Wind Prediction Based on General Regression Neural Network
Chun‐Yao Lee, Yan-Lou He · 2012
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.