Optimal Search and Rescue Model: Updating Probability Density Map of Debris Location by Bayesian Method

Lu Yadong; Zhou Ya

doi:doi:10.11648/j.ijsd.20150101.13

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Optimal Search and Rescue Model: Updating Probability Density Map of Debris Location by Bayesian Method

Lu Yadong, Zhou Ya

Received: 5 September 2015 Accepted: 16 September 2015 Published: 16 September 2015

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Abstract

Optimizing search and rescue plan for the distressed planes calls for analysis of the debris location as well as a systematic way of searching. The searching plan consists of three main parts: simulating possible trajectory, produce a probability density map of the debris' location and generating an optimal searching plan using Dinkelbach's algorithm. Besides, the Bayesian inference is discussed to update the probability density map of the objects' location.

DOI	10.11648/j.ijsd.20150101.13
Published in	International Journal of Statistical Distributions and Applications (Volume 1, Issue 1, September 2015)
Page(s)	12-18
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Optimal Search and Rescue Plan, Dinkelbach's Algorithm, Bayesian Inference, Probability Density Map

References

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[2]	Russell A, Quigley J, van der Meer R. (Apr. 2006). Modeling the reliability of search and rescue operations within the UK through Bayesian belief networks. Proceedings of the First International Conference on Availability, Reliability and Security, 810-816.
[3]	Weiguang Zhang, Jianchu Kang, Hesong Li. (2007). A global optimization algorithms based on cloud model. Journal of Beijing University of Aeronautics and Astronautics, 33(4), 486-490.
[4]	Hannah Bast, Susan Hert. (2000). The Area Partitioning Problem. Proceedings of 12th Canadian Conference on Computational Geometry, 163-172.
[5]	Susan Hert, Brad Richards. (2002). Multiple-Robot Motion Planning Parallel Processing and Geometry. Lecture Notes in Computer Science, Volume 2238, 195-215.
[6]	David Adjiashvili, David Peleg. (2008). Equal-Area Locus-Based Convex Polygon Decomposition. Lecture Notes in Computer Science, Volume 5058, Structural Information and Communication Complexity, 141-155.
[7]	J Mark Keil, Tzvetalin S Vassilev. (2006). Algorithms for optimal area triangulations of a convex polygon. Computational Geometry: Theory and Applications, 35(3):173-187.
[8]	Hert Susan, Lumelsky Valdimir. (1998). Polygon Area Decomposition for Multi-robot Workspace Division. International Journal of Computational Geometry and Applications (S0218-1959), 8(4):437-466.
[9]	Lawrence D. Stone and Thomas M. Kratzke, Metron Inc, John R. Frost. (2011). Search Modeling and Optimization in USCG’s Search and Rescue Optimal Planning System (SAROPS). U.S. Coast Guard, France.
[10]	Oyvind Breivik, Arthur A. Allen.(2008). An Operational Search and Rescue Model for the Norwegian Sea and the North Sea. J Marine Syst, 69(1-2), 99-113.

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APA Style

Lu Yadong, Zhou Ya. (2015). Optimal Search and Rescue Model: Updating Probability Density Map of Debris Location by Bayesian Method. International Journal of Statistical Distributions and Applications, 1(1), 12-18. https://doi.org/10.11648/j.ijsd.20150101.13

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ACS Style

Lu Yadong; Zhou Ya. Optimal Search and Rescue Model: Updating Probability Density Map of Debris Location by Bayesian Method. Int. J. Stat. Distrib. Appl. 2015, 1(1), 12-18. doi: 10.11648/j.ijsd.20150101.13

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AMA Style

Lu Yadong, Zhou Ya. Optimal Search and Rescue Model: Updating Probability Density Map of Debris Location by Bayesian Method. Int J Stat Distrib Appl. 2015;1(1):12-18. doi: 10.11648/j.ijsd.20150101.13

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@article{10.11648/j.ijsd.20150101.13,
  author = {Lu Yadong and Zhou Ya},
  title = {Optimal Search and Rescue Model: Updating Probability Density Map of Debris Location by Bayesian Method},
  journal = {International Journal of Statistical Distributions and Applications},
  volume = {1},
  number = {1},
  pages = {12-18},
  doi = {10.11648/j.ijsd.20150101.13},
  url = {https://doi.org/10.11648/j.ijsd.20150101.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijsd.20150101.13},
  abstract = {Optimizing search and rescue plan for the distressed planes calls for analysis of the debris location as well as a systematic way of searching. The searching plan consists of three main parts: simulating possible trajectory, produce a probability density map of the debris' location and generating an optimal searching plan using Dinkelbach's algorithm. Besides, the Bayesian inference is discussed to update the probability density map of the objects' location.},
 year = {2015}
}

