Time Series Prediction of Electricity Demand Using Adaptive Neuro-Fuzzy Inference Systems

Table 1

Root mean square values for each epoch considering all the scenarios.

Epoch number	ANFIS Scenario 1		ANFIS Scenario 2		ANFIS Scenario 3		SVR		LS-SVR		ARIMA
	RMSE values for training	RMSE values for checking	RMSE values for training	RMSE values for checking	RMSE values for training	RMSE values for checking	RMSE values for training	RMSE values for checking	RMSE values for training	RMSE values for checking	RMSE values for training	RMSE values for checking
1	57.2167	112.558	46.4971	103.663	34.3291	6537.14	66.4006	170.887	65.6463	102.701	70.3049	148.376
2	57.2117	112.631	46.4912	102.59	34.3163	6478.66	65.3564	170.896	65.4131	109.136	70.3043	148.409
3	57.2067	112.705	46.4853	101.52	34.3409	6517.89	64.8084	170.909	65.2659	116.989	70.3038	148.432
4	57.2017	112.779	46.4795	105.151	34.3347	6467.86	64.6973	170.922	65.098	117.018	70.3032	148.489
5	57.1968	112.853	46.4736	105.868	34.3302	6480.19	64.7074	170.934	64.6657	120.457	70.3027	148.513
6	57.1919	113.928	46.4677	111.795	34.3323	6557.93	64.5821	170.948	64.2683	121.738	70.3022	148.493
7	57.1864	113.01	46.4613	117.977	34.3842	6594.07	64.6992	170.96	63.6042	119.821	70.3016	148.513
8	57.181	113.093	46.4549	119.558	34.3316	6551.48	64.5605	170.977	63.1597	122.85	70.301	148.559
9	57.1751	113.176	46.4485	131.342	34.3406	6524.04	64.5173	170.992	63.0961	123.919	70.3004	148.596
10	57.1703	113.259	46.4421	132.514	34.3338	6552.78	64.4919	171.008	63.2443	84.4919	70.2998	148.62
Average	57.19383	112.9992	46.47012	113.1978	34.33737	6526.204	64.88211	170.9433	64.34616	113.91209	70.30239	148.5