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Full-Text Articles in Physical Sciences and Mathematics
Short-Term Load Forecasting Using Mixed Lazy Learning Method, Seyed-Masoud Barakati, Ali Akbar Gharaveisi, Seyed-Mohammad Reza Rafiei
Short-Term Load Forecasting Using Mixed Lazy Learning Method, Seyed-Masoud Barakati, Ali Akbar Gharaveisi, Seyed-Mohammad Reza Rafiei
Turkish Journal of Electrical Engineering and Computer Sciences
A novel short-term load forecasting method based on the lazy learning (LL) algorithm is proposed. The LL algorithm's input data are electrical load information, daily electricity consumption patterns, and temperatures in a specified region. In order to verify the ability of the proposed method, a load forecasting problem, using the Pennsylvania-New Jersey-Maryland Interconnection electrical load data, is carried out. Three LL models are proposed: constant, linear, and mixed models. First, the performances of the 3 developed models are compared using the root mean square error technique. The best technique is then selected to compete with the state-of-the-art neural network (NN) …
A Comparative Performance Evaluation Of Various Approaches For Liver Segmentation From Spir Images, Evgi̇n Göçeri̇, Mehmet Zübeyi̇r Ünlü, Oğuz Di̇cle
A Comparative Performance Evaluation Of Various Approaches For Liver Segmentation From Spir Images, Evgi̇n Göçeri̇, Mehmet Zübeyi̇r Ünlü, Oğuz Di̇cle
Turkish Journal of Electrical Engineering and Computer Sciences
Developing a robust method for liver segmentation from magnetic resonance images is a challenging task because of the similar intensity values between adjacent organs, the geometrically complex liver structure, and injection of contrast media. Most importantly, a high anatomical variability of a healthy or diseased liver is a major challenge in defining the exact boundaries of the liver. Several artifacts of pulsation, motion, and partial volume effects are also among the variety of factors that make automatic liver segmentation difficult. In this paper, we present an overview of liver segmentation methods in magnetic resonance images and show comparative results of …