| 1 |
Making sense of parameter estimation and model simulation in bioprocesses
Sadino-Riquelme MC, Rivas J, Jeison D, Hayes RE, Donoso-Bravo A
Biotechnology and Bioengineering, 117(5), 1357, 2020 |
| 2 |
A multi-objective wind speed and wind power prediction interval forecasting using variational modes decomposition based Multi-kernel robust ridge regression
Naik J, Dash PK, Dhar S
Renewable Energy, 136, 701, 2019 |
| 3 |
A novel prediction intervals method integrating an error & self-feedback extreme learning machine with particle swarm optimization for energy consumption robust prediction
Xu Y, Zhang MQ, Ye LL, Zhu QX, Geng ZQ, He YL, Han YM
Energy, 164, 137, 2018 |
| 4 |
An advanced approach for optimal wind power generation prediction intervals by using self-adaptive evolutionary extreme learning machine
Mahmoud T, Dong ZY, Ma J
Renewable Energy, 126, 254, 2018 |
| 5 |
Interval prediction of solar power using an Improved Bootstrap method
Li KW, Wang R, Lei HT, Zhang T, Liu YJ, Zheng XK
Solar Energy, 159, 97, 2018 |
| 6 |
An ensemble prediction intervals approach for short-term PV power forecasting
Ni Q, Zhuang SX, Sheng HM, Kang GQ, Xiao J
Solar Energy, 155, 1072, 2017 |
| 7 |
Calculation of solar irradiation prediction intervals combining volatility and kernel density estimates
Trapero JR
Energy, 114, 266, 2016 |
| 8 |
Model-free computation of ultra-short-term prediction intervals of solar irradiance
Torregrossa D, Le Boudec JY, Paolone M
Solar Energy, 124, 57, 2016 |
| 9 |
Real-time prediction intervals for intra-hour DNI forecasts
Chu YH, Li MY, Pedro HTC, Coimbra CFM
Renewable Energy, 83, 234, 2015 |
| 10 |
Quantifying uncertainties of neural network-based electricity price forecasts
Khosravi A, Nahavandi S, Creighton D
Applied Energy, 112, 120, 2013 |
