English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

International audienceHow 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

Interpolation Method of Soil Moisture Data Based on BMA