Reasoning Methods of Unmanned Underwater Vehicle Situation Awareness Based on Ontology and Bayesian Network
When unmanned underwater vehicles (UUVs) perform tasks, the marine environment situation information perceived by their sensors is insufficient and cannot be shared; moreover, the reasoning efficiency of the situation information is not high. To deal with these problems, this paper proposes an ontol...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
|
| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2022/7143974 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832545263341797376 |
|---|---|
| author | Hongfei Yao Chunsong Han Fengxia Xu |
| author_facet | Hongfei Yao Chunsong Han Fengxia Xu |
| author_sort | Hongfei Yao |
| collection | DOAJ |
| description | When unmanned underwater vehicles (UUVs) perform tasks, the marine environment situation information perceived by their sensors is insufficient and cannot be shared; moreover, the reasoning efficiency of the situation information is not high. To deal with these problems, this paper proposes an ontology-based situation awareness information expression method, using the Bayesian network method to reason about situation information. First, the situation awareness information is determined in uncertain events when performing tasks in the marine environment. The core and application ontologies of UUV situation awareness are also established. Subsequently, semantic rules are constructed, and uncertain events are identified through the corresponding semantic rules. The Jess inference engine is used to update the ontology model. Because the ontology cannot reason about uncertainty, it is transformed into the Bayesian network to reason about the impacts of uncertain events on tasks. Simulation experiments verify the effectiveness and accuracy of the situation awareness reasoning method that combines the ontology and the Bayesian network. |
| format | Article |
| id | doaj-art-c460349145cc454995043458b877b4c0 |
| institution | Kabale University |
| issn | 1099-0526 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-c460349145cc454995043458b877b4c02025-02-03T07:26:19ZengWileyComplexity1099-05262022-01-01202210.1155/2022/7143974Reasoning Methods of Unmanned Underwater Vehicle Situation Awareness Based on Ontology and Bayesian NetworkHongfei Yao0Chunsong Han1Fengxia Xu2College of Mechanical EngineeringCollege of Mechanical EngineeringCollege of Mechanical EngineeringWhen unmanned underwater vehicles (UUVs) perform tasks, the marine environment situation information perceived by their sensors is insufficient and cannot be shared; moreover, the reasoning efficiency of the situation information is not high. To deal with these problems, this paper proposes an ontology-based situation awareness information expression method, using the Bayesian network method to reason about situation information. First, the situation awareness information is determined in uncertain events when performing tasks in the marine environment. The core and application ontologies of UUV situation awareness are also established. Subsequently, semantic rules are constructed, and uncertain events are identified through the corresponding semantic rules. The Jess inference engine is used to update the ontology model. Because the ontology cannot reason about uncertainty, it is transformed into the Bayesian network to reason about the impacts of uncertain events on tasks. Simulation experiments verify the effectiveness and accuracy of the situation awareness reasoning method that combines the ontology and the Bayesian network.http://dx.doi.org/10.1155/2022/7143974 |
| spellingShingle | Hongfei Yao Chunsong Han Fengxia Xu Reasoning Methods of Unmanned Underwater Vehicle Situation Awareness Based on Ontology and Bayesian Network Complexity |
| title | Reasoning Methods of Unmanned Underwater Vehicle Situation Awareness Based on Ontology and Bayesian Network |
| title_full | Reasoning Methods of Unmanned Underwater Vehicle Situation Awareness Based on Ontology and Bayesian Network |
| title_fullStr | Reasoning Methods of Unmanned Underwater Vehicle Situation Awareness Based on Ontology and Bayesian Network |
| title_full_unstemmed | Reasoning Methods of Unmanned Underwater Vehicle Situation Awareness Based on Ontology and Bayesian Network |
| title_short | Reasoning Methods of Unmanned Underwater Vehicle Situation Awareness Based on Ontology and Bayesian Network |
| title_sort | reasoning methods of unmanned underwater vehicle situation awareness based on ontology and bayesian network |
| url | http://dx.doi.org/10.1155/2022/7143974 |
| work_keys_str_mv | AT hongfeiyao reasoningmethodsofunmannedunderwatervehiclesituationawarenessbasedonontologyandbayesiannetwork AT chunsonghan reasoningmethodsofunmannedunderwatervehiclesituationawarenessbasedonontologyandbayesiannetwork AT fengxiaxu reasoningmethodsofunmannedunderwatervehiclesituationawarenessbasedonontologyandbayesiannetwork |