A GIS-Based Spatial-Temporal Autoregressive Model for Forecasting Marine Traffic Volume of a Shipping Network

Table 6

Forecasting accuracy of marine traffic volume for the spatial-temporal model and STL model

Port name	R		RMSE		MAPE
	STARMA	STL	STARMA	STL	STARMA	STL
Tainan	0.7459	0.6444	71.7818	56.2860	7.7058	5.9089
Balikpapan	0.2879	−0.1428	31.5497	7.7862	60.5876	13.5260
Bangkok	0.9751	0.3573	172.3342	108.7648	31.2253	20.1060
Zhangzhou	0.9942	0.9629	20.3072	114.7340	2.5310	13.4685
Manila	0.9377	0.3327	148.2501	228.3151	62.0349	54.8789
Haiphong	0.9506	0.5281	21.2210	227.1680	16.9982	205.8779
Kuching	0.9723	0.4867	2.2821	4.2561	14.1942	36.2714
Zhanjiang	0.9559	0.8282	55.5359	86.1244	12.4189	17.2552
Lungsod ng Cebu	0.9572	0.7828	61.8685	33.1485	28.4573	13.8344
Samarinda	0.9441	0.5758	25.3620	26.4804	15.0513	14.8198
Mean	0.8827	0.4469	40.7082	46.3403	44.4811	55.3729