土壤电导率预测模型数据

可以用于土壤电导率预测,输入为土壤样本的光谱400nm吸光度，400.5nm吸光度，401nm吸光度，401.5nm吸光度，输出为土壤电导率预测。该模型帮助解决了土壤电导率和土壤光谱吸光度关系建模的问题使用光谱仪器采集土壤光谱数据，将采集的土壤光谱数据使用传统算法，多元线性回归算法等方式以预测土壤电导率。该模型通过输入土壤光谱400nm吸光度，400.5nm吸光度，401nm吸光度，401.5nm吸光度数据，来输出预测的土壤电导率。

This dataset is intended for soil electrical conductivity prediction. The inputs are the absorbance values of soil samples at 400nm, 400.5nm, 401nm, and 401.5nm wavelengths, and the output is the predicted soil electrical conductivity.

This model addresses the challenge of modeling the relationship between soil electrical conductivity and soil spectral absorbance. Soil spectral data is collected using spectrometers, and traditional algorithms such as multiple linear regression are applied to the collected spectral data to predict soil electrical conductivity.

Specifically, this model takes the absorbance data at 400nm, 400.5nm, 401nm, and 401.5nm of soil spectra as input to output the predicted soil electrical conductivity.