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Analysis and Usage of Fuzzy Logic for Optimized Evaluation of Database Queries

by Sardar Sathpal Singh, Prof. Rishi Sayal, P. Venkat Rao
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 16 - Number 3
Year of Publication: 2011
Authors: Sardar Sathpal Singh, Prof. Rishi Sayal, P. Venkat Rao
10.5120/1993-2686

Sardar Sathpal Singh, Prof. Rishi Sayal, P. Venkat Rao . Analysis and Usage of Fuzzy Logic for Optimized Evaluation of Database Queries. International Journal of Computer Applications. 16, 3 ( February 2011), 19-26. DOI=10.5120/1993-2686

@article{ 10.5120/1993-2686,
author = { Sardar Sathpal Singh, Prof. Rishi Sayal, P. Venkat Rao },
title = { Analysis and Usage of Fuzzy Logic for Optimized Evaluation of Database Queries },
journal = { International Journal of Computer Applications },
issue_date = { February 2011 },
volume = { 16 },
number = { 3 },
month = { February },
year = { 2011 },
issn = { 0975-8887 },
pages = { 19-26 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume16/number3/1993-2686/ },
doi = { 10.5120/1993-2686 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:03:52.889702+05:30
%A Sardar Sathpal Singh
%A Prof. Rishi Sayal
%A P. Venkat Rao
%T Analysis and Usage of Fuzzy Logic for Optimized Evaluation of Database Queries
%J International Journal of Computer Applications
%@ 0975-8887
%V 16
%N 3
%P 19-26
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The majority of existing information systems deals with crisp data through crisp database systems. Retrieval of specific queries through fuzzy logic systems have been a rare approach in research. Use of fuzzy logic rule based systems on data bases has shown efficient results experimentally. As such no early work has been done on combination of rule based systems with the database queries to give an efficient output. This paper brings such concise theme of evaluating a student’s performance through such rule based systems. The aim of this paper is to present various fuzzification logic combined with rule based systems. Further experimentally this paper proves that for specific applications on databases using rule based systems can give much better results rather than using simple crisp queries with simple database management. This paper also gives a brief overview of various fuzzy logics, concepts fuzzification and defuzzification. This novel property of rule based system on any database system to evaluate for the performances is the main theme of this paper.

References
  1. L.A. Zadeh, Fuzzy Sets, Information and Control, 1965
  2. L.A. Zadeh, Outline of a New Approach to the Analysis of of Complex Systems and Decision Processes, 1973
  3. L.A. Zadeh,”Fuzzy algorithms,” Info. & Ctl. Vol. 12, 1968, pp. 94-102.
  4. L.A. Zadeh,”Making computers think like people,” IEEE. Spectrum, 8/1984, pp. 26-32.
  5. S. Korner,”Laws of thought,” Encyclopedia of Philosophy, Vol. 4, MacMillan, NY: 1967, pp. 414-417.
  6. C. Lejewski,”Jan Lukasiewicz,” Encyclopedia of Philosophy, Vol. 5, MacMillan, NY: 1967, pp.104-107.
  7. A. Reigber,”My life with Kostas”, unpublished report, Neverending Story Press, 1999
  8. J.F. Baldwin,”Fuzzy logic and fuzzy reasoning,” in Fuzzy Reasoning and Its Applications, E.H.Mamdani and B.R. Gaines (eds.), London: Academic Press, 1981.
  9. W. Bandler and L.J. Kohout, ”Semantics of implication operators and fuzzy relational products,” in Fuzzy Reasoning and Its Applications, E.H. Mamdani and B.R. Gaines (eds.), London: AcademicPress, 1981.
  10. M. Eschbach and J. Cunnyngham, ”The logic of fuzzy Bayesian influence,” paper presented at the International Fuzzy Systems Association Symposium of Fuzzy information Processing in Artificial Intelligence and Operational Research, Cambridge, England: 1984.
  11. F. Esragh and E.H. Mamdani, ”A general approach to linguistic approximation,” in Fuzzy Reasoning and Its Applications, E.H. Mamdani and B.R. Gaines (eds.), London: Academic Press, 1981.
  12. J. Fox, ”Towards a reconciliation of fuzzy logic and standard logic,” Int. Jrnl. of Man-Mach. Stud., Vol. 15, 1981, pp. 213-220.
  13. S. Haack, ”Do we need fuzzy logic?” Int. Jrnl. of Man-Mach. Stud., Vol. 11, 1979, pp.437-445. Proceedings of a Symposium Organized by the Austrian Society for Cybernetic Studies, Hemisphere Publ. Co., NY: 1982.
  14. Shi-Kuo Chang and Wu-Haung Cheng. “DataBase Skeleton and Its Application to Logical DataBase Synthesis”, IEEE Transaction on Software Engineering, Vol. SE-4, No. 1, January 1978.
  15. Eugene Wong. “A Statistical Approach to Incomplete Information in DataBase Systems”, ACM Transactions on DataBase Systems, Vol. 7, No. 3, September 1982, pp. 470-488.
  16. Valiollah Tahani. “A Conceptual Framework for Fuzzy Query Processing - A Step toward very Intelligent DataBase Systems”, Information Processing & Management, Vol. 13, 1977.
  17. Janusz Kacprzyk and A. Ziolkowski. “DataBase Queries with Fuzzy Linguistic Quantifiers”, IEEE Transactions on Systems, Man, and Cybernetics, Vol. SMC-16, No. 3, May/June 1986.
  18. Janusz Kacprzyk et al. “FQUERY lll+: A 'Human- Consistent' DataBase Querying System Based on Fuzzy Logic with Linguistic Quantifiers”, Information Systems, Vol. 14, No. 6, 1989.
  19. M. H. Wong and K. S. Leung. “A Fuzzy DataBase- Query Language”, Information Systems, Vol. 13, No. 5, 1990.
  20. P. Bosc et al. “Fuzzy Querying with SQL: Extensions and Implementation Aspect”, Fuzzy Sets and Systems, Vol. 28, 1988, pp. 333-349.
Index Terms

Computer Science
Information Sciences

Keywords

Fuzzification Defuzzification Rule-Based System Database Fuzzy Sets

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