Application of Support Vector Machine Based on Time Series For Soil Moisture and Nitratenitrogen Content Prediction

Support Vector Machine based on Time Series (SVM-TS) was applied to predict soil moisture and nitrate nitrogen (NO3­ ­N) content. For the prediction of soil moisture, the statistical result (t­test) indicate that there is no obvious difference between predicted and observed values in 0­20cm and 20­60cm soil layers, and that SVM­TS is capable for soil moisture prediction. For the prediction of NO3­N content, there is no obvious difference between predicted and observed values in 0­30cm soil layer, although the difference in 30­60cm soil layer is obviously, compared to the variability of observed value, a large predicted error is acceptable, SVM­TS is applicable for NO3­N content prediction.

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