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

fYear

2012

Firstpage

617

Lastpage

620

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/ISdea.2012.520

Filename

6173282

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1594598