CAJ | 학술논문

以广东省增城市为研究对象，采集了全市内200个土壤样点，利用 BP神经网络插值方法对研究区土壤的氮和磷进行空间插值预测，将插值结果与土壤样点实测值进行对比，得到预测数据的误差均方根。结果表明， BP神经网络的插值精度比克里格高，在样点较少的情况下，BP神经网络的插值结果克服了克里格插值方法的平滑效应。 BP神经网络对插值的样本数据的分布类型没有要求，比传统插值方法有更强的泛化能力，是一种可替代的插值方法。
이광동성증성시위연구대상，채집료전시내200개토양양점，이용 BP신경망락삽치방법대연구구토양적담화린진행공간삽치예측，장삽치결과여토양양점실측치진행대비，득도예측수거적오차균방근。결과표명， BP신경망락적삽치정도비극리격고，재양점교소적정황하，BP신경망락적삽치결과극복료극리격삽치방법적평활효응。 BP신경망락대삽치적양본수거적분포류형몰유요구，비전통삽치방법유경강적범화능력，시일충가체대적삽치방법。
With Zengcheng City, Guangdong Province, as the object of study, 200 soil sampling points were col ected for the spatial interpolation prediction of soil properties by using Kriging method and BP neural network method. After comparing the interpolation results with the measured values, the root mean square error of the prediction data was obtained. The results showed that the interpolation accuracy of BP neural network was higher than that of Kriging method under the same cir-cumstances, and there was no smoothness in using BP neural network method when there were few sample points. In addition, with no requirement on the distri-bution of sample data, BP neural network method had stronger generalization ability than traditional interpolation method, which was an alternative interpolation method.