APLIKASI ALGORITMA FEED FORWARD BACKPROPAGATION UNTUK BEBAN LISTRIK HARI LIBUR PADA TIPE BEBAN ANOMALI

Linda Faridah, M. A. Risnandar, Imam Taufiqurrahman, A. Rahayu
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Abstract

Load pattern for holiday have significant differenct from weekday day, so that require special prediction. This research have purpose to test the performance feed forward backpropagation to know accuracy level of load forecasting for holiday anomalous load. Learning algorithm used feed forward backpropagation from artificial neural network with matlab. Load forecasting optimization is change learning rate and some of learning input. The reasult of this reasult showed learning input give best reasult on mean but difference from that value is small, so learning rate variation small affected at learning
假日负荷模式与工作日有显著差异,需要特殊预测。本研究旨在测试前馈反向传播的性能,以了解假日异常负荷预测的精度水平。学习算法采用人工神经网络的前馈反向传播。负荷预测优化是改变学习率和一些学习输入。结果表明,学习输入在均值上给出了最好的结果,但与均值的差异很小,因此学习率的变化对学习的影响很小
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