Comparative Analysis on Performance Evaluation of Naval Minesweeping
Authors
Huidong Lu, Xinqin Chen, Wei Zhang, Chang Shu, Xuanmin Li, Longteng Li, Chengwen Zhu
Corresponding Author
Huidong Lu
Available Online April 2016.
- DOI
- 10.2991/icmit-16.2016.62How to use a DOI?
- Keywords
- Markov process Bayesian estimation minesweeping probability remaining mine
- Abstract
The estimation of number of remaining mines is an important basis for the performance evaluation of naval minesweeping, and the accuracy of the estimation is related to the mastery of prior information and the selection of evaluation model. In this paper, we build the evaluation models by employing Markov process and Bayesian estimation theory to estimate the number of remaining mines. Then simulation experiments based on the above models were carried out, using the operational data which come from prior information of the minefield and information of swept mines. The results show that the Bayesian estimation is more reliable than Markov process in the case of sufficient prior information.
- 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/).
Cite this article
TY - CONF AU - Huidong Lu AU - Xinqin Chen AU - Wei Zhang AU - Chang Shu AU - Xuanmin Li AU - Longteng Li AU - Chengwen Zhu PY - 2016/04 DA - 2016/04 TI - Comparative Analysis on Performance Evaluation of Naval Minesweeping BT - Proceedings of the 2016 3rd International Conference on Mechatronics and Information Technology PB - Atlantis Press SP - 354 EP - 358 SN - 2352-538X UR - https://doi.org/10.2991/icmit-16.2016.62 DO - 10.2991/icmit-16.2016.62 ID - Lu2016/04 ER -