Xiukang Wang

TL;DR: Wang et al. as discussed by the authors proposed two machine learning algorithms, i.e., Support Vector Machine (SVM) and a novel simple tree-based ensemble method named Extreme Gradient Boosting (XGBoost), for accurate prediction of daily H using limited meteorological data.

TL;DR: In this paper, the authors evaluated the potential of tree-based assemble algorithms (i.e., random forest, M5 model tree, gradient boosting decision tree and extreme gradient boosting) for estimating daily evapotranspiration (ET0) with limited meteorological data using a K-fold cross-validation method.

TL;DR: In this article, the performance of 12 empirical model forms and 12 machine learning algorithms for estimating daily solar radiation (Rs) were further evaluated in different climatic zones of China as a case study, i.e., the temperate continental zone (TCZ), temperate monsoon zone (TMZ), mountain plateau zone (MPZ) and (sub)tropical monsoon zones (SMZ).

TL;DR: In this paper, the effects of mulching and nitrogen (N) fertilizer on the soil environment and crop yield to inform food security are discussed. But, the use of mulch in agriculture provides many benefits to the soil by reducing evaporation, improving temperatures, adjusting the microbial biomass, maintaining the soil organic carbon balance, increasing nutrient cycling, promoting soil enzyme activity, enhancing soil aggregate stability and suppressing weed infestation.

TL;DR: In this article, the authors investigated the coupling effects of different amounts of water and fertilizers on seed cotton yield, water and fertilizer use efficiency as well as economic benefits in northern Xinjiang of Northwest China.