Ontology-based Instantaneous Route Suggestion of Enemy Warplanes with Unknown Mission Profile

Yıl 2020, , 803 - 818, 01.10.2020

Emre Çintaş , Barış Özyer , Sinan Hanay

https://doi.org/10.16984/saufenbilder.711109

Öz

The routes of warplanes are planned confidentially, and they are not shared with any organization in advance. In some cases, border violations may occur, and as a result, it increases the tension between two states. This situation puts many people at risk and impairs the prestige of the state both economically and socially. In this paper, Ontology-Based Instantaneous Route Suggestion System (SUARSIS) based on semantic approach is proposed to predict and plan routes of warplanes before they reach their target. In the proposed system, we developed an architecture called Ontology-based Route Suggestion by using the OWL (Web Ontology Language) language with realistic data. The aircraft model, aircraft fuel system, features of the military field, and the relations in the semantic context are logically defined through ontology. Synthetic scenarios were created to validate the accuracy of the proposed method. Experimental results show that the proposed system has a good performance on predicting warplane routes.

Anahtar Kelimeler

Route suggestion system, semantic web, ontology, intelligent search engines, warplanes

Kaynakça

• Flightradar24 (2020). Live Flight Tracker [online]. Website https://www.flightradar24.com [accessed 09 January 2020].
• Anonymous (2020). Military Ontology [online]. Website http://rdf.muninn-project.org/ontologies/military.html [accessed 02 February 2020].
• T. Berners-Lee, J. Hendler and O. Lassila, “The Semantic Web,” Scientific American, Vol. 284, No. 5, pp. 34-43, 2001.
• J. Cantais, D. Dominguez, V. Gigante, L. Laera and V. Tamma, “An example of food ontology for diabetes control,” In: International Semantic Web Conference on Ontology Patterns for the Semantic Web, Galway, Ireland, pp. 1-9, 2005.
• D. Çelik Ertuğrul, “FoodWiki: A Mobile App Examines Side Effects of Food Additives via Semantic Web,” Journal of Medical Systems, Vol. 40, No. 2, pp. 1-15, 2016.
• D. Çelik, “Towards a semantic-based information extraction system for matching resumes to job openings,” Turkish Journal of Electrical Engineering & Computer Sciences, Vol. 24, No. 1, pp. 141-159, 2016.
• J. Samper, V. Tomas, J. Martinez and L. VandenBerg, “An ontological infrastructure for traveller information systems,” In: IEEE Intelligent Transportation Systems Conference (ITSC06), Toronto, Canada, pp. 1197–1202, 2006.
• A. Gangemi and J. Euzenat, “GoodRelations: An ontology for describing products and services offers on the web,” In: International Conference on Knowledge Engineering and Knowledge Management, Berlin, pp. 329-346, 2008.
• J. Nederstigt, S.S. Aanen, D. Vandic and F. Frasincar, “Floppies: A framework for large-scale ontology population of product information from tabular data in E-commerce stores,” Decision Support System, Vol. 59, No. 1, pp. 296-311, 2014.
• C.B. Auer, G. Kobilarov, J. Lehmann, R. Cyganiak and Z. Ives, “DBpedia: A nucleus for a web of open data,” In: 6th International Semantic Web Conference (ISWC), Berlin, pp. 722–735, 2007.
• K. Bollacker, C. Evans, P. Paritosh, T. Sturge and J. Taylor, “Freebase: a collaboratively created graph database for structuring human knowledge,” In: ACM SIGMOD International Conference on Management of Data, Canada, pp. 1247–1250, 2008.
