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 in | International journal of computational intelligence systems Vol. 8; no. 3; pp. 561 - 590 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Dordrecht
Springer Netherlands
01.06.2015
Springer Nature B.V Springer |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1875-6891 1875-6883 1875-6883 |
| DOI | 10.1080/18756891.2015.1036223 |
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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. |
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| 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 |
| Author_xml | – sequence: 1 givenname: Jun surname: Liu fullname: Liu, Jun email: DrJLBit@163.com, mathmhb@bit.edu.cn organization: Institute of Computing Technologies, China Academy of Railway Sciences, School of Automation, Beijing Institute of Technology – sequence: 2 givenname: Tianyun surname: Shi fullname: Shi, Tianyun organization: Institute of Computing Technologies, China Academy of Railway Sciences – sequence: 3 givenname: Ping surname: Li fullname: Li, Ping organization: Institute of Computing Technologies, China Academy of Railway Sciences – sequence: 4 givenname: Xuemei surname: Ren fullname: Ren, Xuemei organization: School of Automation, Beijing Institute of Technology – sequence: 5 givenname: Hongbin surname: Ma fullname: Ma, Hongbin organization: School of Automation, Beijing Institute of Technology |
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| Cites_doi | 10.1016/S0020-0190(02)00447-7 10.1038/scientificamerican0682-114 10.1109/ICNN.1995.488968 10.1109/25.832978 10.1126/science.220.4598.671 10.1109/4235.985692 10.1504/IJBIC.2009.022775 10.1016/j.cnsns.2012.05.010 10.1007/s00707-009-0270-4 10.1109/TEVC.2009.2011992 10.1023/A:1008202821328 10.1109/25.832979 10.1109/TEVC.2010.2053935 10.1109/NABIC.2009.5393690 10.1007/s10898-007-9149-x |
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| Copyright | the authors 2017 2015. This work is licensed under https://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
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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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