This paper examines the e ectiveness of using a quasi-Newton based training of a feedforward neural network for forecasting. We have developed a novel quasi-Newton based training algorithm using a generalized logistic function. We have shown that a well designed feed forward structure can lead to a good forecast without the use of the more complicated feedback/feedforward structure of the recur...

In this paper, we introduce two artificial neural network formulations that can be used to predict the preference ratings from the pairwise comparison matrices of the Analytic Hierarchy Process (AHP). First, we introduce a modified Hopfield network that can be used to exactly determine the vector of preference ratings associated with a positive reciprocal comparison matrix. The dynamics of this...

In this article, the effect of operating conditions, such as temperature, Gas Hourly Space Velocity (GHSV), CH4/O2 ratio and diluents gas (mol% N2) on ethylene production by Oxidative Coupling of Methane (OCM) in a fixed bed reactor at atmospheric pressure was studied over Mn/Na2WO4/SiO2 ca...

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...

in this article, the effect of operating conditions, such as temperature, gas hourly space velocity (ghsv), ch4/o2 ratio and diluents gas (mol% n2) on ethylene production by oxidative coupling of methane (ocm) in a fixed bed reactor at atmospheric pressure was studied over mn/na2wo4/sio2 catalyst. based on the properties of neural networks, an artificial neural network was used for model develo...

Early detection of cancer is the most promising way to enhance a patient's chance for survival. This paper presents a computer aided classification method in computed tomography (CT) images of lungs developed using artificial neural network. The entire lung is segmented from the CT images and the parameters are calculated from the segmented image. The statistical parameters like mean, standard ...