@misc{d1ce278a61b94544a9bccadcb5b5ca16,
title = "Revealing the Impact of Climate Variability on the Wind Resource Using Data Mining Techniques (Poster)",
abstract = "A data mining technique called 'k-means clustering' can be used to group winds at the NWTC into 4 major clusters. The frequency of some winds in the clusters is correlated with regional pressure gradients and climate indices. The technique could also be applied to wind resource assessment and selecting scenarios for flow modeling.",
keywords = "climate variability, data analysis, data mining, measurements, wind resources",
author = "NREL",
year = "2011",
language = "American English",
series = "Presented at the AGU Fall Meeting 2011, 5-9 December 2011, San Francisco, California",
type = "Other",
}