abstract this study aims at profitability prediction of listed companies in tehran stocks exchange (tse), using artificial neural network. the respected sample consists of 90 firms from 2002  to 2009 (720 firm/years). attention to the framework of study reduced the number of 720 firm/years to 630 firm/years. these firms separated in two groups of learning sample (540 firm/years) and test sample...

A novel data-driven soft sensor is designed for online product quality prediction and control performance modification in industrial units. A combined approach of time variable parameter (TVP) model, dynamic auto regressive exogenous variable (DARX) algorithm, nonlinear correlation analysis and criterion-based elimination method is introduced in this work. The soft sensor performance validation...

Aerobic power (VO2max) is an important indicator of the health and physical fitness. Executive problems in direct VO2max measurement has led to developing sub-maximal aerobic power prediction equations. The purpose of present study was to develop native aerobic power prediction equation based on 6-Minute Walk Test (6MWT) and body composition indices in children. In 192 healthy children (8 to 12...

Computational prediction of protein localization is one common way to characterize the functions of newly sequenced proteins. Sequence features such as amino acid (AA) composition have been widely used for subcellular localization prediction due to their simplicity while suffering from low coverage and low prediction accuracy. We present a physichemical encoding method that maps protein sequenc...

We present and test a sequential learning algorithm for the prediction of human mobility that leverages large datasets of sequences to improve prediction accuracy, in particular for users with a short and non-repetitive data history such as tourists in a foreign country. The algorithm compensates for the difficulty of predicting the next location when there is limited evidence of past behavior ...

Statistical parsers have become increasingly accurate, to the point where they are useful in many natural language applications. However, estimating parsing accuracy on a wide variety of domains and genres is still a challenge in the absence of gold-standard parse trees. In this paper, we propose a technique that automatically takes into account certain characteristics of the domains of interes...

background : in medical studies, when the joint prediction about occurrence of two events should be anticipated, a statistical bivariate model is used. due to the limitations of usual statistical models, other methods such as artificial neural network (ann) and hybrid models could be used. in this paper, we propose a hybrid artificial neural network-genetic algorithm (ann-ga) model to predictio...