[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.5391/JKIIS.2007.17.3.390

Conceptual Model for Fuzzy-CBR Support System for Collision Avoidance at Sea Using Ontology

Park, Gyei-Kark (Faculty of Maritime Transportation System)
Kim, Woong-Gyu (Graduate School, Department of Maritime Transportation System Mokpo National Maritime University)
Benedictos, John Leslie RM (Graduate School, Department of Maritime Transportation System Mokpo National Maritime University)

Publication Information

Journal of the Korean Institute of Intelligent Systems / v.17, no.3, 2007 , pp. 390-396 More about this Journal

Abstract

Fuzzy-CBR Collision Avoidance Support System is a system that finds a solution from past knowledge retrieved from the database and adapted to a new situation. Its algorithm has resulted to an adapting a solution for a 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 environment and use them as inputs, for a ship collision avoidance support system., Similarity will be obtained through document articulation and using abstraction levels. A conceptual model of a maneuvering situation will be built using these ontologies.

Keywords

Ontology; conceptual model; mapping; similarity; abstraction level; Fuzzy-CBR; retrieve; adapt;

Citations & Related Records

Reference

1	A. Aadmont and E. Plaza, Case-Based Reasoning: Foundational Issues, Methodological Variations, and system approaches, AI Communications, 7(1):39-59, 1994
2	R. Nossum and V. Oleschuk, Dynamic Documents Indexing in Evolving Contexts, CiteSee.IST Scientific Literature and Digital Library, Microsoft research, National Science Foundation, Nasa,
3	R. Fojioka, S. Tano, W. Okamoto, A. Inoue and T. Iwatani, Treatment of fuzziness in natural language by Fuzzy Lingual Sytem -FUNS, FUZZ-IEEE'95. pp.1045-1050, 1995
4	H. J. Lee and K. P. Rhee, Development of Collision Avoidance System by Using Expertand Search Algorithm, Int'l. Ship Building System, Vol.48, No.3, pp.197-210, 2001
5	D. M. Sanches, J. M. Cavero and E. Marcos, On Models and Ontologies, 1st Workshp on Philosophical Foundations of Information systems Engineering, PHISE05,
6	T. Iwatani, S. Tano and W. Okamoto, Fuzzy Case Base Reasoning in FUNS (Fuzzy Lingual Reasoning), UFE Technical Report, TR-4N020, 1994
7	Y. N. Na, W. G. Choi and S. J. Lee, Self Organizing Fuzzy Controller Using Command Fusion Method and Genetic Algorithm. International Journal for Fuzzy Logic and Intelligent Systems, 2003
8	I. Watson, CBR is a methodology not a technology, In, Research and Development in Expert Systems XV, 1998
9	S. Tano, T. Iwatani, W. Okamoto, A. Inoue and R. Fojioka, Natural Language Communication System-Concept and Conversation Examples. pp. 1039-1044, 1995
10	G. K. Park, J. L. R. M. Benedictos, Ship's Collision Avoidance System Using Fuzzy-CBR, Vol.16, No.2, pp. 39-44, Proc. of KFIS Autumn Conference, 2006
11	N. K. Im and G. K. Park, Simulation Study on Auto Navigation System. pp. 572-576, Proc. of the 6th Symposium on Advanced Intelligent Systems, 2005