Spatial Interpolation of Soil Nutrients Based on BP Neural Network |
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Authors: | Qing LI Jiachang CHENG Yueming HU |
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Affiliation: | 1. Guangzhou Yuetu Information Technology Co., Ltd., Guangzhou 510640, China; 2. College of Informatics, South China Agricultural University, Guangzhou 510642, China; 3. Key Laboratory of Guangdong Province Land Use and Remediation, Guangzhou 510642, China |
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Abstract: | 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. |
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Keywords: | BP neural network Soil nutrients Spatial prediction Kriging |
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