本文提出一种混沌时间序列预测技术。
This paper presents a method of forecasting chaotic time series.
提出了一种新的用于时间序列预测方法。
因此本文提出基于属性分类的时间序列预测方案。
Then sample time series was chosen which had the same property with predicting object.
时间序列预测模型在生产性行业里具有广泛的作用。
Time serial predicting model can act well in many industries.
时间序列的预测在经济和工程领域具有十分重要的意义。
The prediction of time series is very important in the economic and engineering fields.
本文讨论如何应用时间序列建模预测电力负荷。
This paper discusses the prediction of power load by time series modelling.
研究还表明，该方法在水文月径流时间序列的预测中同样有效。
On runoff time series forecasting, this method shows a good result, too. 3.
灰色系统预测法对时间序列的预测有较高的精度。
The grey system has a high precision for the time series prediction.
最新的原始的时间序列的下一个样本由另一个神经网络预测。
Last, the next sample of the original time series was predicted by another neural network.
本文的第六章讨论混沌时间序列的预测问题。
In chapter 6, we discuss the predict method of chaotic time series.
第二、对混沌时间序列进行预测。
论文的研究目的是为了对时间序列的发展趋势进行预测。
The destination of this study is to predict the trend of time series.
第一步使用时间序列模型进行预测研究。
运用时间序列法对未来几年的产量进行预测。
Finally, we use time series method to predict the output of the next few years.
然后将混沌时间序列的相关理论引入到风速、风功率预测中。
Then the chaotic time series theory is introduced into the wind speed prediction.
然后将混沌时间序列的相关理论引入到风速、风功率预测中。
Then the chaotic time series theory is introduced into the wind speed prediction.
应用推荐