A novel decomposition-ensemble learning framework for multi-step ahead wind energy forecasting

RG da Silva, MHDM Ribeiro, SR Moreno, VC Mariani… - Energy, 2021 - Elsevier
Wind energy is one of the sources which is still in development in Brazil. However, it already
represents 17% of the National Interconnected System. Due to the high level of uncertainty …

Time series forecasting using ensemble learning methods for emergency prevention in hydroelectric power plants with dam

SF Stefenon, MHDM Ribeiro, A Nied, KC Yow… - Electric Power Systems …, 2022 - Elsevier
In hydroelectric plants, the responsibility for the operation of the reservoirs typically lies with
the national system operator, who controls the level of the reservoirs based on a stochastic …

Decoding electroencephalography signal response by stacking ensemble learning and adaptive differential evolution

MHDM Ribeiro, RG da Silva, JHK Larcher, A Mendes… - Sensors, 2023 - mdpi.com
Electroencephalography (EEG) is an exam widely adopted to monitor cerebral activities
regarding external stimuli, and its signals compose a nonlinear dynamical system. There are …

Day-ahead electricity price forecasting employing a novel hybrid frame of deep learning methods: A case study in NSW, Australia

YQ Tan, YX Shen, XY Yu, X Lu - Electric Power Systems Research, 2023 - Elsevier
Day-ahead electricity price forecasting plays a vital role in electricity markets under
liberalization and deregulation, which can provide references for participants in bidding …

Comparative Analysis between Intelligent Machine Committees and Hybrid Deep Learning with Genetic Algorithms in Energy Sector Forecasting: A Case Study on …

T Conte, R Oliveira - Energies, 2024 - mdpi.com
Global environmental impacts such as climate change require behavior from society that
aims to minimize greenhouse gas emissions. This includes the substitution of fossil fuels …

Far beyond day-ahead with econometric models for electricity price forecasting

P Ghelasi, F Ziel - arXiv preprint arXiv:2406.00326, 2024 - arxiv.org
The surge in global energy prices during the recent energy crisis, which peaked in 2022,
has intensified the need for mid-term to long-term forecasting for hedging and valuation …

[PDF][PDF] Artificial Intelligence and Signal Decomposition Approach Applied to Retail Sales Forecasting

RSD Silva, M Ribeiro, VHK Larcher, VC Mariani… - Training - sbic.org.br
Sales forecasting is essential for decision-making and are crucial in many areas of a firm,
such as planning and scheduling, resource management, marketing, logistics, and supply …

An Adaptive Filtering Method for Bridge Vibration Signals Based on Improved CEEMDAN and Multi-Scale Permutation Entropy.

D He, B Wang, X Gao, X Wang - Environmental & Earth …, 2021 - search.ebscohost.com
Aiming at the serious noise of bridge vibration signals in complex environment, this paper
proposed an adaptive filtering and denoising optimization method for bridge structural …

[PDF][PDF] Selection of an Artificial Intelligence Forecasting Approach for PV Panel Prices

A Alhosani, S Amer, A Sleptchenko - ieomsociety.org
As the world moves towards renewable energy sources, solar energy is becoming more
widely recognized. This impacts photovoltaic (PV) panel prices, which requires deeper …