The air velocity root mean square
, in the exit air terminal devices, is higher in test II than in test I, while in the turbulence intensity the opposite is verified.
The Least mean square
algorithm changes the filter tap weight so that the error e(k) is minimized in the mean square
The stochastic cocycle [PHI]: [R.sub.+] X [OMEGA] [right arrow] B(X) is said to be exponentially stable in mean square
if there exist two positive constants N, v such that
Using our main theorem from below one can establish the same mean square
convergence rate [[gamma].sub.2] = 0.5 for systems (1.1) satisfying the more general conditions (1.2)-(1.5), even for dissipative systems of SDEs on infinite intervals [0,+[infinity]].
Then, the models were fitted according to the number of input variables (3 and 4 inputs), number of layers (1, 2 and 3 layers) and transfer functions (Polynomial, Sigmoid, RBF and Tangent); in this case, the best fitted model was considered as that with lowest mean square
error (MSE) of the predicted values.
Results Train Test Overall MSE 79671.423 253835.159 114918.846 RMSE 282.261 503.821 338.997 NRMSE 0.045 40.908 18.520 MAE 196.618 352.406 228.146 MAPE 47.503 136.486 65.512 MSE: mean square
error; RMSE: root mean square
error; NRMSE: normalized root mean square
error; MAE: mean absolute error; MAPE: mean absolute percentage error
The presented artificial neural network was trained using the Levenberg-Marquardt algorithm and the mean square
error was used as a performance function .
In each band, the high protruding frequency is extracted as the feature, and root mean square
(RMS) value for these protruding frequencies are used for fault detection.
error, normalized cross-correlation, and structural similarity were used as evaluation indexes to verify the superiority of this method.
Necessary and sufficient conditions for the system to achieve mean square
bipartite consensus based on event-triggered protocols are given.