• G. W. F. M. Suchanek, “YAGO: a core of semantic knowledge,” In: ACM 16th International Conference on World Wide Web, Banff, AB, Canada, pp. 697–706, 2007.
• D. Vrandecic, “Wikidata: a new platform for collaborative data collection,” In: ACM 21th International Conference on World Wide Web, Lyon, France, pp. 1063–1064, 2012.
• J.B. Carlson, B. Kisiel, B. Settles, E.R. Hruschka and T. M. Mitchell, “Toward an architecture for never-ending language learning,” In: Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, Buenos Aires, Argentina, pp. 1306–1313, 2010.
• M. Nickel, K. Murphy, V. Tresp and E. A. Gabrilovich, “A review of relational machine learning for knowledge graphs,” In: Proceedings of the IEEE, pp. 11–33, 2016.
• R. M. Nor, M. F. Ramli and M. H. Kharuddin, “Modeling and Simulation of Vehicle Routing Problem Based on Clustering Locations,” Institute of Engineering Mathematics, Vol. 23, No. 5, pp. 4146-4148, 2017.
• P. L. N. U. Cooray and T. D. Rupasinghe, “Machine Learning-Based Parameter Tuned Genetic Algorithm for Energy Minimizing Vehicle Routing Problem,” Journal of Industrial Engineering, Vol. 2017, No. 2017, pp. 1–13, 2017.
• M. A. Dramski, “Comparison between Dijkstra algorithm and simplified ant colony optimization in navigation,” Scientific Journals, Vol. 29, No. 2012, pp. 25-29, 2012.
• F. Scholer, “3D Path Planning for Autonomous Aerial Vehicles in Constrained Spaces,” PhD, Aalborg University, Denmark, 2012.
• X. Yang, M. Ding, C. Zhou and S. Shou, “Fast on-ship route planning using improved sparse A-star algorithm for UAVs,” In: Proceedings of SPIE - The International Society for Optical Engineering, 2009.
• G. Shang, Z. Lei, Z. Fengting and Z. Chunxian, “Solving Traveling Salesman Problem by Ant Colony Optimization Algorithm with Association Rule,” In: Third International Conference on Natural Computation (ICNC2007), Haikou, China, pp. 693-698, 2007.
• B. Özkan, U. Cevre and A. Uğur, “Melez Bir Eniyileme Yöntemi ile Rota Planlama,” Akademik Bilişim Konferansı, Çanakkale, pp. 1-9 (in Turkish) 2008.
• E. Kasturi, D. S. Prasanna, K. S. Vinu and S. Manivannan, “Airline Route profitability analysis and Optimization using BIG DATA analytics on aviation data sets under heuristic techniques,” Procedia Computer Science, Vol. 87, No. 2016, pp. 86-92, 2016.
• S. Bakhtyar and J. Holmgren, “A Data Mining Based Method for Route and Freight Estimation,” Procedia Computer Science, Vol. 52, No. 2015, pp. 396-403, 2015.
• SWRL, “A Semantic Web Rule Language Combining OWL and RuleML,” W3C Member, Submission 21, 2004.
• M. Cavcar, “Aerodinamik Kuvvetler Özet,” Anadolu Üniversitesi, (in Turkish) 2011.
• M. Cavcar, “Seyahat Performansı - Menzil Özet,” Anadolu Üniversitesi, (in Turkish) 2014.
• RI. Martinez-Va and E. Perez, “Optimum cruise lift coefficient in initial design of jet aircraft,” Journal of Aircraft, Vol. 4, No. 1992, pp. 712-714, 1992.
• M. Horridge and S. Bechhofer, “The OWL API: A Java API for OWL Ontologies,” Semantic Web, Vol. 1, No. 2011, pp. 11-21, 2011.
• E. Sirin, B. Parsia, B. C. Grau, A. Kalyanpur and Y. Katz, “PELLET: A practical owl-dl reasoner, Web Semantics: science, services and agents on the World Wide Web,” Journal of Web Semantics, Vol. 5, No. 2007, pp. 51-53, 2007.
• S. Hartanto, M. Furqan, U. P. A. Siahaan and W. Fitriani, “Haversine Method in Looking for the Nearest Masjid,” International Journal of Engineering Research, Vol. 3, No. 2017, pp. 187-195, 2017.
• Netbeans (2020). Netbeans 8.2 IDE [online]. Website https://netbeans.org/ [accessed 10 January 2020].