[1]WANG Tongtong,ZHAI Junhai,HE Huan,et al.Applicability of BP Neural Network Model and SVM Model to Predicting Soil Moisture Under incorporation of Biochar into Soils[J].Research of Soil and Water Conservation,2017,24(03):86-91.
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Applicability of BP Neural Network Model and SVM Model to Predicting Soil Moisture Under incorporation of Biochar into Soils
Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume:
24
Number of periods:
2017 03
Page number:
86-91
Column:
Public date:
2017-06-28
- Title:
- Applicability of BP Neural Network Model and SVM Model to Predicting Soil Moisture Under incorporation of Biochar into Soils
- Keywords:
- soil moisture; biochar; prediction model; SVM model; BP neural network model
- CLC:
- S152.7
- DOI:
- -
- Abstract:
- As a soil amendment, biochar has a good effect on the soil moisture in the semi-arid area. In order to know the effect of adding biochar on soil water content prediction model, a district positioning experiment was carried out in semi-arid Guyuan ecology research station on the Loess Plateau. In the experiment, different kinds and amounts of biochar were added to soil and the soil water contents were monitored regularly. In consideration of soil water nonlinear characteristic and random effect of adding biochar, BP Neural Network model and SVM (Support Vector Machine) model were selected to build water content prediction model for biochar-added soil and the applicability of the two models were finally evaluated according to the measured data and predicted data by using RMSE, MRE, MAE and R2 to assess the precision. The results showed that the average relative error value of BP Neural Network model was 3.78% and the max relative error value was 13.14%, while the average relative error value of SVM model was 0.56% and the max relative error value was 2.42%, respectively. The RMSE, MRE, MAE value of SVM model(0.34~0.17, 0.07 and 0.56~1.27, respectively) were less than BP Neural Network model(1.04~1.16, 0.47~0.68 and 3.78~4.57 respectively), and the R2 value of SVM model (0.96~0.99) were greater than BP Neural Network model(0.56~0.64), respectively. BP Neural Network model and SVM model both performed well in predicting soil water content and the prediction results of SVM model were more steady and precise. So the SVM model is the appropriate model to predict water content in biochar-added soil. The reuslt can provide theoretical evidence for prediction and management of moisture in the biochar-added soil in the semi-arid area.
- References:
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1900-01-01