The Optimization Model of Searching the Wreckage

DOI

10.2991/amsm-16.2016.24How to use a DOI?

Keywords

the particle network mode; Monte Carlo simulation method; Bayesian theory; probability distribution

Abstract

In order to search the wreckage, this paper establish the particle network model, in terms of Monte Carlo simulation method and the Bayesian theory. Based on analytic inverse extrapolation, we use Monte Carlo simulation method to simulate thousands of particles and the distribution of the aircraft crash position. According to the relationship between the successful search probability, the depth of seabed, and the size of crashed plane, the model is developed. We get the successful search probability in each grid. Based on Bayesian theory and above probability distribution, we renew the probability distribution in each grid, if no wreckage is found after the search is completed. To ensure the largest success probability for each search, we find the wreckage in the least time. In this paper, we set several positions of the wreckage. In this method to search 16 times, we minimize the total search area.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xinglong Ren
AU  - Hong Fang
PY  - 2016/05
DA  - 2016/05
TI  - The Optimization Model of Searching the Wreckage
BT  - Proceedings of the 2016 International Conference on Applied Mathematics, Simulation and Modelling
PB  - Atlantis Press
SP  - 102
EP  - 105
SN  - 2352-538X
UR  - https://doi.org/10.2991/amsm-16.2016.24
DO  - 10.2991/amsm-16.2016.24
ID  - Ren2016/05
ER  -