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12/18/2022
Contextually Enhanced ES-dRNN with Dynamic Attention for Short-Term Load Forecasting
In this paper, we propose a new short-term load forecasting (STLF) model...
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04/21/2022
STD: A Seasonal-Trend-Dispersion Decomposition of Time Series
The decomposition of a time series is an essential task that helps to un...
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03/17/2022
Recurrent Neural Networks for Forecasting Time Series with Multiple Seasonality: A Comparative Study
This paper compares recurrent neural networks (RNNs) with different type...
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03/02/2022
Boosted Ensemble Learning based on Randomized NNs for Time Series Forecasting
Time series forecasting is a challenging problem particularly when a tim...
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03/02/2022
ES-dRNN with Dynamic Attention for Short-Term Load Forecasting
Short-term load forecasting (STLF) is a challenging problem due to the c...
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12/05/2021
ES-dRNN: A Hybrid Exponential Smoothing and Dilated Recurrent Neural Network Model for Short-Term Load Forecasting
Short-term load forecasting (STLF) is challenging due to complex time se...
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07/08/2021
Ensembles of Randomized NNs for Pattern-based Time Series Forecasting
In this work, we propose an ensemble forecasting approach based on rando...
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07/04/2021
Autoencoder based Randomized Learning of Feedforward Neural Networks for Regression
Feedforward neural networks are widely used as universal predictive mode...
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07/04/2021
Randomized Neural Networks for Forecasting Time Series with Multiple Seasonality
This work contributes to the development of neural forecasting models wi...
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07/04/2021
Data-Driven Learning of Feedforward Neural Networks with Different Activation Functions
This work contributes to the development of a new data-driven method (D-...
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09/24/2020
N-BEATS neural network for mid-term electricity load forecasting
We address the mid-term electricity load forecasting (MTLF) problem. Thi...
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04/22/2020
Pattern-based Long Short-term Memory for Mid-term Electrical Load Forecasting
This work presents a Long Short-Term Memory (LSTM) network for forecasti...
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03/29/2020
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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03/29/2020
Ensemble Forecasting of Monthly Electricity Demand using Pattern Similarity-based Methods
This work presents ensemble forecasting of monthly electricity demand us...
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03/29/2020
A Hybrid Residual Dilated LSTM end Exponential Smoothing Model for Mid-Term Electric Load Forecasting
This work presents a hybrid and hierarchical deep learning model for mid...
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03/03/2020
Pattern Similarity-based Machine Learning Methods for Mid-term Load Forecasting: A Comparative Study
Pattern similarity-based methods are widely used in classification and r...
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09/04/2019
A Constructive Approach for Data-Driven Randomized Learning of Feedforward Neural Networks
Feedforward neural networks with random hidden nodes suffer from a probl...
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08/16/2019
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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08/15/2019
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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08/11/2019
Data-Driven Randomized Learning of Feedforward Neural Networks
Randomized methods of neural network learning suffer from a problem with...
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10/13/2017