TELKOMNIKA Telecommunication, Computing, Electronics and Control
Application and evaluation of the neural network in gearbox

TELKOMNIKA Telecommunication, Computing, Electronics and Control
Application and evaluation of the neural network in gearbox

Artificial neural network, Automatic transmission gearbox, Back propagation neural networks, Neural network classifiers, Pattern recognition

We developed old designed of a Back-Propagation neural network (BPNN), which it was designed by other researchers, and we made modification in their structure. The 1st velocity ratio was discriminated by lowest speed, and highest twist. The 6th velocity ratio was discriminated by highest speed, and lowest twist. The aim of this paper is to design neural structure get best performance to control an electrical automotive transportation six-speed gearbox of the vehicle. We focus on the evaluation of the BPNN to select the suitable number of layers and neurons. Experimentally, the structure of the proposed BPNN are constructed from four layers: eight input nodes in the first layer that received data in binary number, 45 neurons in 1st hidden-layer, 25 neurons in 2nd hidden-layer, and 6 neurons in the fourth layer. The MSE and number of Epochs are the main factors used for the evaluation of the proposed structure, and compared with the other structures which was designed by other researchers. Experimentally, we discovered that the best value of Epoch and MSE was chosen when the BPNN consisted of two hidden-layers, 45, and 25 neurons in the 1st and 2 nd hidden-layer respectively. The implementation was applied using MATLAB software.

Dheyaa Shaheed Al-Azzawi

DOI: 10.12928/TELKOMNIKA.v18i1.13760

Universitas Ahmad Dahlan

February 2020

Sri Wahyuni

ISSN: 1693-6930

http://journal.uad.ac.id/index.php/TELKOMNIKA

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TELKOMNIKA Telecommunication, Computing, Electronics and Control