Wind Prediction Based on General Regression Neural Network

摘要：

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.

关键词： neural network linear time-series-based model wind speed predicted.

作者: Chun-Yao Lee Yan-Lou He

作者单位: Department of Electrical Engineering, Chung Yuan Christian University, Chung Li City, Taiwan

会议类型: 国际会议

会议名称: 2012 International Conference on Intelligent System Design and Engineering Applications(2012年智能系统设计与工程应用国际会议 ISDEA 2012)

会议地点: 三亚

会议语种:英文

页码: 617-620

在线出版日期: 2012-01-06（万方平台首次上网日期，不代表论文的发表时间）