In prediction-based reversible watermarking schemes, watermark bits are embedded in the prediction errors. An accurate prediction results in smaller prediction errors, more efficient embedding, and less distortion for the watermarked image. In this paper, an accurate prediction is made using artificial neural networks. Before the embedding operation, 2 neural networks are trained by the pixel v...

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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...

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...

short-term prediction of traffic flow is central to alleviating congestion and controlling the negative impacts of environmental pollution resulting from vehicle emissions on both inter- and intra-urban highways. the strong need to monitor and control congestion time and costs for metropolis in developing countries has therefore motivated the current study. this paper establishes the applicatio...

This paper addresses wind speed prediction in the dynamic line rating (DLR) environment. We have described architecture of DLR system as well main characteristics nonlinear forecasting models, such neural and fuzzy logic networks. Described models were tested compared using real data (time series with on speed, direction, air temperature, solar radiation). The goal was to increase accuracy time...