Grzegorz Dudek

Orcid: 0000-0002-2285-0327

According to our database1, Grzegorz Dudek authored at least 55 papers between 2008 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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Bibliography

2024
Contextually enhanced ES-dRNN with dynamic attention for short-term load forecasting.
Neural Networks, January, 2024

Forecasting cryptocurrencies volatility using statistical and machine learning methods: A comparative study.
Appl. Soft Comput., January, 2024

2023
STD: A Seasonal-Trend-Dispersion Decomposition of Time Series.
IEEE Trans. Knowl. Data Eng., October, 2023

Ensemble of Randomized Neural Networks with STD Decomposition for Forecasting Time Series with Complex Seasonality.
Proceedings of the Advances in Computational Intelligence, 2023

Forecasting Cryptocurrency Prices Using Contextual ES-adRNN with Exogenous Variables.
Proceedings of the Computational Science - ICCS 2023, 2023

Combining Forecasts using Meta-Learning: A Comparative Study for Complex Seasonality.
Proceedings of the 10th IEEE International Conference on Data Science and Advanced Analytics, 2023

2022
A Hybrid Residual Dilated LSTM and Exponential Smoothing Model for Midterm Electric Load Forecasting.
IEEE Trans. Neural Networks Learn. Syst., 2022

Recurrent Neural Networks for Forecasting Time Series with Multiple Seasonality: A Comparative Study.
CoRR, 2022

ES-dRNN with Dynamic Attention for Short-Term Load Forecasting.
Proceedings of the International Joint Conference on Neural Networks, 2022

Boosted Ensemble Learning Based on Randomized NNs for Time Series Forecasting.
Proceedings of the Computational Science - ICCS 2022, 2022

2021
ES-dRNN: A Hybrid Exponential Smoothing and Dilated Recurrent Neural Network Model for Short-Term Load Forecasting.
CoRR, 2021

Ensembles of Randomized NNs for Pattern-based Time Series Forecasting.
CoRR, 2021

Pattern similarity-based machine learning methods for mid-term load forecasting: A comparative study.
Appl. Soft Comput., 2021

A constructive approach to data-driven randomized learning for feedforward neural networks.
Appl. Soft Comput., 2021

Randomized Neural Networks for Forecasting Time Series with Multiple Seasonality.
Proceedings of the Advances in Computational Intelligence, 2021

Autoencoder based Randomized Learning of Feedforward Neural Networks for Regression.
Proceedings of the International Joint Conference on Neural Networks, 2021

Ensembles of Randomized Neural Networks for Pattern-Based Time Series Forecasting.
Proceedings of the Neural Information Processing - 28th International Conference, 2021

Data-Driven Learning of Feedforward Neural Networks with Different Activation Functions.
Proceedings of the Artificial Intelligence and Soft Computing, 2021

2020
Multilayer perceptron for short-term load forecasting: from global to local approach.
Neural Comput. Appl., 2020

N-BEATS neural network for mid-term electricity load forecasting.
CoRR, 2020

A Hybrid Residual Dilated LSTM end Exponential Smoothing Model for Mid-Term Electric Load Forecasting.
CoRR, 2020

Are Direct Links Necessary in RVFL NNs for Regression?
CoRR, 2020

Pattern-based Long Short-term Memory for Mid-term Electrical Load Forecasting.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Data-Driven Randomized Learning of Feedforward Neural Networks.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

3ETS+RD-LSTM: A New Hybrid Model for Electrical Energy Consumption Forecasting.
Proceedings of the Neural Information Processing - 27th International Conference, 2020

Generating Random Parameters in Feedforward Neural Networks with Random Hidden Nodes: Drawbacks of the Standard Method and How to Improve It.
Proceedings of the Neural Information Processing - 27th International Conference, 2020

Ensemble Forecasting of Monthly Electricity Demand Using Pattern Similarity-Based Methods.
Proceedings of the Artificial Intelligence and Soft Computing, 2020

Are Direct Links Necessary in Random Vector Functional Link Networks for Regression?
Proceedings of the Artificial Intelligence and Soft Computing, 2020

