Forecasting gold price using a novel hybrid model with ICEEMDAN and LSTM-CNN-CBAM
Y Liang, Y Lin, Q Lu - Expert Systems with Applications, 2022 - Elsevier
Gold price has always played an important role in the world economy and finance. In order
to predict the gold price more accurately, this paper proposes a novel decomposition …
to predict the gold price more accurately, this paper proposes a novel decomposition …
Stock price prediction using deep learning and frequency decomposition
Nonlinearity and high volatility of financial time series have made it difficult to predict stock
price. However, thanks to recent developments in deep learning and methods such as long …
price. However, thanks to recent developments in deep learning and methods such as long …
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 …
Ridge regression ensemble of machine learning models applied to solar and wind forecasting in Brazil and Spain
In recent years, with the rapid development of wind and solar power generation, some
problems arise gradually and are often inherent to intermittency. Currently, one of the …
problems arise gradually and are often inherent to intermittency. Currently, one of the …
Forecasting carbon price in China using a novel hybrid model based on secondary decomposition, multi-complexity and error correction
H Yang, X Yang, G Li - Journal of Cleaner Production, 2023 - Elsevier
As global warming intensifies, the reduction of carbon emissions is imminent. Carbon price
is directly related to whether carbon can be effectively reduced. Therefore, accurately …
is directly related to whether carbon can be effectively reduced. Therefore, accurately …
An adaptive hierarchical decomposition-based method for multi-step cutterhead torque forecast of shield machine
Cutterhead torque is generated by interaction between geological environment and shield
machine, which is one of the main load parameters of shield machine during the tunneling …
machine, which is one of the main load parameters of shield machine during the tunneling …
Long‐range precipitation forecast based on multipole and preceding fluctuations of sea surface temperature
X Wu, S Guo, S Qian, Z Wang, C Lai… - International Journal of …, 2022 - Wiley Online Library
Long-range precipitation forecasting is crucial for flooding control and water resources
management. However, making precise forecasting is rather difficult due to the complex …
management. However, making precise forecasting is rather difficult due to the complex …
A review of the application of hybrid machine learning models to improve rainfall prediction
Rainfall is one of the most important meteorological phenomena that impacts many fields,
including agriculture, energy, water resources management, and mining, among others …
including agriculture, energy, water resources management, and mining, among others …
A novel wind power forecasting system integrating time series refining, nonlinear multi-objective optimized deep learning and linear error correction
J Wang, Y Qian, L Zhang, K Wang, H Zhang - Energy Conversion and …, 2024 - Elsevier
Wind power prediction is crucial for successfully integrating large-scale wind energy with the
grid and achieving a carbon-neutral energy mix. However, previous studies encountered …
grid and achieving a carbon-neutral energy mix. However, previous studies encountered …
Hydrogeochemical characterization based water resources vulnerability assessment in India's first Ramsar site of Chilka lake
A limnological site is significantly characterized by rich biological, chemical, and physical
properties of the environment and is also described as the epitome of a large aquatic …
properties of the environment and is also described as the epitome of a large aquatic …