According to the season effect of air quality forecasting and the physical meaning of granules, the experiments tested different values of the window width winSize={3, 7, 15, 30, 90}; Figure 4 presented the MSEtest of AQI prediction on both composition models and the direct models.
The collision probability performance is also demonstrated for different values of initial contention window size, CW min = 16, CW min = 24, and CW min = 32.
For two different values of the observation window sizes, namely N=10 and N=1000, we plot in Figs. 8 and 9, respectively, the NRMSE for the channel power estimator using both versions I and II as a function of the true SNR.
The inversion analysis in Case 1 was repeated for different values of the first-time-window triggering velocity.
Open image in new window Fig. 8 Membership function for λ, a and b Open image in new window Fig. 9 A t) vs t for different values of λ Open image in new window Fig. 10 A t)vs t for different values of a Open image in new window Fig. 11 A t) vs t for different values of b.
Open image in new window Fig. 6 a, b Velocity profile and temperature profile for different values of l Open image in new window Fig. 7 a and b Temperature profiles for different values of Ec and γ, respectively.
Open image in new window Fig. 1 Comparison of objective function under λ = 0.8 and different values of γ Open image in new window Fig. 2 Comparison of objective function under γ = 0.8 and different values of λ.
Figure 4 Predicted normalized conductance change as a function of window length for different values of parasitic resistance.
Figure 5A presents the plot of the average noise, Ω(r), for ρ0 technical replicates, defined as 15 as a function of, the inverse of the square root of window size, for different values of α : for all values of α, Ω(r) goes as, as it should be expected for a random noise.
This search may be long enough to cause ISI. Figure 2 shows the duration of Rake operational window for different values of in different channel profiles.
