Browsing by Subject "1D CNN"
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A novel hybrid deep learning approach including combination of 1D power signals and 2D signal images for power quality disturbance classification
(Pergamon-Elsevier Science Ltd, 2021)As a result of the widespread use of power electronic equipment and the increase in consumption, the importance of effective energy policies and the smart grid begins to increase. Nonlinear loads and other loads in electric ... -
Random fully connected layered 1D CNN for solving the Z-bus loss allocation problem
(Elsevier Sci Ltd, 2021)Power loss allocation methods should be efficient enough to meet the needs of the customers on the bus and effectively calculate the losses from generators and consumers. In order to perform these tasks, a highly robust ...