Abstract
This paper presents the architecture of a communication system which was implemented in MiG-29 airplanes. This system provides a continuous on-line access to the situational awareness information which is necessary for the pilot. The interoperability of this system with other NATO systems allows to collect and transfer data between them. Artificial Intelligence methods are used to implement and improve this system. This modification enables the system to work faster and increases the situational awareness of the pilot on the battlefield.
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Angryk, R.A., Czerniak, J.: Heuristic algorithm for interpretation of multi-valued attributes in similarity-based fuzzy relational databases. Int. J. Approximate Reasoning 51(8), 895–911 (2010)
Apiecionek, Ł., Romantowski, M.: Secure IP network model. Comput. Method Sci. Technol. 4, 209–213 (2013)
Apiecionek, Ł., Romantowski, M., Śliwa, J., Jasiul, B., Goniacz, R.: Safe exchange of information for civil-military operations. In: Military Communications and Information Technology: A Comprehensive Approach Enabler, pp. 39–50 (2011)
Apiecionek, Ł., Biernat, D., Makowski, W., Lukasik, M.: Practical implementation of AI for military airplane battlefield support system. In: 2015 8th International Conference on Human System Interactions (HSI), pp. 249–253. IEEE (2015)
Apiecionek, Ł., Czerniak, J.M., Zarzycki, H.: Protection tool for distributed denial of services attack. In: Kozielski, S., Mrozek, D., Kasprowski, P., Małysiak-Mrozek, B. (eds.) BDAS 2014. CCIS, vol. 424, pp. 405–414. Springer, Heidelberg (2014)
Apiecionek, L., Romantowski, M.: Security solution for cloud computing (2014)
Bradtke, S.J., Barto, A.G.: Learning to predict by the method of temporal differences. Mach. Learn. 22, 33–57 (1996). (Springer)
Kosinski, W., Prokopowicz, P., Slezak, D.: On algebraic operations on fuzzy reals. In: Rutkowski, L., Kacprzyk, J. (eds.) Neural Networks and Soft Computing. Advances in Soft Computing, vol. 19, pp. 54–61. Springer, Heidelberg (2003)
Kozielski, M., Skowron, A., Wróbel, Ł., Sikora, M.: Regression rulelearning for methane forecasting in coal mines. In: Kozielski, S., Mrozek, D., Kasprowski, P., Małysiak-Mrozek, B., Kostrzewa, D. (eds.) BDAS 2015. CCIS, vol. 521, pp. 495–504. Springer, Heidelberg (2015)
Kruszynski, H., Kosowski, T., Apiecionek, L.: CID server JASMINE. In: V Communications Conference in Sieradz (2014)
Lojka, T., Zolota, M., Zolotová, I., et al.: Communication engine in human-machine alarm interface system. In: Sincak, P., Hartono, P., Vircikova, M., Vascak, J., Jaksa, R. (eds.) Emergent Trends in Robotics and Intelligent Systems. Advances in Intelligent Systems and Computing, pp. 129–136. Springer, Heidelberg (2015)
Vidhate, D., Kulkarni, P.: Cooperative machine learning with information fusion for dynamic decision making in diagnostic applications. In: 2012 International Conference on Advances in Mobile Network, Communication and its Applications (MNCAPPS), pp. 70–74. IEEE (2012)
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Apiecionek, Ł., Makowski, W., Woźniak, M. (2016). AI Implementation in Military Combat Identification – A Practical Solution. In: Kozielski, S., Mrozek, D., Kasprowski, P., Małysiak-Mrozek, B., Kostrzewa, D. (eds) Beyond Databases, Architectures and Structures. Advanced Technologies for Data Mining and Knowledge Discovery. BDAS BDAS 2015 2016. Communications in Computer and Information Science, vol 613. Springer, Cham. https://doi.org/10.1007/978-3-319-34099-9_51
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DOI: https://doi.org/10.1007/978-3-319-34099-9_51
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