Saline-alkali Soil Philip Infiltration Model Parameters Prediction Based on Support Vector Machine
With the test data of soil infiltration in field native saline wasteland as sample,using the regression algorithm of the support vector machine,the prediction model was established among the soil moisture content, bulk density, organic matter content, clay content, silt content,soluble,pH and the Philip infiltration parameters under the condition of saline.The prediction results showed that the average relative error of the sorptivity was 4.05%,the steady infiltration rate was 5.49%,and the ninety minutes cumulative infiltration amount was 4. 28%under the training samples; the average relative error of the sorptivity, the steady infiltration rate and the ninety minutes cumulative infiltration amount were 4.22%,3.58%and 4.48%,respectively,under the testing samples.It could be seen that both the training samples and testing samples,the predictive values of the two infiltration parameters were well-coincident with the actual values and the accuracy of the established forecast was high.It shows that the prediction model of the Philip infiltration parameters based on the SVM is feasible under the condition of saline and it can provide technical support of infiltration parameters for improving the saline soil.
support vector machinesaline-alkali soilsoil infiltration parametersPhilip infiltration modelsoil physical and chemical parameters