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| 基于广义回归神经网络的时间序列预测研究 | |
| 引用本文： | 冯志鹏,宋希庚,薛冬新,郑爱萍,孙玉明.基于广义回归神经网络的时间序列预测研究[J].振动．测试与诊断,2003,23(2):105-109. |
| 作者姓名： | 冯志鹏 宋希庚 薛冬新 郑爱萍 孙玉明 |
| 作者单位： | 1. 大连理工大学内燃机研究所,大连,116024 2. 锦州石化公司设计院,辽宁锦州,121000 3. 辽宁石油化工学校 辽宁锦州,121000 |
| 基金项目： | 辽宁省教委高校自然科学基金资助项目 (编号 :990 4 2 1 0 93) |
| 摘 要： | 介绍了广义回归神经网络的基本理论,提出了应用BIC准则确定输入神经元数目的方法．将其应用于大型旋转机械振动状态时间序列的单步和多步预测,与传统的采用误差反向传播学习算法的三层前馈感知器网络(BP神经网络)的预测结果进行对比。结果表明,该网络的预测性能优于后者,即使样本数据稀少,也能获得满意的预测结果。 |
| 关 键 词： | 广义回归神经网络 时间序列预测 平滑参数 网络结构 旋转机械 振动状态 |
| 修稿时间： | 2001年12月27 |
General Regression Neural Network Based Prediction of Time Series |
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| Feng Zhipeng,Song Xigeng,Xue Dongxin.General Regression Neural Network Based Prediction of Time Series[J].Journal of Vibration,Measurement & Diagnosis,2003,23(2):105-109. | |
| Authors: | Feng Zhipeng Song Xigeng Xue Dongxin |
| Abstract: | The basics of a general regression neural network(GRNN) is introduced. The BIC method generalized from the Auto Regression model is presented to determine the number of input neurons. The GRNN is applied to the single step and multi step ahead prediction of a time series of the vibration of a rotating machine,and its performance is compared with that of a 3 layer perceptrons network with error back propagation training algorithm(BPNN). The comparison indicates that the GRNN is superior in prediction of a time series to the BPNN,and a satisfactory prediction can be still made by the GRNN even with sparse sample data. |
| Keywords: | prediction time series neural network general regression neural network |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |