ML Anthology

Copula Graphical Models for Wind Resource Estimation

Kalyan Veeramachaneni, Alfredo Cuesta-Infante, Una-May O'Reilly
IJCAI 2015 pp. 2646-2654
/ijcai/2015/veeramachaneni2015ijcai-copula/

Abstract

We develop multivariate copulas for modeling multiple joint distributions of wind speeds at a wind farm site and neighboring wind source. A ndimensional Gaussian copula and multiple copula graphical models enhance the quality of the prediction site distribution. The models, in comparison to multiple regression, achieve higher accuracy and lower cost because they require less sensing data.

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Cite

Text

Veeramachaneni et al. "Copula Graphical Models for Wind Resource Estimation." International Joint Conference on Artificial Intelligence, 2015.

Markdown

[Veeramachaneni et al. "Copula Graphical Models for Wind Resource Estimation." International Joint Conference on Artificial Intelligence, 2015.](https://mlanthology.org/ijcai/2015/veeramachaneni2015ijcai-copula/)

BibTeX

@inproceedings{veeramachaneni2015ijcai-copula,
  title     = {{Copula Graphical Models for Wind Resource Estimation}},
  author    = {Veeramachaneni, Kalyan and Cuesta-Infante, Alfredo and O'Reilly, Una-May},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2015},
  pages     = {2646-2654},
  url       = {https://mlanthology.org/ijcai/2015/veeramachaneni2015ijcai-copula/}
}