| 1 |
Achieving the carbon intensity target of China: A least squares support vector machine with mixture kernel function approach
Zhu BZ, Ye SX, Jiang MX, Wang P, Wu ZC, Xie R, Chevallier J, Wei YM
Applied Energy, 233, 196, 2019 |
| 2 |
Feature parameter extraction and intelligent estimation of the State-of-Health of lithium-ion batteries
Deng YW, Ying HJ, Jiaqiang E, Zhu H, Wei KX, Chen JW, Zhang F, Liao GL
Energy, 176, 91, 2019 |
| 3 |
Determination of physicochemical properties of petroleum derivatives and biodiesel using GC/MS and chemometric methods with uncertainty estimation
Rocha WFD, Sheen DA
Fuel, 243, 413, 2019 |
| 4 |
Developing steady and dynamic ORP models for mercury emissions control in power plants using WFGD operating data
Lv Y, Romero CE, Charles J, Pauvlinch KA, Watkins RW
Fuel, 235, 54, 2019 |
| 5 |
A hybrid remaining useful life prognostic method for proton exchange membrane fuel cell
Cheng YJ, Zerhouni N, Lu C
International Journal of Hydrogen Energy, 43(27), 12314, 2018 |
| 6 |
Multi-step ahead forecasting in electrical power system using a hybrid forecasting system
Du P, Wang JZ, Yang WD, Niu T
Renewable Energy, 122, 533, 2018 |
| 7 |
Development of a least squares support vector machine model for prediction of natural gas hydrate formation temperature
Mesbah M, Soroush E, Rezakazemi M
Chinese Journal of Chemical Engineering, 25(9), 1238, 2017 |
| 8 |
A dynamic model for the bed temperature prediction of circulating fluidized bed boilers based on least squares support vector machine with real operational data
Lv Y, Hong F, Yang TT, Fang F, Liu JZ
Energy, 124, 284, 2017 |
| 9 |
Short-term wind speed prediction: Hybrid of ensemble empirical mode decomposition, feature selection and error correction
Jiang Y, Huang GQ
Energy Conversion and Management, 144, 340, 2017 |
| 10 |
Equilibrium ratio of hydrocarbons and non-hydrocarbons at reservoir conditions: Experimental and modeling study
Ahmadi MA, Zendehboudi S, James LA
Fuel, 210, 315, 2017 |
