Fig. 2. Time series comparison between observed rice yield and predicted rice yield in South Korea from 1991 to 2005.
Fig. 1. Performance of Random forest in national mean rice yield of South Korea with train data (1991-2005).
Fig. 3. Variable importance plot from Random Forest in rice prediction with train data (1991-2005). Max temp: Monthly mean temperature, Mean temp: Monthly mean temperature, Min temp: Monthly minimum temperature, Mean sh: Monthly mean sunshine hour. %IncMSE: mean square error, the higher %IncMSE is more important.
Fig. 4. Partial dependence plots for the top ranked predictor variable, year, from variable importance measures of Random Forests models with train data (1991-2005).
Fig. 5. Observed yield and 10-year moving average, 5-year moving average and 3-year moving average of National mean yield in South Korea.
Fig. 6. Variable importance plot from Random Forest in yield fluctuation prediction with detrended train data(1991-2005). Max temp: Monthly mean temperature, Mean temp: Monthly mean temperature, Min temp: Monthly minimum temperature, Mean sh : Monthly mean sunshine hour. %IncMSE: mean square error, the higher %IncMSE is more important.
Fig. 7. Time series comparison between observed rice yield and predicted rice yield in South Korea with train data (1991-2005) and test data (2006-2015).
Fig. 8. Performance of Random forest in national mean rice yield of South Korea with test year (2006-2015).
Fig. 9. Variable importance comparison between train set (1991-2005) and test set (2006-2016).
Table 1. Comparison of model predictive performance when trend is removed by using the moving average
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