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TY  - JOUR
T1  - Optimal Search and Rescue Model: Updating Probability Density Map of Debris Location by Bayesian Method
AU  - Lu Yadong
AU  - Zhou Ya
Y1  - 2015/09/16
PY  - 2015
N1  - https://doi.org/10.11648/j.ijsd.20150101.13
DO  - 10.11648/j.ijsd.20150101.13
T2  - International Journal of Statistical Distributions and Applications
JF  - International Journal of Statistical Distributions and Applications
JO  - International Journal of Statistical Distributions and Applications
SP  - 12
EP  - 18
PB  - Science Publishing Group
SN  - 2472-3509
UR  - https://doi.org/10.11648/j.ijsd.20150101.13
AB  - Optimizing search and rescue plan for the distressed planes calls for analysis of the debris location as well as a systematic way of searching. The searching plan consists of three main parts: simulating possible trajectory, produce a probability density map of the debris' location and generating an optimal searching plan using Dinkelbach's algorithm. Besides, the Bayesian inference is discussed to update the probability density map of the objects' location.
VL  - 1
IS  - 1
ER  -

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Author Information

Lu Yadong

Department of Mathematics, Sichuan University, Chengdu, China
Zhou Ya

Department of Mathematics, Sichuan University, Chengdu, China

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APA Style

Lu Yadong, Zhou Ya. (2015). Optimal Search and Rescue Model: Updating Probability Density Map of Debris Location by Bayesian Method. International Journal of Statistical Distributions and Applications, 1(1), 12-18. https://doi.org/10.11648/j.ijsd.20150101.13

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ACS Style

Lu Yadong; Zhou Ya. Optimal Search and Rescue Model: Updating Probability Density Map of Debris Location by Bayesian Method. Int. J. Stat. Distrib. Appl. 2015, 1(1), 12-18. doi: 10.11648/j.ijsd.20150101.13

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AMA Style

Lu Yadong, Zhou Ya. Optimal Search and Rescue Model: Updating Probability Density Map of Debris Location by Bayesian Method. Int J Stat Distrib Appl. 2015;1(1):12-18. doi: 10.11648/j.ijsd.20150101.13

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@article{10.11648/j.ijsd.20150101.13,
  author = {Lu Yadong and Zhou Ya},
  title = {Optimal Search and Rescue Model: Updating Probability Density Map of Debris Location by Bayesian Method},
  journal = {International Journal of Statistical Distributions and Applications},
  volume = {1},
  number = {1},
  pages = {12-18},
  doi = {10.11648/j.ijsd.20150101.13},
  url = {https://doi.org/10.11648/j.ijsd.20150101.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijsd.20150101.13},
  abstract = {Optimizing search and rescue plan for the distressed planes calls for analysis of the debris location as well as a systematic way of searching. The searching plan consists of three main parts: simulating possible trajectory, produce a probability density map of the debris' location and generating an optimal searching plan using Dinkelbach's algorithm. Besides, the Bayesian inference is discussed to update the probability density map of the objects' location.},
 year = {2015}
}

Copy | Download

TY  - JOUR
T1  - Optimal Search and Rescue Model: Updating Probability Density Map of Debris Location by Bayesian Method
AU  - Lu Yadong
AU  - Zhou Ya
Y1  - 2015/09/16
PY  - 2015
N1  - https://doi.org/10.11648/j.ijsd.20150101.13
DO  - 10.11648/j.ijsd.20150101.13
T2  - International Journal of Statistical Distributions and Applications
JF  - International Journal of Statistical Distributions and Applications
JO  - International Journal of Statistical Distributions and Applications
SP  - 12
EP  - 18
PB  - Science Publishing Group
SN  - 2472-3509
UR  - https://doi.org/10.11648/j.ijsd.20150101.13
AB  - Optimizing search and rescue plan for the distressed planes calls for analysis of the debris location as well as a systematic way of searching. The searching plan consists of three main parts: simulating possible trajectory, produce a probability density map of the debris' location and generating an optimal searching plan using Dinkelbach's algorithm. Besides, the Bayesian inference is discussed to update the probability density map of the objects' location.
VL  - 1
IS  - 1
ER  -

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