CRAN

gainML 0.1.0

Machine Learning-Based Analysis of Potential Power Gain from Passive Device Installation on Wind Turbine Generators

Released Jun 28, 2019 by Hoon Hwangbo

This package is available for Renjin and there are no known compatibility issues.

Dependencies

FNN 1.1.3 fields 9.8-3

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) .

Installation

Maven

This package can be included as a dependency from a Java or Scala project by including the following your project's pom.xml file. Read more about embedding Renjin in JVM-based projects.

<dependencies>
  <dependency>
    <groupId>org.renjin.cran</groupId>
    <artifactId>gainML</artifactId>
    <version>0.1.0-b1</version>
  </dependency>
</dependencies>
<repositories>
  <repository>
    <id>bedatadriven</id>
    <name>bedatadriven public repo</name>
    <url>https://nexus.bedatadriven.com/content/groups/public/</url>
  </repository>
</repositories>

View build log

Renjin CLI

If you're using Renjin from the command line, you load this library by invoking:

library('org.renjin.cran:gainML')

Test Results

This package was last tested against Renjin 0.9.2726 on Jul 13, 2019.

Source

R

View GitHub Mirror

Release History