基于广义回归神经网络的风预报

2012 Second International Conference on Intelligent System Design and Engineering Application Pub Date : 2012-01-06 DOI:10.1109/ISDEA.2012.520

Chun-Yao Lee, Yan-Lou He

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引用次数: 12

摘要

本研究采用广义回归神经网络(GRNN)进行风速预测。训练数据集为从中港国际机场获得的真实风速。以2006 - 2008年3年的5天(120小时)为例，评价GRNN的预测效果。与传统的基于线性时间序列的模型相比，GRNN方法在风力预测方面的优越性是有效的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Wind Prediction Based on General Regression Neural Network

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.

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来源期刊

2012 Second International Conference on Intelligent System Design and Engineering Application

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