China ; Forecast ; Model ; Neural network ; Space time ; Spatial weighting ; Statistics ; Temperature ; Time series
The article presents a hybrid framework combining machine learning and statistical methods to address a modelisation of the nonlinearities and nonstationarities of environmental space-time series. A four-stage procedure is proposed and it is applied