Building of CBR’s DB Using Ontology for a Collision Avoidance System

• Autorzy: Park G. K. , Kim W. G. , Benedictos J.
• Języki publikacji: EN

Abstrakty

EN

We have proposed Fuzzy-CBR to find a solution from past knowledge retrieved from the database and adapted to the new situation. However, ontology is needed in identifying concepts, relations and instances that are involved in a situation in order to improve and facilitate the efficient retrieval of similar cases from the CBR database. This paper proposes the way to apply ontology for identifying the concepts involved in a new case, used as inputs, for ship collision avoidance support system and in solving for similarity through document articulation and abstraction levels. These ontologies will be used to build a conceptual model of a manoeuvring situation.

Słowa kluczowe

EN

anticollision; ontology; Collision Avoidance System; Case Based Reasoning (CBR); Fuzzy CBR Technique; CBR Data Base; Manoeuvring Situations; Risk of Collision

• Wydawca: Faculty of Navigation, Gdynia Maritime University
• Czasopismo: TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
• Rocznik: 2008
• Tom: Vol. 2, no. 4
• Strony: 369--374
• Opis fizyczny: Bibliogr. 11 poz., rys., tab.

Twórcy

autor

Park G. K.

• Mokpo National Maritime University,

autor

Kim W. G.

• Mokpo National Maritime University,

autor

Benedictos J.

• Mokpo, South Korea

Bibliografia

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• 2 Nam-Kyun Im and Gei-Kark Park, 2005, Simulation Study on Auto Navigation System. pp. 572-576, Proceedings of the 6th International Symposium on Advanced Intelligent Systems.
• 3 Yong-Nam Na, Wang-gyu Choi and Sung-juu Lee, 2003, Self Organizing Fuzzy Controller Using Command Fusion Method and Genetic Algorithm, International Journal for Fuzzy Logic and Intelligent Systems.
• 4 Gei-Kark Park, John Leslie RM Benedictos, 2006, Ship’s Collision Avoidance System Using Fuzzy-CBR, Vol.16, No. 2, pp. 39-44, Proc. of KFIS Autumn Conference, Gumi, 17-18 November.
• 5 Ian Watson, 1998, CBR is a methodology not a technology, In, Research and Development in Expert Systems XV.
• 6 Toshiro Iwatani, Shun'ichi Tano and Wataro Okamoto, 1994, Fuzzy Case Base Reasoning in FLINS (Fuzzy Lingual Reasoning), LIFE Technical Report, TR-4N020.
• 7 Shun'ichi Tano, Toshiro Iwatani, Wataro Okamoto, Atsoushi Inoue and Ryousuke Fojioka, Fuzzy Natural Language Communication System - FLINS: Concept and Conversation Examples, FUZZ-IEEE'95, pp. 1039-1044, 1995.
• 8 Ryousuke Fojioka, Shun'ichi Tano, Wataro Okamoto, Atsoushi Inoue and Toshiro Iwatani, Treatment of fuzziness in natural language by Fuzzy Lingual Sytem - FLINS, FUZZ-IEEE'95. pp.1045-1050, 1995.
• 9 Agnar Aadmont and Enric Plaza, Case-Based Reasoning: Foundational Issues, Methodological Variations, and system approaches,AI Communications, 7(1):39-59, 1994.
• 10 R.Nossum and V.Oleschuk, Dynamic Documents Indexing in Evolving Contexts,Vol=151, Proceedings on CIR’05 Workshop on Context Based Information Retrieval, <http://sunsite.informatik.rwth-aachen.de/Publications/CEUR-WS/Vol-151/index.html >.
• 11 D.M.Sanches, J.M.Cavero and E. Marcos, On Models and Ontologies, 1st Workshp on Philosophical Foundations of Information systems Engineering, PHISE05, 2005 <http://kybele.escet.urjc.es/PHISE05/index.php?page=Program>