509-8
 
dc.identifier.scopuseid_2-s2.0-84866839774
 
dc.identifier.spage1
 
dc.identifier.urihttp://hdl.handle.net/10722/165306
 
dc.languageeng
 
dc.publisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000284
 
dc.publisher.placeUnited States
 
dc.relation.ispartofCongress on Evolutionary Computation Proceedings
 
dc.rightsCongress on Evolutionary Computation Proceedings. Copyright © IEEE.
 
dc.rights©2012 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
 
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License
 
dc.subjectAir pollution
 
dc.subjectPublic transportation
 
dc.subjectEvolutionary algorithm
 
dc.subjectChemical reaction optimization
 
dc.subjectAir pollution monitoring
 
dc.titleSensor deployment for air pollution monitoring using public transportation system
 
dc.typeConference_Paper
 
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<item><contributor.author>Yu, JJQ</contributor.author>
<contributor.author>Li, VOK</contributor.author>
<contributor.author>Lam, AYS</contributor.author>
<date.accessioned>2012-09-20T08:16:52Z</date.accessioned>
<date.available>2012-09-20T08:16:52Z</date.available>
<date.issued>2012</date.issued>
<identifier.citation>The 2012 IEEE Congress on Evolutionary Computation (CEC 2012), Brisbane, Australia, 10-15 June 2012. In IEEE CEC Proceedings, 2012, p. 1-7</identifier.citation>
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<description>IEEE World Congress on Computational Intelligence (WCCI 2012), Brisbane, Australia, 10-15 June 2012  hosted three conferences: the 2012 International Joint Conference on Neural Networks (IJCNN 2012), the 2012 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2012), and the 2012 IEEE Congress on Evolutionary Computation (IEEE CEC 2012)</description>
<description.abstract>Air pollution monitoring is a very popular research topic and many monitoring systems have been developed. In this paper, we formulate the Bus Sensor Deployment Problem (BSDP) to select the bus routes on which sensors are deployed, and we use Chemical Reaction Optimization (CRO) to solve BSDP. CRO is a recently proposed metaheuristic designed to solve a wide range of optimization problems. Using the real world data, namely Hong Kong Island bus route data, we perform a series of simulations and the results show that CRO is capable of solving this optimization problem efficiently. &#169; 2012 IEEE.</description.abstract>
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<rights>Creative Commons: Attribution 3.0 Hong Kong License</rights>
<subject>Air pollution</subject>
<subject>Public transportation</subject>
<subject>Evolutionary algorithm</subject>
<subject>Chemical reaction optimization</subject>
<subject>Air pollution monitoring</subject>
<title>Sensor deployment for air pollution monitoring using public transportation system</title>
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Author Affiliations
  1. The University of Hong Kong
  2. UC Berkeley