Optimization of the input layer structure for feed-forward NARX neural network
Zongyan Li
Matt Best
2134/22533
https://repository.lboro.ac.uk/articles/journal_contribution/Optimization_of_the_input_layer_structure_for_feed-forward_NARX_neural_network/9226565
This paper presents an optimization method for
reducing the number of input channels and the complexity of the
feed-forward NARX neural network (NN) without compromising the
accuracy of the NN model. By utilizing the correlation analysis
method, the most significant regressors are selected to form the input
layer of the NN structure. An application of vehicle dynamic model
identification is also presented in this paper to demonstrate the
optimization technique and the optimal input layer structure and the
optimal number of neurons for the neural network is investigated.
2016-09-22 12:27:57
Correlation analysis
F-ratio
Levenberg-Marquardt
MSE
NARX
Neural network
Optimisation
Engineering not elsewhere classified