| 1 |
Multi-step wind speed forecast based on sample clustering and an optimized hybrid system
Chen XJ, Zhao J, Jia XZ, Li ZL
Renewable Energy, 165, 595, 2021 |
| 2 |
Advance short-term wind energy quality assessment based on instantaneous standard deviation and variogram of wind speed by a hybrid method
Liu GB, Zhou JZ, Jia BJ, He FF, Yang YQ, Sun N
Applied Energy, 238, 643, 2019 |
| 3 |
Crude oil price prediction model with long short term memory deep learning based on prior knowledge data transfer
Cen ZP, Wang J
Energy, 169, 160, 2019 |
| 4 |
A new hybrid model to predict the electrical load in five states of Australia
Wu JR, Cui ZS, Chen YY, Kong DM, Wang YG
Energy, 166, 598, 2019 |
| 5 |
An enhanced PCA-based chiller sensor fault detection method using ensemble empirical mode decomposition based denoising
Li GN, Hu YP
Energy and Buildings, 183, 311, 2019 |
| 6 |
Oil-gas-water three-phase flow characterization and velocity measurement based on time-frequency decomposition
Shi XW, Tan C, Dong F, Murai YC
International Journal of Multiphase Flow, 111, 219, 2019 |
| 7 |
A hybrid system for short-term wind speed forecasting
He QQ, Wang JZ, Lu HY
Applied Energy, 226, 756, 2018 |
| 8 |
A novel decompose-ensemble methodology with AIC-ANN approach for crude oil forecasting
Ding YS
Energy, 154, 328, 2018 |
| 9 |
Improving forecasting accuracy of daily enterprise electricity consumption using a random forest based on ensemble empirical mode decomposition
Li C, Tao Y, Ao WG, Yang S, Bai Y
Energy, 165, 1220, 2018 |
| 10 |
Comparison of two new intelligent wind speed forecasting approaches based on Wavelet Packet Decomposition, Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Artificial Neural Networks
Liu H, Mi XW, Li YF
Energy Conversion and Management, 155, 188, 2018 |
