TY - GEN
T1 - Data-driven construction of local models for short-term wind speed prediction
AU - Salas, Joaquín
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - Currently, there is a growing interest in improving the methods applied to the prediction of wind speed. In this document, we propose to combine physically-based decision rules, inferred through a datadriven process, with local regression models. Specifically, quantitative and qualitative analysis of historical records lead us to define a regression structure with a decision tree at the top and local regression models at each leaf. Specifically, our results suggest that this encoding improves the predictions for wind speed for a number of regression schemes, including radial basis neural networks, binary regression trees, support vector regression, adaptive network-based fuzzy inference systems, and bagging trees. A reduction of about 14% in the RMSE is shown for the latter.
AB - Currently, there is a growing interest in improving the methods applied to the prediction of wind speed. In this document, we propose to combine physically-based decision rules, inferred through a datadriven process, with local regression models. Specifically, quantitative and qualitative analysis of historical records lead us to define a regression structure with a decision tree at the top and local regression models at each leaf. Specifically, our results suggest that this encoding improves the predictions for wind speed for a number of regression schemes, including radial basis neural networks, binary regression trees, support vector regression, adaptive network-based fuzzy inference systems, and bagging trees. A reduction of about 14% in the RMSE is shown for the latter.
UR - http://www.scopus.com/inward/record.url?scp=84952642474&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-27101-9_39
DO - 10.1007/978-3-319-27101-9_39
M3 - Contribución a la conferencia
SN - 9783319271002
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 509
EP - 519
BT - Advances in Artificial Intelligence and Its Applications - 14th Mexican International Conference on Artificial Intelligence, MICAI 2015, Proceedings
A2 - Alcántara, Oscar Herrera
A2 - Lagunas, Obdulia Pichardo
A2 - Figueroa, Gustavo Arroyo
PB - Springer Verlag
T2 - 14th Mexican International Conference on Artificial Intelligence, MICAI 2015
Y2 - 25 October 2015 through 31 October 2015
ER -