农业降雨量预测模型数据
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可以用于农业地下水降雨量预测,输入为农业中地下水的灌溉用水,地下水地下水位,化学需氧量,硝酸盐,磷酸盐,土壤湿度,土壤类型,肥料用量。输出为降雨量。该模型帮助解决了降雨量和农业气候以及地下水理化指标的关系建模的问题。使用理化实验以及温度计等采集地下水理化指标以及气候因素,将采集的地下水理化指标以及气候数据使用传统算法,多元线性回归算法等方式以预测降雨量。该模型通过输入地下水的灌溉用水,地下水位,化学需氧量,硝酸盐,磷酸盐,土壤湿度,土壤类型,肥料用量,来输出预测的降雨量。
This dataset is applicable to agricultural groundwater-related rainfall prediction. Its input variables include agricultural groundwater irrigation water amount, groundwater level, chemical oxygen demand (COD), nitrate, phosphate, soil moisture, soil type and fertilizer application dosage, while the output is rainfall. This model addresses the problem of modeling the correlations between rainfall, agro-climatic factors and groundwater physicochemical indices. Groundwater physicochemical indices and climatic factors are collected via physicochemical experiments, thermometers and other measuring instruments, and the collected datasets are used for rainfall prediction through traditional algorithms such as multiple linear regression. Specifically, this model takes the aforementioned input parameters to generate the predicted rainfall.




