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The concern of employing erroneous data for training is twofold.
Data for training SAN was obtained using a model whose parameters were calculated from experimental data.
The developed ANN model used input/output experimental data for training and classification.
However, the simulated data for training robotic tasks worked much better than they expected.
The input data for training this neural network were provided by the Taguchi method.
We have used real hardware data for training the ANFIS network.
This allows us to use a large amount of data for training the system.
Therefore, these parameters were mainly used as input data for training and testing the ANN.
Moreover, some researchers used more than five years of meteorological data for training the neural network.
Hu and Loizou [29] split their data for training and testing.
We used about 70% of this data for training the deep neural architectures.
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