Classifying payment patterns with artificial neural networks: An autoencoder approach

Prediction the Return Fluctuations with Artificial Neural Networks' Approach

Time changes of return, inefficiency studies performed and presence of effective factors on share return rate are caused development modern and intelligent methods in estimation and evaluation of share return in stock companies. Aim of this research is prediction of return using financial variables with artificial neural network approach. Therefore, the statistical population of this study incl...

An Approach of Artificial Neural Networks Modeling Based on Fuzzy Regression for Forecasting Purposes

In this paper, a new approach of modeling for Artificial Neural Networks (ANNs) models based on the concepts of fuzzy regression is proposed. For this purpose, we reformulated ANN model as a fuzzy nonlinear regression model while it has advantages of both fuzzy regression and ANN models. Hence, it can be applied to uncertain, ambiguous, or complex environments due to its flexibility for forecas...

Artificial Neural Networks for Classifying Magnetic Measurements in Tokamak Reactors

This paper is mainly concerned with the application of a novel technique of data interpretation to the characterization and classification of measurements of plasma columns in Tokamak reactors for nuclear fusion applications. The proposed method exploits several concepts derived from soft computing theory. In particular, Artifical Neural Networks have been exploited to classify magnetic variabl...

The use of artificial neural networks in classifying lung scintigrams

Using artificial neural networks for classifying ICU patient states.

T he rapid accurate diagnosis of critical disorders is an essential component of intensive care. Traditional diagnostic techniques have relied on physician e.x.pe-ric nee, which is based on a data set chosen from his or her rather than from scientific merit. In this article, we aim to show that there are alternative methods of selecting clinical variables on which to base a diagnosis. We sugges...