Optimal Tunnel Coverage Problem by One New Nature-Inspired Energy Conservation Optimization

This paper mainly provides one new nature inspired Energy Conversation Optimization (ECO) method to search for the optimal sensor position of sensor network in the typical tunnels, fully covering the tunnel and dynamically locating the high-speed train in the tunnel. Firstly, one objective of this s...

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Published inInternational journal of computational intelligence systems Vol. 8; no. 3; pp. 561 - 590
Main Authors Liu, Jun, Shi, Tianyun, Li, Ping, Ren, Xuemei, Ma, Hongbin
Format Journal Article
LanguageEnglish
Published Dordrecht Springer Netherlands 01.06.2015
Springer Nature B.V
Springer
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Online AccessGet full text
ISSN1875-6891
1875-6883
1875-6883
DOI10.1080/18756891.2015.1036223

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Abstract This paper mainly provides one new nature inspired Energy Conversation Optimization (ECO) method to search for the optimal sensor position of sensor network in the typical tunnels, fully covering the tunnel and dynamically locating the high-speed train in the tunnel. Firstly, one objective of this study is to briefly introduce the framework of transmitting the sensor’s data in the railway network, the objectives and the constraints of the optimal coverage problem. Secondly, another objective of this paper is to provide some fundamental assumptions and concepts of ECO algorithm, together with the corresponding convergence analysis and the main steps of ECO algorithm. Additionally, the ECO algorithm is mainly utilized to address the optimal tunnel coverage problem. Numerical results mainly concentrate on the effectiveness of ECO algorithm comparing with the PSO algorithm and deal with four typical optimal coverage problems in the presence of the line tunnel, the indirect line tunnel and the complicated tunnels, etc. Finally, the ECO algorithm can offer the guideline for the smallest number of sensors and the corresponding positions in the given tunnel, fully covering the whole tunnel and providing the location of high-speed trains.
AbstractList This paper mainly provides one new nature inspired Energy Conversation Optimization (ECO) method to search for the optimal sensor position of sensor network in the typical tunnels, fully covering the tunnel and dynamically locating the high-speed train in the tunnel. Firstly, one objective of this study is to briefly introduce the framework of transmitting the sensor's data in the railway network, the objectives and the constraints of the optimal coverage problem. Secondly, another objective of this paper is to provide some fundamental assumptions and concepts of ECO algorithm, together with the corresponding convergence analysis and the main steps of ECO algorithm. Additionally, the ECO algorithm is mainly utilized to address the optimal tunnel coverage problem. Numerical results mainly concentrate on the effectiveness of ECO algorithm comparing with the PSO algorithm and deal with four typical optimal coverage problems in the presence of the line tunnel, the indirect line tunnel and the complicated tunnels, etc. Finally, the ECO algorithm can offer the guideline for the smallest number of sensors and the corresponding positions in the given tunnel, fully covering the whole tunnel and providing the location of high-speed trains.
Author Ren, Xuemei
Ma, Hongbin
Shi, Tianyun
Liu, Jun
Li, Ping
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Snippet This paper mainly provides one new nature inspired Energy Conversation Optimization (ECO) method to search for the optimal sensor position of sensor network in...
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SubjectTerms Algorithms
Energy conversation optimization
High speed rail
IP (Internet Protocol)
optimal tunnel coverage problem
Optimization
Position sensing
railway transportation
Railway tunnels
Research Article
sensor network
Sensors
Tunnels
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Title Optimal Tunnel Coverage Problem by One New Nature-Inspired Energy Conservation Optimization
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