Title :
Wind Prediction Based on General Regression Neural Network
Author :
Lee, Chun-Yao ; He, Yan-Lou
Author_Institution :
Dept. of Electr. Eng., Chung Yuan Christian Univ., Chungli, Taiwan
Abstract :
This study adopts the general regression neural network (GRNN) to predict wind speeds. The training data sets are the real wind speeds obtained from CKS International Airport. The 5 days (120 hours) of the three year from 2006 to 2008 is selected as an example to appraise the prediction performance by using GRNN. Comparing to the traditional linear time-series-based model, the superiority of GRNN method to wind prediction can be valid.
Keywords :
neural nets; power engineering computing; regression analysis; time series; wind power; CKS International Airport; GRNN; general regression neural network; linear time-series-based model; wind speed prediction; Atmospheric modeling; Data models; Neural networks; Predictive models; Training; Vectors; Wind speed; linear time-series-based model; neural network; wind speed predicted;
Conference_Titel :
Intelligent System Design and Engineering Application (ISDEA), 2012 Second International Conference on
Conference_Location :
Sanya, Hainan
Print_ISBN :
978-1-4577-2120-5
DOI :
10.1109/ISdea.2012.520
