Artificial Neural Network Model Development for the Analysis of Maximum Pressure of Hole Entry Journal Bearing Using SciLab

Artificial neural network (ANN) is used as an advanced technology for the prediction of the behaviour of mechanical systems. ANN research is focused on developing computational approaches to analyse the complex and time-consuming problems. The present paper shows the ANN predictions for maximum pressure of hole entry hybrid journal bearing for different values of non-dimensional load and speed parameters. The present ANN model is trained and tested in SciLab using literature data and found capable to show more accurate results. Feed forward back propagation algorithm is used in this ANN model to minimize the error and to update the weights. Sigmoid activation function is used for hidden layer neurons and output layer neuron. ANN is found as best predictor for journal bearing analysis.