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Interpolation Method of Soil Moisture Data Based on BMA

Abstract : How to consider both the spatial distribution and the time series characters of the soil moisture data, which have an effect on the result of interpolation, is the key to improve the soil moisture data interpolation result. This paper proposes a new interpolation method : the BMA-I (BMA-Interpolation), which contains kriging method, and BMA(Bayse Model Average) method. Spatial forecasting model uses synergetic kring method. Time series forecasting model uses LS-SVM algorithm. The model average uses BMA method. Taking the project of Shandong Bohai granary as an example, through comparing with kriging method, the proposed approach can improve the problems existing in the kriging method effectively, and can give a reliable forecast uncertainty interval, the simulation results more accurate and reasonable.
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Wan Shu-Jing, Zhang Cheng-Ming, Liu Ji-Ping, Yu Ting, Ma Jing. Interpolation Method of Soil Moisture Data Based on BMA. 8th International Conference on Computer and Computing Technologies in Agriculture (CCTA), Sep 2014, Beijing, China. pp.480-488, ⟨10.1007/978-3-319-19620-6_54⟩. ⟨hal-01420263⟩



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