Prediction of Ship Traffic Flow and Congestion Based on Extreme Learning Machine with Whale Optimization Algorithm and Fuzzy c-Means Clustering

Table 3

Comparison of prediction of ship traffic density between proposed and comparison methods.

Time slice	15 min			30 min			1 h
Method	MAE	RMSE	MAPE (%)	MAE	RMSE	MAPE (%)	MAE	RMSE	MAPE (%)
WOA-ELM	3.427 1	0.563 6	7.0071	0.529 8	0.656 7	7.156 7	0.617 9	0.786 8	7.444 3
EMD-WOA-ELM	0.263 1	0.343 9	4.446 0	0.342 1	0.408 7	4.468 6	0.400 6	0.473 1	4.518 8
VMD-WOA-ELM	0.126 5	0.158 9	2.132 2	0.196 2	0.248 4	2.744 1	0.174 5	0.234 0	2.002 3
ELM	0.447 3	0.585 4	7.460 1	0.532 7	0.677 1	7.321 7	0.705 9	0.9109	8.054 8
BP	0.4346	0.586 6	7.308 5	0.557 1	0.683 5	8.071 8	0.687 6	0.832 2	7.861 6