
NBEATS neural network for midterm electricity load forecasting
We address the midterm electricity load forecasting (MTLF) problem. Thi...
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Patternbased Long Shortterm Memory for Midterm Electrical Load Forecasting
This work presents a Long ShortTerm Memory (LSTM) network for forecasti...
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Are Direct Links Necessary in RVFL NNs for Regression?
A random vector functional link network (RVFL) is widely used as a unive...
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Ensemble Forecasting of Monthly Electricity Demand using Pattern Similaritybased Methods
This work presents ensemble forecasting of monthly electricity demand us...
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A Hybrid Residual Dilated LSTM end Exponential Smoothing Model for MidTerm Electric Load Forecasting
This work presents a hybrid and hierarchical deep learning model for mid...
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Pattern Similaritybased Machine Learning Methods for Midterm Load Forecasting: A Comparative Study
Pattern similaritybased methods are widely used in classification and r...
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A Constructive Approach for DataDriven Randomized Learning of Feedforward Neural Networks
Feedforward neural networks with random hidden nodes suffer from a probl...
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Generating Random Parameters in Feedforward Neural Networks with Random Hidden Nodes: Drawbacks of the Standard Method and How to Improve It
The standard method of generating random weights and biases in feedforwa...
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Improving Randomized Learning of Feedforward Neural Networks by Appropriate Generation of Random Parameters
In this work, a method of random parameters generation for randomized le...
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DataDriven Randomized Learning of Feedforward Neural Networks
Randomized methods of neural network learning suffer from a problem with...
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A Method of Generating Random Weights and Biases in Feedforward Neural Networks with Random Hidden Nodes
Neural networks with random hidden nodes have gained increasing interest...
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Grzegorz Dudek
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