A New Approach to Forecasting Container Throughput of Guangzhou Port with Domain Knowledge

Authors:
Anqiang Huang;Shouyang Wang;Xun Zhang
Affiliations:
School of Economy and Management, Beihang University, Beijing, China;Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China;Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China
Venue:
International Journal of Knowledge and Systems Science
Year:
2013

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Abstract

Although judgmental models are widely applied in practice to alleviate the limitation of statistical models ignoring domain knowledge, they are still suffering from many kinds of biases and inconsistencies inherent in subjective judgments. Moreover, most of the prior studies are often concentrated on making judgmental adjustments to statistical projections and ignore incorporating domain knowledge in other forecasting steps. This paper proposes a framework under which domain knowledge are integrated with the whole forecasting process and a new forecasting method is developed. The new method is applied to forecasting the container throughput of Guangzhou Port, one of the most important ports of China. In order to test the effectiveness of the new method, the authors compare its performance with that of the ARIMAX model. The results show that the new method significantly outperforms the ARIMAX model.