| 1 |
The moderating role of renewable and non-renewable energy in environment-income nexus for ASEAN countries: Evidence from Method of Moments Quantile Regression
Anwar A, Siddique M, Dogan E, Sharif A
Renewable Energy, 164, 956, 2021 |
| 2 |
Crude oil prices and clean energy stock indices: Lagged and asymmetric effects with quantile regression
Dawar I, Dutta A, Bouri E, Saeed T
Renewable Energy, 163, 288, 2021 |
| 3 |
Deterministic and probabilistic wind speed forecasting with de-noising-reconstruction strategy and quantile regression based algorithm
Hu JM, Heng JN, Wen JM, Zhao WG
Renewable Energy, 162, 1208, 2020 |
| 4 |
Fault detection of wind turbines via multivariate process monitoring based on vine copulas
Xu QF, Fan ZH, Jia WY, Jiang CX
Renewable Energy, 161, 939, 2020 |
| 5 |
Probabilistic individual load forecasting using pinball loss guided LSTM
Wang Y, Gan DH, Sun MY, Zhang N, Lu ZX, Kang CQ
Applied Energy, 235, 10, 2019 |
| 6 |
Electricity consumption probability density forecasting method based on LASSO-Quantile Regression Neural Network
He YY, Qin Y, Wang S, Wang X, Wang C
Applied Energy, 233, 565, 2019 |
| 7 |
A D-vine copula quantile regression approach for the prediction of residential heating energy consumption based on historical data
Niemierko R, Toppel J, Trankler T
Applied Energy, 233, 691, 2019 |
| 8 |
Prediction and explanation of the formation of the Spanish day-ahead electricity price through machine learning regression
Diaz G, Coto J, Gomez-Aleixandre J
Applied Energy, 239, 610, 2019 |
| 9 |
Energy intensity and its differences across China's regions: Combining econometric and decomposition analysis
Guang FT, He Y, Le Wen, Sharp B
Energy, 180, 989, 2019 |
| 10 |
Wind speed forecasting based on Quantile Regression Minimal Gated Memory Network and Kernel Density Estimation
Zhang ZD, Qin H, Liu YQ, Yao LQ, Yu X, Lu JT, Jiang ZQ, Feng ZK
Energy Conversion and Management, 196, 1395, 2019 |
