The achieved running time (8 seconds) for a complete radio coverage can be considered as a reasonably quick propagation prediction, fulfilling thus the requirements in terms of speed for wireless network planning in the presence of randomly distributed femtocells.
The modeling efforts showed that the optimal network architecture was 23-34-1 and thet the best WQI predictions were associated with the quick propagation (QP) training algorithm; a learning rate of 0.06; and a QP coefficient of 1.75.
According to the previous report, the quick propagation of PEDOT chains happens in a limited time under rapid initiated condition, and a lot of initial nanofibrous oligomers can be formed in the early stage[18].
The network was trained by Quick propagation (QP) and the other three algorithms as a model.
Artificial neural network based on Quick propagation algorithm with topology 4-10-1 4-10-1 4-10-1 performance in this study.
In order to do solar radiation forecasting, quick propagation algorithms Artificial Neural Network (ANN) models were developed.
Moreover, the dissemination of multi-hop messages takes place in two phases: first one for quick propagation of message and second one for increasing the reception reliability.
Figure 1 The performance of the network at different hidden neurons using, Incremental backpropagation algorithm (IBP), Batch backpropagation algorithm (BBP) and Quick propagation algorithm (QP).
The results show that NN with quick propagation algorithm gives superior performance for predicting and evaluating the noise of washing machine systems.
