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Physical Sciences and Mathematics Commons

Open Access. Powered by Scholars. Published by Universities.®

Journal

TÜBİTAK

Artificial neural networks

2017

Articles 1 - 2 of 2

Full-Text Articles in Physical Sciences and Mathematics

A New Approach For Digital Image Watermarking To Predict Optimal Blocks Using Artificial Neural Networks, Raheleh Khorsand Movaghar, Hossein Khaleghi Bizaki Jan 2017

A New Approach For Digital Image Watermarking To Predict Optimal Blocks Using Artificial Neural Networks, Raheleh Khorsand Movaghar, Hossein Khaleghi Bizaki

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we propose a novel nonblind digital image watermarking based on discrete wavelet transform and singular value decomposition. This robust scheme takes advantage of artificial neural networks for selecting suitable image blocks in which the watermark signal can be embedded. Local characteristics of the blocks such as luminance and texture sensitivity are the main criteria that the selections are based on. Generally, selection is based on a prediction of the results with the objective of transparency and watermark resilience. In other words, before embedding the water mark signal, it is estimated which blocks would be the best for …


Probabilistic Day-Ahead System Marginal Price Forecasting With Ann For The Turkish Electricity Market, Erdem Özgüner, Osman Bülent Tör, Ali̇ Nezi̇h Güven Jan 2017

Probabilistic Day-Ahead System Marginal Price Forecasting With Ann For The Turkish Electricity Market, Erdem Özgüner, Osman Bülent Tör, Ali̇ Nezi̇h Güven

Turkish Journal of Electrical Engineering and Computer Sciences

This study presents a system day-ahead hourly market clearing price forecasting tool for the day-ahead (DA) market and a system DA hourly marginal price forecasting tool for the real-time market of the Turkish electric market (TEM). These forecasting tools are developed based on artificial neural networks (ANNs). A series of historical price data of the TEM are utilized to model and optimize the ANN structure and to develop the ANN-based price forecasting tool. The methodology used to select the optimum ANN architecture provides the minimum daily mean absolute percentage error for both day-ahead market prices in the TEM. Performances of …