2019
Generating random weights and biases in feedforward neural networks with random hidden nodes.
Inf. Sci., 2019

A Constructive Approach for Data-Driven Randomized Learning of Feedforward Neural Networks.
CoRR, 2019

Improving Randomized Learning of Feedforward Neural Networks by Appropriate Generation of Random Parameters.
Proceedings of the Advances in Computational Intelligence, 2019

Pattern-Based Forecasting Monthly Electricity Demand Using Multilayer Perceptron.
Proceedings of the Artificial Intelligence and Soft Computing, 2019

Sensitivity Analysis of the Neural Networks Randomized Learning.
Proceedings of the Artificial Intelligence and Soft Computing, 2019

2017
Artificial Immune System With Local Feature Selection for Short-Term Load Forecasting.
IEEE Trans. Evol. Comput., 2017

A Method of Generating Random Weights and Biases in Feedforward Neural Networks with Random Hidden Nodes.
CoRR, 2017

Neuro-Fuzzy System for Medium-Term Electric Energy Demand Forecasting.
Proceedings of the Information Systems Architecture and Technology: Proceedings of 38th International Conference on Information Systems Architecture and Technology - ISAT 2017, 2017

Classification Tree for Material Defect Detection Using Active Thermography.
Proceedings of the Information Systems Architecture and Technology: Proceedings of 38th International Conference on Information Systems Architecture and Technology - ISAT 2017, 2017

Multivariate Regression Tree for Pattern-Based Forecasting Time Series with Multiple Seasonal Cycles.
Proceedings of the Information Systems Architecture and Technology: Proceedings of 38th International Conference on Information Systems Architecture and Technology - ISAT 2017, 2017

2016
Neural networks for pattern-based short-term load forecasting: A comparative study.
Neurocomputing, 2016

2015
Pattern similarity-based methods for short-term load forecasting - Part 1: Principles.
Appl. Soft Comput., 2015

Pattern similarity-based methods for short-term load forecasting - Part 2: Models.
Appl. Soft Comput., 2015

Extreme learning machine for function approximation - interval problem of input weights and biases.
Proceedings of the 2nd IEEE International Conference on Cybernetics, 2015

Extreme Learning Machine as a Function Approximator: Initialization of Input Weights and Biases.
Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015, 2015

2014
Generalized Regression Neural Network for Forecasting Time Series with Multiple Seasonal Cycles.
Proceedings of the Intelligent Systems'2014, 2014

Short-Term Load Forecasting Using Random Forests.
Proceedings of the Intelligent Systems'2014, 2014

Tournament Searching Method for Optimization of the Forecasting Model Based on the Nadaraya-Watson Estimator.
Proceedings of the Artificial Intelligence and Soft Computing, 2014

2013
Artificial Immune System for Forecasting Time Series with Multiple Seasonal Cycles.
Trans. Comput. Collect. Intell., 2013

Genetic algorithm with binary representation of generating unit start-up and shut-down times for the unit commitment problem.
Expert Syst. Appl., 2013

Forecasting Time Series with Multiple Seasonal Cycles Using Neural Networks with Local Learning.
Proceedings of the Artificial Intelligence and Soft Computing, 2013

2012
An Artificial Immune System for Classification With Local Feature Selection.
IEEE Trans. Evol. Comput., 2012

Tournament Feature Selection with Directed Mutations.
Proceedings of the Swarm and Evolutionary Computation, 2012

Variable Selection in the Kernel Regression Based Short-Term Load Forecasting Model.
Proceedings of the Artificial Intelligence and Soft Computing, 2012

2011
Artificial Immune Clustering Algorithm to Forecasting Seasonal Time Series.
Proceedings of the Computational Collective Intelligence. Technologies and Applications, 2011

2010
Tournament Searching Method to Feature Selection Problem.
Proceedings of the Artifical Intelligence and Soft Computing, 2010

2008
Artificial Immune System for Short-Term Electric Load Forecasting.
Proceedings of the Artificial Intelligence and Soft Computing, 2008


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