In this paper, vapor pressure for pure compounds is estimated using the Artificial Neural Networks and a simple Group Contribution Method (ANN–GCM). For model comprehensiveness, materials were chosen from various families. Most of materials are from 12 families. Vapor pressure data of 100 compounds is used to train, validate and test the ANN-GCM model. Va...

Digital Images are contaminated by noise during acquisition and/or transmission over communication channel. Eliminating impulse noise and uniform noise from the images without damaging their boundaries and fine details is an important and a challenging task in the image processing applications. A nonlinear technique based on decision mechanism for suppressing impulse noise and uniform noise fro...

Basic definitions concerning the multi-layer feed-forward neural networks are given. The back-propagation training algorithm is explained. Partial derivatives of the objective function with respect to the weight and threshold coefficients are derived. These derivatives are valuable for an adaptation process of the considered neural network. Training and generalisation of multi-layer feed-forwar...

Facial expression recognition is also gaining interest among the researchers because of its inevitable advantages in image retrieval which can be extended many fields like medicine, artificial intelligence, robotics and neural networks. So it is one of the hot topic for researchers. Existing methods such as PCA, LDA, LPP etc. with Euclidian distance classifier are popular. Neural network classi...

the main purpose of this paper is prediction of tse corporate financial bankruptcy using artificial neural networks. the mean values of key ratios reported in past bankruptcy studies were selected for neural network inputs (working capital to total assets, net income to total assets, total debt to total assets, current assets to current liabilities, quick assets to current liabilities). the neu...

Railway scheduling is a complex task of rail operators that involves the generation of a conflict-free train timetable. This paper presents a discrete-event simulation-based optimization approach for solving the train timetabling problem to minimize total weighted unplanned stop time in a hybrid single and double track railway networks. The designed simulation model is used as a platform for ge...

In this paper is presented an investigation of the speech recognition classification performance. This investigation on the speech recognition classification performance is performed using two standard neural networks structures as the classifier. The utilized standard neural network types include Feed-forward Neural Network (NN) with back propagation algorithm and a Radial Basis Functions Neur...