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ysosirius
windfarmGA:Genetic Algorithm for Wind Farm Layout Optimization
The genetic algorithm is designed to optimize wind farms of any shape. It requires a predefined amount of turbines, a unified rotor radius and an average wind speed value for each incoming wind direction. A terrain effect model can be included that downloads an 'SRTM' elevation model and loads a Corine Land Cover raster to approximate surface roughness.
Maintained by Sebastian Gatscha. Last updated 2 months ago.
windfarm-layoutoptimizationgenetic-algorithmrenewable-energycpp
29 stars 4.99 score 17 scripts
jeff-hughes
paramtest:Run a Function Iteratively While Varying Parameters
Run simulations or other functions while easily varying parameters from one iteration to the next. Some common use cases would be grid search for machine learning algorithms, running sets of simulations (e.g., estimating statistical power for complex models), or bootstrapping under various conditions. See the 'paramtest' documentation for more information and examples.
Maintained by Jeffrey Hughes. Last updated 7 days ago.
1 stars 4.85 score 47 scripts
techtonique
bcn:Boosted Configuration Networks
Boosted Configuration (neural) Networks for supervised learning.
Maintained by T. Moudiki. Last updated 6 months ago.
machine-learningneural-networksstatistical-learningcpp
5 stars 4.00 score 4 scripts