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20172025
most citedImproving Randomized Learning of Feedforward Neural Networks by Appropriate Generation of Random Parameters

10 citations · 28 across the 18 of their papers we have counts for

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2 papers · 1 filter

eess.SP2020★ 4 cited

Pattern-based Long Short-term Memory for Mid-term Electrical Load Forecasting

Paweł Pełka, Grzegorz Dudek

This work presents a Long Short-Term Memory (LSTM) network for forecasting a monthly electricity demand time series with a one-year horizon. The novelty of this work is the use of…

eess.SP2020★ 1 cited

A Hybrid Residual Dilated LSTM end Exponential Smoothing Model for Mid-Term Electric Load Forecasting

Grzegorz Dudek, Paweł Pełka, Slawek Smyl

This work presents a hybrid and hierarchical deep learning model for mid-term load forecasting. The model combines exponential smoothing (ETS), advanced Long Short-Term Memory (LST…