Wireless Sensor and Actuator Networks for Lighting Energy ...

ŷ k +1
= 2 +
1
S
1+
k
1
S k
[2]
(5.14)
The prediction and corresponding prediction error generated by double
exponential smoothing approach on the same set of daylight data as that used in Figure
5-3 is shown in Figure 5-6, where the blue solid line in (a) is the true daylight data
sampled every ten seconds and the green dashed line is the prediction. Unlike Kalman
and Wiener filtering approaches, which may be started with random initial guesses, the
double exponential soothing method has to be initiated by smoothing over the first few
data points. In this case, the first 24 data points were used for initialization, and the
MSE is 91.9.
Figure 5-6 Prediction performance of double exponential smoothing.
Compare the performance of the above three predictive models (Figure 5-3,
Figure 5-5 and Figure 5-6). Each model can provide a reasonably good prediction.
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