山核桃病害程度预测模型数据

山核桃病害程度预测,输入为降水量,干球温度,相对湿度,风速,输出为山核桃的病情。该模型帮助解决了关于山核桃病情程度的预测和与气象因素的关系建模的问题。山核桃病害程度与气象因素的关系模型，首先通过查阅大量文献和对接专家经验获取山核桃病害情况及山核桃病害的发病规律。模型通过BP神经网络算法，使用历史测报的气象数据，可以预测未来的山核桃病害程度。该模型通过输入当天的平均温度、风速、干球温度,相对湿度,来输出预测未来的山核桃病害程度。

Pecan Disease Severity Prediction: The input parameters include precipitation, dry-bulb temperature, relative humidity, and wind speed, while the output is the severity of pecan diseases. This model addresses the challenges of pecan disease severity prediction and the modeling of the correlation between pecan diseases and meteorological factors. The model for the relationship between pecan disease severity and meteorological factors was developed by first consulting a large body of scientific literature and incorporating expert experience to obtain information on pecan diseases and their incidence regularities. Utilizing the Backpropagation (BP) neural network algorithm and historically monitored meteorological data, the model can predict the future severity of pecan diseases. Specifically, by inputting the daily average temperature, wind speed, dry-bulb temperature, and relative humidity, the model outputs the predicted future severity of pecan diseases.