Simplified-Boost Reinforced Model-Based Complex Wind Signal Forecasting

Table 3

Multistep forecasting performance of dataset A.

Dataset A	RMSE (m/s)			MAE (m/s)			MAPE (%)
Model	1 step	3 steps	5 steps	1 step	3 steps	5 steps	1 step	3 steps	5 steps
DT	1.103	1.370	1.623	0.829	1.128	1.384	8.435	12.318	15.935
RF	0.904	1.307	1.604	0.684	1.079	1.282	7.210	11.770	14.423
BPNN	1.158	1.370	1.719	0.930	1.103	1.398	8.728	11.659	15.114
RNN	1.081	1.561	1.695	0.866	1.187	1.342	8.479	12.938	14.621
GRU	1.050	1.749	1.906	0.807	1.366	1.531	8.341	15.544	18.497
LSTM	0.955	1.597	1.793	0.755	1.272	1.444	7.931	14.556	16.377
Proposed	0.766	1.055	1.092	0.585	0.776	0.817	6.089	8.112	8.564
Dataset A	SMAPE (%)			R			MASE
Model	1 step	3 steps	5 steps	1 step	3 steps	5 steps	1 step	3 steps	5 steps
DT	8.506	12.385	14.882	0.966	0.946	0.921	1.175	0.794	0.852
RF	7.386	11.682	13.897	0.977	0.950	0.924	1.022	0.762	0.746
BPNN	9.351	11.631	14.755	0.974	0.945	0.912	1.337	0.759	0.823
RNN	8.867	13.610	14.418	0.968	0.934	0.915	1.241	0.835	0.816
GRU	8.964	16.202	17.159	0.971	0.915	0.894	1.181	0.980	0.966
LSTM	8.109	14.464	15.430	0.974	0.925	0.904	1.107	0.911	0.898
Proposed	6.237	8.264	8.564	0.983	0.968	0.965	0.879	0.549	0.502