Obtaining Anti-Missile Decoy Launch Solution from a Ship Using Machine Learning Techniques
One of the most dangerous situations a warship may face is a missile attack launched from other ships, aircrafts, submarines or land. In addition, given the current scenario, it is not ruled out that a terrorist group may acquire missiles and use them against ships operating close to the coast, whic...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Universidad Internacional de La Rioja (UNIR)
2022-06-01
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| Series: | International Journal of Interactive Multimedia and Artificial Intelligence |
| Subjects: | |
| Online Access: | https://www.ijimai.org/journal/bibcite/reference/3042 |
| _version_ | 1818545921947860992 |
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| author | Ramón Touza Javier Martínez Torres María Álvarez Javier Roca |
| author_facet | Ramón Touza Javier Martínez Torres María Álvarez Javier Roca |
| author_sort | Ramón Touza |
| collection | DOAJ |
| description | One of the most dangerous situations a warship may face is a missile attack launched from other ships, aircrafts, submarines or land. In addition, given the current scenario, it is not ruled out that a terrorist group may acquire missiles and use them against ships operating close to the coast, which increases their vulnerabilitydue to the limited reaction time. One of the means the ship has for its defense are decoys, designed to deceive the enemy missile. However, for their use to be effective it is necessary to obtain, in a quick way, a valid launching solution. The purpose of this article is to design a methodology to solve the problem of decoy launching and to provide the ship immediately with the necessary data to make the firing decision. To solve the problem machine learning models (neural networks and support vector machines) and a set of training data obtained in simulations will be used. The performance measures obtained with the implementation of multilayer perceptron models allow the replacement of the current procedures based on tables and launching rules with machine learning algorithms that are more flexible and adaptable to a larger number of scenarios. |
| first_indexed | 2024-12-12T07:46:18Z |
| format | Article |
| id | doaj.art-e9aa3cd976ea4f16a56876323503b6b8 |
| institution | Directory Open Access Journal |
| issn | 1989-1660 |
| language | English |
| last_indexed | 2024-12-12T07:46:18Z |
| publishDate | 2022-06-01 |
| publisher | Universidad Internacional de La Rioja (UNIR) |
| record_format | Article |
| series | International Journal of Interactive Multimedia and Artificial Intelligence |
| spelling | doaj.art-e9aa3cd976ea4f16a56876323503b6b82022-12-22T00:32:36ZengUniversidad Internacional de La Rioja (UNIR)International Journal of Interactive Multimedia and Artificial Intelligence1989-16602022-06-017416317010.9781/ijimai.2021.11.001ijimai.2021.11.001Obtaining Anti-Missile Decoy Launch Solution from a Ship Using Machine Learning TechniquesRamón TouzaJavier Martínez TorresMaría ÁlvarezJavier RocaOne of the most dangerous situations a warship may face is a missile attack launched from other ships, aircrafts, submarines or land. In addition, given the current scenario, it is not ruled out that a terrorist group may acquire missiles and use them against ships operating close to the coast, which increases their vulnerabilitydue to the limited reaction time. One of the means the ship has for its defense are decoys, designed to deceive the enemy missile. However, for their use to be effective it is necessary to obtain, in a quick way, a valid launching solution. The purpose of this article is to design a methodology to solve the problem of decoy launching and to provide the ship immediately with the necessary data to make the firing decision. To solve the problem machine learning models (neural networks and support vector machines) and a set of training data obtained in simulations will be used. The performance measures obtained with the implementation of multilayer perceptron models allow the replacement of the current procedures based on tables and launching rules with machine learning algorithms that are more flexible and adaptable to a larger number of scenarios.https://www.ijimai.org/journal/bibcite/reference/3042machine learningmissiledecoysmultilayer perceptronsupport vector machine |
| spellingShingle | Ramón Touza Javier Martínez Torres María Álvarez Javier Roca Obtaining Anti-Missile Decoy Launch Solution from a Ship Using Machine Learning Techniques International Journal of Interactive Multimedia and Artificial Intelligence machine learning missile decoys multilayer perceptron support vector machine |
| title | Obtaining Anti-Missile Decoy Launch Solution from a Ship Using Machine Learning Techniques |
| title_full | Obtaining Anti-Missile Decoy Launch Solution from a Ship Using Machine Learning Techniques |
| title_fullStr | Obtaining Anti-Missile Decoy Launch Solution from a Ship Using Machine Learning Techniques |
| title_full_unstemmed | Obtaining Anti-Missile Decoy Launch Solution from a Ship Using Machine Learning Techniques |
| title_short | Obtaining Anti-Missile Decoy Launch Solution from a Ship Using Machine Learning Techniques |
| title_sort | obtaining anti missile decoy launch solution from a ship using machine learning techniques |
| topic | machine learning missile decoys multilayer perceptron support vector machine |
| url | https://www.ijimai.org/journal/bibcite/reference/3042 |
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