Forecasting with trees

The prevalence of approaches based on gradient boosted trees among the top contestants in the M5 competition is potentially the most eye-catching result. Tree-based methods out-shone other solutions, in particular deep learning-based solutions. The winners in both tracks of the M5 competition heavily relied on them. This prevalence is even more remarkable given the dominance of other methods in the literature and the M4 competition. This article tries to explain why tree-based methods were so widely used in the M5 competition. We see possibilities for future improvements of tree-based models and then distill some learnings for other approaches, including but not limited to neural networks.     

数控机床的维护与故障管理

我国的数控机床发展很快,数控机床的产量越来越大。数控机床的发展一方面要提高其质量和数量,另一方面还要充分认识到数控机床应用和维修的重要性,认识到正确的使用和良好的维护、维修措施,是机床长期可靠运行的重要保障。     

MARKET‐DEMAND BOOSTING AND PRIVATIZATION IN A MIXED DUOPOLY

This study incorporates demand‐boosting strategies into a mixed duopoly model in order to consider the endogenous determination of market demand. The results indicate equilibrium characteristics that differ from those found under an exogenous demand setting. As consumers become more sensitive to the demand‐boosting strategies of firms, the government must choose a lower level of privatization. This suggests that the responsiveness of consumer demand to the demand‐boosting strategies of firms constitutes a limiting factor for privatization.