Hybridization of hybrid structures for time series forecasting: A review
Achieving the desired accuracy in time series forecasting has become a binding domain,
and develo** a forecasting framework with a high degree of accuracy is one of the most …
and develo** a forecasting framework with a high degree of accuracy is one of the most …
Energy price prediction using data-driven models: A decade review
The accurate prediction of energy price is critical to the energy market orientation, and it can
provide a reference for policymakers and market participants. In practice, energy prices are …
provide a reference for policymakers and market participants. In practice, energy prices are …
A hybrid model for carbon price forecasting using GARCH and long short-term memory network
The reform of the EU ETS markets in 2017 has induced new carbon price forecasting
challenges. This study proposes a novel decomposition-ensemble paradigm VMD …
challenges. This study proposes a novel decomposition-ensemble paradigm VMD …
A combined forecasting system based on statistical method, artificial neural networks, and deep learning methods for short-term wind speed forecasting
Wind speed forecasting is gaining importance as the share of wind energy in electricity
systems increases. Numerous forecasting approaches have been used to predict wind …
systems increases. Numerous forecasting approaches have been used to predict wind …
Ensemble forecasting system for short-term wind speed forecasting based on optimal sub-model selection and multi-objective version of mayfly optimization algorithm
Z Liu, P Jiang, J Wang, L Zhang - Expert Systems with Applications, 2021 - Elsevier
Wind energy has attracted considerable attention in the past decades as a low-carbon,
environmentally friendly, and efficient renewable energy. However, the irregularity of wind …
environmentally friendly, and efficient renewable energy. However, the irregularity of wind …
A combined forecasting model for time series: Application to short-term wind speed forecasting
Wind speed forecasting has been growing in popularity, owing to the increased demand for
wind power electricity generation and developments in wind energy competitiveness. Many …
wind power electricity generation and developments in wind energy competitiveness. Many …
A novel machine learning-based electricity price forecasting model based on optimal model selection strategy
Current electricity price forecasting models rely on only simple hybridizations of data
preprocessing and optimization methods while ignoring the significance of adaptive data …
preprocessing and optimization methods while ignoring the significance of adaptive data …
An innovative random forest-based nonlinear ensemble paradigm of improved feature extraction and deep learning for carbon price forecasting
J Wang, X Sun, Q Cheng, Q Cui - Science of the Total Environment, 2021 - Elsevier
Carbon price is the basis of develo** a low carbon economy. The accurate carbon price
forecast can not only stimulate the actions of enterprises and families, but also encourage …
forecast can not only stimulate the actions of enterprises and families, but also encourage …
Predicting China's carbon price based on a multi-scale integrated model
S Qi, S Cheng, X Tan, S Feng, Q Zhou - Applied energy, 2022 - Elsevier
Carbon price is one of the core indicators of the carbon market. Making accurate predictions
of carbon prices based on insight into the volatility characteristics of the carbon market will …
of carbon prices based on insight into the volatility characteristics of the carbon market will …
Carbon price forecasting system based on error correction and divide-conquer strategies
X Niu, J Wang, L Zhang - Applied Soft Computing, 2022 - Elsevier
Carbon price forecasting is an important component of a sound carbon price market
mechanism. The accurate prediction of carbon prices is an active topic of research …
mechanism. The accurate prediction of carbon prices is an active topic of research …