Short term electricity demand forecasting using partially linear additive quantile regression with an application to the unit commitment problem


Journal article


Moshoko Emily Lebotsa, Caston Sigauke, Alphonce Bere, Robert Fildes, John E. Boylan
Applied Energy, vol. 222, 2018 Jun 15, pp. 104-118

Cite

Cite

APA   Click to copy
Lebotsa, M. E., Sigauke, C., Bere, A., Fildes, R., & Boylan, J. E. (2018). Short term electricity demand forecasting using partially linear additive quantile regression with an application to the unit commitment problem. Applied Energy, 222, 104–118.


Chicago/Turabian   Click to copy
Lebotsa, Moshoko Emily, Caston Sigauke, Alphonce Bere, Robert Fildes, and John E. Boylan. “Short Term Electricity Demand Forecasting Using Partially Linear Additive Quantile Regression with an Application to the Unit Commitment Problem.” Applied Energy 222 (June 15, 2018): 104–118.


MLA   Click to copy
Lebotsa, Moshoko Emily, et al. “Short Term Electricity Demand Forecasting Using Partially Linear Additive Quantile Regression with an Application to the Unit Commitment Problem.” Applied Energy, vol. 222, June 2018, pp. 104–18.


BibTeX   Click to copy

@article{moshoko2018a,
  title = {Short term electricity demand forecasting using partially linear additive quantile regression with an application to the unit commitment problem},
  year = {2018},
  month = jun,
  day = {15},
  journal = {Applied Energy},
  pages = {104-118},
  volume = {222},
  author = {Lebotsa, Moshoko Emily and Sigauke, Caston and Bere, Alphonce and Fildes, Robert and Boylan, John E.},
  month_numeric = {6}
}

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