## 3 Materials and Methods
### Data Description  
In this study, annual container throughput from 2004 to 2020 was obtained from the official websites of the world's top 20 container ports. For each port, there are 17 observations. The statistical description of the data is shown in Table 4 and the time plots of the  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Learning Method** & **Searching Parameter** & **Searching Range** \\ \hline NM & No applicable & No applicable \\ MA & Size of moving window & 2 \\ AR & Autoregressive order & 1 \\ ARIMA & No applicable & No applicable \\ MLP & Size of hidden layer & \(8,16,32,64,100,128,256,512\) \\ GRU & Size of hidden layer & \(8,16,32,64,100,128,256,512\) \\ LSTM & Size of hidden layer & \(8,16,32,64,100,128,256,512\) \\ CNN & Number of filters & \(8,16,32,64,100,128,256,512\) \\ Transformer & Number of encoder/decoder layer & \(1,2,3,4\) \\ \hline \hline \end{tabular}
\end{table}
Table 3: Searching range of each method.  
Figure 7: Process of comparison.  
container throughput of the world's top 20 container ports are shown in Figure 8. It can be seen from the figure that the annual container throughput of most ports shows a trend of gradual increase, such as Antwerp, Guangzhou, Qingdao, Ningbo, Busan, etc. However, some, such as Hong Kong, showed a downward trend. Some ports, such as Dalian and Dubai, showed a trend of increasing first and then decreasing.  
Before the experiment, the obtained data should be divided into the training set and testing set. The training set is used to tune the parameters of the model, so that the forecasting results of the model will be closer to the real value. The testing set is used to test the accuracy of the trained model on the new data. According to [PERSON] et al. (2018), 80/20 is a common ratio of training and testing sets [55]. Therefore, the training set includes 13 observations (76%) from 2004 to 2016. The testing set includes four observations (24%) from 2017 to 2020.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Port** & **Mean** & **SD** & **Max** & **Min** \\ \hline Ningbo & 1617.4 & 786.05 & 2872.00 & 400.50 \\ Shanghai & 3167.23 & 865.51 & 4350 & 1455.4 \\ Singapore & 3031.71 & 467.16 & 3720 & 2132.9 \\ Shenzhen & 2222.69 & 374.38 & 2774 & 1365.5 \\ Hong Kong & 2187.56 & 188.18 & 2449.4 & 1830 \\ Busan & 1664.03 & 384.83 & 2199 & 1149.2 \\ Guangzhou & 1442.5 & 612.93 & 2323 & 330 \\ Qingdao & 1387.51 & 510.66 & 2200 & 514 \\ Dubai & 1257.11 & 271.97 & 1573 & 642.9 \\ Tianjin & 1154.67 & 435.45 & 1835 & 381.6 \\ Rotterdam & 1167.74 & 193.12 & 1482 & 829.2 \\ Kelang & 984.91 & 288.37 & 1373 & 524.4 \\ Kaohsiung & 982.51 & 54.38 & 1059.3 & 858.1 \\ Dalian & 686.26 & 289.59 & 1021 & 220 \\ Hamburg & 871.68 & 80.18 & 973.7 & 700.3 \\ Antwerp & 891.72 & 166.85 & 1204 & 606.3 \\ Xiamen & 719.56 & 281.92 & 1141 & 287.2 \\ Tanjung & 715.77 & 184.87 & 985 & 402 \\ Los Angeles & 823.28 & 77.63 & 946 & 710.3 \\ Long Beach & 682.15 & 82.03 & 811 & 506.7 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Summary statistics of top 20 container ports’ throughput.  
Figure 8: The container throughput of the world’s top 20 container ports from 2004 to 2020.