A Novel Power-Driven Grey Model with Whale Optimization Algorithm and Its Application in Forecasting the Residential Energy Consumption in China

Table 8

Fitted and predicted results of various grey models in Example B.

Year	Real data	GM(1,1)	Error (%)	ARGM	Error (%)	DGM	Error (%)	NGM	Error (%)	NIGM	Error (%)	FGM(1,1)	Error (%)	SAIGM	Error (%)	GM(1,1,)	Error (%)
2008	320611	320611	0	320611	0	320611	0	320611	0	311679.0155	−2.785925775	320611	0	320611	0	320611	0
2009	336126	349189.7029	3.886549367	344430.113	2.47E + 00	349311.5014	3.922785319	195251.0697	−41.91134582	343554.0921	2.209912975	336126	−6.09E − 09	334656.6702	−0.437136603	302216.2049	−10.08841777
2010	360648	363180.4997	0.70220817	364871.1079	1.17097776	363285.296	0.731265934	324553.7721	−10.00815973	368260.8022	2.110867706	362542.7915	0.525385288	363846.1266	0.886772319	336515.6299	−6.691391627
2011	387043	377731.8583	−2.405712472	382413.0823	−1.196228253	377818.0957	−2.383431369	378605.0893	−2.18009644	387411.2353	0.095140671	384858.2814	−0.564464039	385905.0726	−0.294005419	363964.4755	−5.962780493
2012	402138	392866.2383	−2.305616897	397467.1865	−1.161495191	392932.263	−2.289198485	401199.7052	−0.233326558	402254.9392	0.029079382	402143.1792	0.001287911	402575.3761	0.108762691	386004.0797	−4.012035752
2013	416913	408606.9995	−1.992262303	410386.2597	−1.565492142	408651.0547	−1.981695294	410644.7418	−1.503493099	413760.4517	−0.756164554	414991.5431	−0.46087718	415173.395	−0.417258508	403772.8105	−3.15E + 00
2014	425806	424978.4373	−0.194352063	421473.1004	−1.017575986	424998.6581	−0.189603218	414592.9707	−2.633365728	422678.4964	−0.734490251	424176.7152	−0.382635476	424693.9224	−0.261170013	418169.7514	−1.793363307
2015	429905	442005.8207	2.814766209	430987.5627	0.251814401	442000.2281	2.813465333	416243.4155	−3.177814742	429590.9676	−0.073046936	430405.4018	0.116398218	431888.7395	0.461436707	429905.0001	1.97E − 08
2016	435819	459715.4311	5.483109076	439152.6474	0.764915571	459681.9259	5.475421199	416933.337	−4.333373018	434948.8973	−0.199647723	434274.3904	−0.354415389	437325.9795	0.345781049	439539.3936	0.853655668
2017	448529.1	478134.6031	6.600575768	446159.7284	−0.528253708	478070.9591	6.58638629	417221.7391	−6.980006624	439101.8855	−2.101806668	436274.3346	−2.732211883	441434.99	−1.581638728	447515.8839	−0.225897516
2018	464000	497291.7661	7.174949597	452173.0382	−2.548914172	497195.624	7.154229303	417342.2974	−10.05553935	442320.9107	−4.672217527	436804.2529	−5.861152385	444540.236	−4.193914654	454184.3177	−2.115448779