원문정보
보안공학연구지원센터(IJBSBT)
International Journal of Bio-Science and Bio-Technology
Vol.6 No.5
2014.10
pp.143-152
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
Handling uncertainty and impreciseness of knowledge appears to be a challenging task in Information Systems. Intuitionistic fuzzy (IF) set theory and rough set theory enhances databases by allowing it for the management of uncertainty and impreciseness. This paper presents a new efficient query optimization technique for the multi-valued or imprecise IF rough database. The usefulness of this technique was illustrated on malaria knowledge from the rural tribal communities of Tripura where most of the information is multi-valued and imprecise. Then the querying about knowledge on malaria is executed into SQL server to make the implementation of IF rough data querying simpler.
목차
Abstract
1. Introduction
2. Preliminaries
2.1. Intuitionistic Fuzzy (IF) set [1]
2.2. Rough Set [9]
3. IF Rough Relational Database Model [5, 6]
3.1. IF Rough Methodology
3.2. IF Rough Algorithm
4. Application: Knowledge towards Malaria
4.1 Table Design
5. SQL: IF ROUGH DATA QUERIES
6. Conclusion
References
APPENDIX
1. Introduction
2. Preliminaries
2.1. Intuitionistic Fuzzy (IF) set [1]
2.2. Rough Set [9]
3. IF Rough Relational Database Model [5, 6]
3.1. IF Rough Methodology
3.2. IF Rough Algorithm
4. Application: Knowledge towards Malaria
4.1 Table Design
5. SQL: IF ROUGH DATA QUERIES
6. Conclusion
References
APPENDIX
저자정보
참고문헌
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