Agriculture Disease Diagnosis Expert System Based on Knowledge and Fuzzy Reasoning: A Case Study of Flower

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; SQL server 2005 is adopted for building database.