Univariate Time Series Analysis of Short-Term Forecasting Horizons Using Artificial Neural Networks: The Case of Public Ambulance Emergency Preparedness

Table 6

Paired sample -test results: actual versus FFNN forecast of 2018 demand.

		Mean	s.d.	S.E. mean	-value	value	95% C.I.
Actual	12	1506.92	94.54	27.29	-0.71	0.493	(-177.67, 60.33)
FFNN	12	1535.58	127.78	36.89
Difference	12	-28.67	140.07	40.44