In hhwangbo/gainML: Machine Learning-Based Analysis of Potential Power Gain from Passive Device Installation on Wind Turbine Generators
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
gainML
The goal of gainML is to provide an effective machine learning-based tool that quantifies the gain of passive device installation on wind turbine generators (WTGs).
Installation
You can install the released version of gainML from CRAN with:
install.packages("gainML")
Example
Examples are given in the package manual and the vignette, so please refer to them.
hhwangbo/gainML documentation built on June 26, 2019, 11 a.m.
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knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%" )
gainML
The goal of gainML is to provide an effective machine learning-based tool that quantifies the gain of passive device installation on wind turbine generators (WTGs).
Installation
You can install the released version of gainML from CRAN with:
install.packages("gainML")
Example
Examples are given in the package manual and the vignette, so please refer to them.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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