A novel decomposition-ensemble learning framework for multi-step ahead wind energy forecasting
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 …
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
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 …
the national system operator, who controls the level of the reservoirs based on a stochastic …
Forecasting wholesale prices of yellow corn through the Gaussian process regression
B Jin, X Xu - Neural Computing and Applications, 2024 - Springer
For market players and policy officials, commodity price forecasts are crucial problems that
are challenging to address due to the complexity of price time series. Given its strategic …
are challenging to address due to the complexity of price time series. Given its strategic …
Hybrid wavelet stacking ensemble model for insulators contamination forecasting
Contaminated insulators can have higher surface conductivity, which can result in
irreversible failures in the electrical power system. In this paper, the ultrasound equipment is …
irreversible failures in the electrical power system. In this paper, the ultrasound equipment is …
[HTML][HTML] Soybean and soybean oil price forecasting through the nonlinear autoregressive neural network (NARNN) and NARNN with exogenous inputs (NARNN–X)
X Xu, Y Zhang - Intelligent Systems with Applications, 2022 - Elsevier
Price forecasting is a key concern for market participants in the agriculture sector. This study
explores usefulness of the nonlinear autoregressive neural network (NARNN) and NARNN …
explores usefulness of the nonlinear autoregressive neural network (NARNN) and NARNN …
Steel price index forecasting through neural networks: the composite index, long products, flat products, and rolled products
X Xu, Y Zhang - Mineral Economics, 2023 - Springer
Forecasting commodity prices is a vital issue to a wide spectrum of market participants and
policy makers in the metal sector. In this work, the forecast problem is investigated by …
policy makers in the metal sector. In this work, the forecast problem is investigated by …
Corn cash-futures basis forecasting via neural networks
X Xu, Y Zhang - Advances in Computational Intelligence, 2023 - Springer
Cash-futures basis forecasting represents a vital concern for various market participants in
the agricultural sector, which has been rarely explored due to limitations on data and …
the agricultural sector, which has been rarely explored due to limitations on data and …
Canola and soybean oil price forecasts via neural networks
X Xu, Y Zhang - Advances in Computational Intelligence, 2022 - Springer
Forecasts of commodity prices are vital issues to market participants and policy-makers.
Those of cooking section oil are of no exception, considering its importance as one of main …
Those of cooking section oil are of no exception, considering its importance as one of main …
[HTML][HTML] Yellow corn wholesale price forecasts via the neural network
X Xu, Y Zhang - EconomiA, 2023 - emerald.com
Purpose Forecasts of commodity prices are vital issues to market participants and policy
makers. Those of corn are of no exception, considering its strategic importance. In the …
makers. Those of corn are of no exception, considering its strategic importance. In the …
[HTML][HTML] Electricity price forecasting based on self-adaptive decomposition and heterogeneous ensemble learning
Electricity price forecasting plays a vital role in the financial markets. This paper proposes a
self-adaptive, decomposed, heterogeneous, and ensemble learning model for short-term …
self-adaptive, decomposed, heterogeneous, and ensemble learning model for short-term …