Study on the agricultural knowledge representation model based on fuzzy production rules

  • Authors:
  • Chun-Jiang Zhao;Hua-Rui Wu

  • Affiliations:
  • National Engineering Research Center for Information Technology in Agriculture, Beijing, China and Key Laboratory for Information Technologies in Agriculture, The Ministry of Agriculture, Beijing, ...;National Engineering Research Center for Information Technology in Agriculture, Beijing, China and Key Laboratory for Information Technologies in Agriculture, The Ministry of Agriculture, Beijing, ...

  • Venue:
  • ICIC'09 Proceedings of the 5th international conference on Emerging intelligent computing technology and applications
  • Year:
  • 2009

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Abstract

The broad knowledge source in the agricultural field causes many problems such as poor knowledge structure, fuzzy and uncertain representation of objective phenomena, which requires that, in the agricultural intelligent system, the knowledge representation and processing pattern could reflect this kind of uncertainty or fuzziness. The representation and reasoning capability of traditional production rules, however, is somewhat insufficient in the representation of knowledge uncertainty or fuzziness. In order to overcome the foregoing insufficiency, the weighed fuzzy logic production rule was put forward to characterize the uncertainty or fuzzy knowledge; the descriptive method of fuzzy production rules was proposed based on BNF, finally, the feasibility and validity of fuzzy production rules on the representation of the uncertain and fuzzy agricultural knowledge was tested with the implemented instance of wheat expert system.