• The Journal of Asian Finance, Economics and Business
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• 제9권4호
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• pp.83-92
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• 2022

Due to the uncertainty in the order of the integrated model, the SARIMA-LSTM model, SARIMA-SVR model, LSTM-SARIMA model, and SVR-SARIMA model are constructed respectively to determine the best-combined model for forecasting the China-Russia trade turnover. Meanwhile, the effect of the order of the combined models on the prediction results is analyzed. Using indicators such as MAPE and RMSE, we compare and evaluate the predictive effects of different models. The results show that the SARIMA-LSTM model combines the SARIMA model's short-term forecasting advantage with the LSTM model's long-term forecasting advantage, which has the highest forecast accuracy of all models and can accurately predict the trend of China-Russia trade turnover in the post-epidemic period. Furthermore, the SARIMA - LSTM model has a higher forecast accuracy than the LSTM-ARIMA model. Nevertheless, the SARIMA-SVR model's forecast accuracy is lower than the SVR-SARIMA model's. As a result, the combined models' order has no bearing on the predicting outcomes for the China-Russia trade turnover time series.

• 한국철도학회지
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• 제4권1호
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• pp.9-15
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• 2001

The railways in Russia is a core of the industrial, trade and technological development. They changed the country for the best affecting all sides of its life. The total length of the railways in Russia is 87,500 km (7％ of the World railway network). They account for about a 25％ of the World freight and 15% of the passenger traffic. In terms of length of electrified railways Russia is a World leader and in terms of total length of tracks it is second after the USA. Annual freight turnover is the third after the USA and China. (omitted)