水稻病害预报模型数据
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针对水稻品种,根据水稻当前物候期,基于气象数据、历史经验数据,获取当地植保站水稻病情预报信息,结合巡检人员巡检信息,对水稻可能发生或已经发生的病害进行预报。1、数据采集:通过业务系统采集品种、水稻物候期、巡检病害名称等信息;通过API调用当地植保站病害名称等信息;通过物联网设备监测采集气象信息。 2、数据处理:基于气象条件等数据,采用模糊假言推理算法FMP来实现水稻病害的短期预警。模糊假言推理FMP:R(x,y)= R(A(x),B(y)),(X,Y)∈X*Y 3、数据应用:通过动态监测、分析水稻病害数据,为农业主体提供病害预警,避免大面积病害发生,保障水稻生产。
This dataset is developed for rice variety-specific disease forecasting. It forecasts potential or already occurring rice diseases by leveraging the current phenological stages of rice, meteorological data, historical empirical data, local plant protection station's rice disease forecast information, and on-site inspection records. 1. Data Collection: Information including rice varieties, rice phenological stages, and inspected disease names is collected via the business system; Relevant disease name information from local plant protection stations is obtained through API calls; Meteorological data is collected via IoT device monitoring. 2. Data Processing: Short-term early warning of rice diseases is implemented based on meteorological conditions and related data using the Fuzzy Modus Ponens (FMP) algorithm. The formal definition of Fuzzy Modus Ponens (FMP) is: $R(x, y) = R(A(x), B(y)), (X, Y) in X imes Y$ 3. Data Application: By dynamically monitoring and analyzing rice disease data, this dataset provides disease early warnings for agricultural entities, preventing large-scale disease outbreaks and ensuring stable rice production.




