Artificial neural networks have emerged as a good candidate to mathematical wear models, due to their capabilities of handling nonlinear behavior, learning from experimental data and generalization. In the present work the potential of using neural networks for the prediction of abrasive wear properties of unfilled and graphite filled carbon fabric reinforced epoxy composite under various testi...

In most countries, the main step in the process of power system restoration, following a complete/partial blackout, is energization of primary restorative transmission lines. Artificial neural network (ANN) is employed for performing a nonlinear input–output mapping in this work, in order to estimate the temporary overvoltages (TOVs) due to transmission lines energization. In the proposed metho...

This paper presents the development of an artificial neural network (ANN) model based on the multi-layer perceptron (MLP) for analyzing internet traffic data over IP networks. We applied the ANN to analyze a time series of measured data for network response evaluation. For this reason, we used the input and output data of an internet traffic over IP networks to identify the ANN model, and we st...

In this paper, we purpose a diagnostic procedure to identify the macular disease from pattern electroretionography (PERG) signals using artificial neural networks (ANN) methods. Multilayer feed forward ANN trained with a Levenberg Marquart backpropagation algorithm was implemented. The designed classification structure has about 96% sensitivity, 100% specifity and correct classification is calc...

A simple method to detect gestures revealing muscle and joint pain is described in this paper. Kinect Sensor is used for data acquisition. This sensor only processes twenty joint coordinates in three dimensional space for feature extraction. The recognition part is achieved using a neural network optimized by Levenberg-Marquardt learning rule. A high recognition rate of 91.9% is achieved using ...

Financial forecasting is an example of signal processing problems. A number of ways to train/learn the network are available. We have used Levenberg-Marquardt algorithm for error back-propagation for weight adjustment. Pre-processing of data has reduced much of the variation at large scale to small scale, reducing the variation of training data. Keywords— Gradient descent method, jacobian matri...

Accomplishment of optimization technique on Object Oriented design component is a very challenging task. The prior model DyRM has introduced a technique to perform modeling of design reusability under three real-time constraints. The proposed study extends the DyRM model by incorporating optimization using multilayered perception techniques in neural network. The system takes the similar input ...

Leukaemia is a cancer of blood that causes more death than any other cancers among children and young adults under the age of 20. This disease can be cured if it is detected and treated at the early stage. Based on this argument, the requirement for fast analysis of blood cells for leukaemia is of paramount importance in the healthcare industry. This paper presents the classification of White B...