Method of on-call submarine searching for surface ship formation based on hidden Markov model Article Swipe
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.19693/j.issn.1673-3185.01507
[Objectives] In order to improve the successful probability of searching for target submarines and to make the operation of the surface ship formation more effectively,the problem about the path planning for the on-call submarine searching for ships is studied.[Methods] Firstly, an on-call submarine searching model of surface ships was constructed based on the Hidden Markov Model(HMM). A two-stage heuristic method was designed to maximize the probability of searching for submarine search expectation. The problem of local optimum was avoided by using evolutionary algorithm(EA)to cross and mutate the individuals in the population,and a comparison with conventional searching methods was made. Then, the effects of different segmentation methods on path optimization were studied experimentally.[Results] The simulation results of single-ship and multi-ship searching for submarines show that the method adopted in this paper can obtain the maximum submarine search expectation and the optimal searching path. The segmentation times experiment show that a reasonable re-division of the search area is beneficial to find a better searching path.[Conclusions] This model can find an optimal path for submarine search and improve the searching efficiency of the surface ship formation.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doaj.org/article/b725aa64de3f4df4a8acc8aba9c44235
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4389411645
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4389411645Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.19693/j.issn.1673-3185.01507Digital Object Identifier
- Title
-
Method of on-call submarine searching for surface ship formation based on hidden Markov modelWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2019Year of publication
- Publication date
-
2019-12-01Full publication date if available
- Authors
-
Bian Dapeng, Shanshan Yu, Zhang‐Zhi Shi, Minghui Yu, Yun WangList of authors in order
- Landing page
-
https://doaj.org/article/b725aa64de3f4df4a8acc8aba9c44235Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://doaj.org/article/b725aa64de3f4df4a8acc8aba9c44235Direct OA link when available
- Concepts
-
Submarine, Hidden Markov model, Marine engineering, Computer science, Markov chain, Surface (topology), Markov model, Artificial intelligence, Engineering, Mathematics, Machine learning, GeometryTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.studied.<b>[Methods]</b> | 38 |
| abstract_inverted_index.path.<b>[Conclusions]</b> | 162 |
| abstract_inverted_index.experimentally.<b>[Results]</b> | 111 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| citation_normalized_percentile.value | 0.42160488 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |