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Toward efficient modeling of fuzzy expert systems: a survey

Author

Listed:
  • S. Aly

    (Czech University of Agriculture, Prague, Czech Republic)

  • I. Vrana

    (Czech University of Agriculture, Prague, Czech Republic)

Abstract

Efficient modeling of the artificial intelligence tools has become a necessity in order to cut down the development and maintenance cost associated with building application systems in the business, industrial and agriculture sectors that are frequently amendable to sudden unexpected environmental and economic conditions changes. This can be accomplished through developing an efficient modeling language which exploits the beneficial features of the emerging object-oriented technology. This research is aimed at reviewing the recent scientific aspects of the research concerning conceptual modeling of fuzzy knowledge-based system, which exhibits a large extent of applicability in last few decades due to its capability to deal with vagueness, uncertainty and subjectivity, those are inherent in real world problems. The most recent researches and applications of fuzzy expert system are surveyed. The existing knowledge modeling techniques are reviewed and the prominent ones are pinpointed. This paper is intended to identify the main and common bottlenecks of the existing knowledge modeling tools to overcome it in developing a reliable conceptual model of fuzzy expert system.

Suggested Citation

  • S. Aly & I. Vrana, 2006. "Toward efficient modeling of fuzzy expert systems: a survey," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 52(10), pages 456-460.
    • Handle: RePEc:caa:jnlage:v:52:y:2006:i:10:id:5051-agricecon
    DOI: 10.17221/5051-AGRICECON
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    References listed on IDEAS

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    1. Kun Chang Lee & Jae Ho Han & Yong Uk Song & Won Jun Lee, 1998. "A fuzzy logic‐driven multiple knowledge integration framework for improving the performance of expert systems," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 7(4), pages 213-222, December.
    2. Ngai, E. W. T. & Wat, F. K. T., 2003. "Design and development of a fuzzy expert system for hotel selection," Omega, Elsevier, vol. 31(4), pages 275-286, August.
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