Agriculture disease diagnosis expert system based on knowledge and fuzzy reasoning: a case study of flower

  • Authors:

  • Tang Huili;Ye Jiyao;Zhou Lianqing;Shi Zhou

  • Affiliations:

  • Institute of Agricultural Remote Sensing & Information Technology, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, China;Institute of Agricultural Remote Sensing & Information Technology, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, China;Institute of Agricultural Remote Sensing & Information Technology, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, China;Institute of Agricultural Remote Sensing & Information Technology, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, China

  • Venue:
  • FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 3
  • Year:
  • 2009

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Abstract

To fulfill the complexity of agriculture disease problem, fuzzy reasoning method is presented in agriculture disease diagnosis expert system; both positive and negative effects of disease symptoms on diagnosis results have been considered; weighed Euclidean distance method is introduced to calculate the comparability; effective diagnosis results and reliabilities are given out. Finally, a case study of flower is provided to show the reasoning process and examine the diagnosis results. ASP.NET and C# are applied in the system; SQLServer 2005 is adopted for building database.