Provides an effective machine learning-based tool that quantifies the gain of passive device installation on wind turbine generators. H. Hwangbo, Y. Ding, and D. Cabezon (2019) <doi:10.48550/arXiv.1906.05776>.
Version: 0.1.0 Depends: R (≥ 3.6.0) Imports: fields (≥ 9.0), FNN (≥ 1.1), utils, stats Suggests: knitr, rmarkdown Published: 2019-06-28 DOI: 10.32614/CRAN.package.gainML Author: Hoon Hwangbo [aut, cre], Yu Ding [aut], Daniel Cabezon [aut], Texas A&M University [cph], EDP Renewables [cph] Maintainer: Hoon Hwangbo <hhwangb1 at utk.edu> License: GPL-3 Copyright: Copyright (c) 2019 Y. Ding, H. Hwangbo, Texas A&M University, D. Cabezon, and EDP Renewables NeedsCompilation: no CRAN checks: gainML results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=gainML to link to this page.
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