农业水质pH预测模型数据
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可以用于水质pH预测,输入溶解氧浊度,电导率,氨氮.总磷,重金属,温度,有机碳总量,细菌计数。输出为水质pH。该模型帮助解决了水质pH和水质理化参数以及水质状况关系建模的问题。使用理化实验以及温度计等采集水体水质等数据,将采集的数据使用传统算法,多元线性回归算法等方式以预测水质pH。该模型通过输入溶解氧浊度,电导率,氨氮.总磷,重金属,温度,有机碳总量,细菌计数,来输出预测的水质pH。
This dataset is designed for water quality pH prediction, with input parameters including dissolved oxygen, turbidity, electrical conductivity, ammonia nitrogen, total phosphorus, heavy metals, temperature, total organic carbon, and bacterial count, and the output target is water quality pH. This model solves the problem of modeling the relationship between water quality pH, physical and chemical water quality parameters and water quality status. Water quality data were collected via physical and chemical experiments, thermometers and other measuring instruments, and traditional algorithms such as multiple linear regression were adopted to predict water quality pH based on the collected data. Specifically, this model outputs the predicted water quality pH by inputting the above-mentioned water quality physical and chemical indicators.




