Advances in computational intelligence of polymer composite materials: machine learning assisted modeling, analysis and design
The superior multi-functional properties of polymer composites have made them an ideal
choice for aerospace, automobile, marine, civil, and many other technologically demanding …
choice for aerospace, automobile, marine, civil, and many other technologically demanding …
A review and discussion of decomposition-based hybrid models for wind energy forecasting applications
Z Qian, Y Pei, H Zareipour, N Chen - Applied energy, 2019 - Elsevier
With the continuous growth of wind power integration into the electrical grid, accurate wind
power forecasting is an important component in management and operation of power …
power forecasting is an important component in management and operation of power …
Carbon price forecasting based on CEEMDAN and LSTM
F Zhou, Z Huang, C Zhang - Applied energy, 2022 - Elsevier
Abstract After signing the Paris Agreement and piloting carbon trading for many years, China
has taken a significant step toward carbon neutrality. Carbon price forecasting is helpful to …
has taken a significant step toward carbon neutrality. Carbon price forecasting is helpful to …
A dual-scale deep learning model based on ELM-BiLSTM and improved reptile search algorithm for wind power prediction
J Xiong, T Peng, Z Tao, C Zhang, S Song, MS Nazir - Energy, 2023 - Elsevier
Accurate wind power forecast is critical to the efficient and safe running of power systems. A
hybrid model that combines complementary ensemble empirical mode decomposition …
hybrid model that combines complementary ensemble empirical mode decomposition …
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 …
Application of variational mode decomposition and chaotic grey wolf optimizer with support vector regression for forecasting electric loads
Z Zhang, WC Hong - Knowledge-Based Systems, 2021 - Elsevier
Accurate electric load forecasting is critical in guaranteeing the efficiency of the load
dispatch and supply by a power system, which prevents the wasting of electricity and …
dispatch and supply by a power system, which prevents the wasting of electricity and …
Stock price prediction using deep learning and frequency decomposition
H Rezaei, H Faaljou, G Mansourfar - Expert Systems with Applications, 2021 - Elsevier
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 …
Multi-step-ahead wind speed forecasting based on a hybrid decomposition method and temporal convolutional networks
Recently, the boom in wind power industry has called for the accurate and stable wind
speed forecasting, on which reliable wind power generation systems depend heavily. Due to …
speed forecasting, on which reliable wind power generation systems depend heavily. Due to …
PM2. 5 concentration forecasting at surface monitoring sites using GRU neural network based on empirical mode decomposition
G Huang, X Li, B Zhang, J Ren - Science of the Total Environment, 2021 - Elsevier
The main component of haze is the particulate matter (PM) 2.5. How to explore the laws of
PM2. 5 concentration changes is the main content of air quality prediction. Combining the …
PM2. 5 concentration changes is the main content of air quality prediction. Combining the …
A novel complexity-based mode feature representation for feature extraction of ship-radiated noise using VMD and slope entropy
Y Li, B Tang, Y Yi - Applied Acoustics, 2022 - Elsevier
To extract more distinguishing features of ships, slope entropy (SloE) is introduced into
underwater acoustic signal processing as a new feature to analyze ship-radiated noise …
underwater acoustic signal processing as a new feature to analyze ship-radiated noise …