Performance Evaluation of Naval Minesweeping and Estimation of the Number of Remaining Mines based on Bayesian Estimation Theory

DOI

10.2991/icmse-15.2015.82How to use a DOI?

Keywords

Bayesian estimation mine sweeping probability remaining mine.

Abstract

It is very difficult to get exact accurate estimated value When the Markov process theory is used to calculate the number of remaining mines, because the prior knowledge has not been fully utilized. For solving the above problems, this paper establishes posterior distribution model of Estimation of the number of remaining mines, based on Bayesian estimation theory. Then several typical distributions are discussed, such as the binomial distribution, Poisson distribution, negative binomial distribution and uniform distribution, and the mean and variance of the number of remaining mines are given. Finally the simulation calculation is carried out for the given minefield prior data, the results show that the model accuracy is related to mine number, mine sweeping probability and other factors.

Copyright

© 2015, 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  - Xinqin Chen
AU  - Huidong Lu
AU  - Longteng Li
AU  - Chang Shu
AU  - Xuanmin Li
AU  - Chengwen Zhu
AU  - Xianyu Meng
AU  - Zhang Tian
PY  - 2015/12
DA  - 2015/12
TI  - Performance Evaluation of Naval Minesweeping and Estimation of the Number of Remaining Mines based on Bayesian Estimation Theory
BT  - Proceedings of the 2015 6th International Conference on Manufacturing Science and Engineering
PB  - Atlantis Press
SP  - 451
EP  - 455
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmse-15.2015.82
DO  - 10.2991/icmse-15.2015.82
ID  - Chen2015/12
ER  -