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Abstract. On the background of new economic normality, the regional cooperation between China and Russia has got rapidly developed. Russia is the important country of the "one belt and one road" line, and to establish free trade area is the main propulsive forms of "one belt and one road". The paper analyzes the trade effect of setting up Sino-Russian Free Trade Area (FTA). It includes trade create effect and trade transfer effect between China and Russia in partial equilibrium analysis, SinoRussia trade intensity index calculation, for the purpose of setting up Sino-Russia FTA to governments. It can get the following conclusions: in terms of trade intensity index, Russia is more dependent on the Chinese market; Russia achieves more trade creation effect from Sino-Russian Free Trade Area than that China obtain; the compre hensive trade effect of Sino-Russian FTA is positive.

In order to better study the chosen path of the consumption model of public green energy and more accurately predict consumers’ green energy consumer behavior, we take new energy vehicles as an example to explore the driving mechanism and internal mechanism of the public green energy consumption model from the perspective of motivation. We propose an ensemble learning model based on a stacking strategy. The model uses XGBoost, random forest and gradient lifting decision trees as primary learners to transform features, and uses logistic regression as a meta-learner to predict users’ consumer behavior. The experimental results show that this feature engineering method can significantly improve the accuracy rate in multiple model algorithms, and the prediction effect of the ensemble learning model is better than that of a single model, with the accuracy rate of 82.81%. In conclusion, the ensemble learning model based on a stacking strategy can effectively predict the public’s consumer behavior. This provides a theoretical basis and policy recommendations for promoting green energy products represented by new energy vehicles, thereby improving the practical path for proposing green energy consumption.