Table 3.

The definitions and formulas of indexes involved in this paper.

Metric	Definition	Equation
MAE	The mean absolute error of N forecasting results	$MAE=\frac{1}{N}{\displaystyle {\displaystyle \sum }_{i=1}^N}\left|F_i-A_i\right|$
MSE	The mean squared error of N forecasting results	$MSE=\frac{1}{n}{\displaystyle {\displaystyle \sum }_{i=1}^n}{\left(F_i-A_i\right)}^2$
RMSE	The square root of average of the error squares	$RMSE=\sqrt{\frac{1}{N}\times {\displaystyle {\displaystyle \sum }_{i=1}^N}{\left(F_i-A_i\right)}^2}$
NMSE	The normalized average of the squares of the errors	$NMSE= \frac{1}{N}{\displaystyle {\displaystyle \sum }_{i=1}^N}\frac{{\left(F_i-A_i\right)}^2}{F_i{A}_i}$
MAPE	The average of N absolute percentage error	$MAPE= \frac{1}{N}{\displaystyle {\displaystyle \sum }_{i=1}^N}\left|\frac{A_i-F_i}{A_i}\right|\times 100\%$
IA	The index of agreement of forecasting results	$IA= 1-{\displaystyle {\displaystyle \sum }_{i=1}^N}{\left(F_i-A_i\right)}^2/{\displaystyle {\displaystyle \sum }_{i=1}^N}{\left(\left|F_i-Ā\right|+\left|A_i+Ā\right|\right)}^2$
R	The correlation coefficient	$R= \frac{\left(A_i-Ā\right)\left(F_i-\overline{F}\right)}{{\sigma }_F{\sigma }_A}$
AE	The absolute error of forecasting results	$AE= \left|F_i-A_i\right|$
FB	The fractional bias of N forecasting results	$FB= 2\left(Ā-\overline{F}\right)/\left(Ā+\overline{F}\right)$
IOA	The index of agreement	$IOA=1-\frac{{{\displaystyle \sum }}_{i=1}^N{\left(F_i-A_i\right)}^2}{{{\displaystyle \sum }}_{i=1}^N{\left(\left|F_i-\overline{F}\right|+\left|A_i+Ā\right|\right)}^2}$