由于股票预测是不确定、非线性、非平稳的时间序列问题，传统的方法往往难以取得满意的预测效果。
Because stock forecasting is a uncertain, nonlinear and nonstationary time series problem, it is difficult to achieve a satisfying prediction effect by traditional methods.
茧丝纤度曲线的预测研究茧丝纤度曲线可视为是长度有限且随机变动的非平稳时间序列。
Size curves of cocoon filaments can be regarded as non-stationary time series with finite length varying at random.
然而石油期货价格具有时间序列数据的典型特点，即非线性和非平稳性，这给价格的预测带来了极大的困难。
However, the oil futures prices involve the typical characteristics of time series data, nonlinearity and nonstationarity, which brings insuperable difficulties in the price forecasts.
针对故障率时间序列的非线性与非平稳特性，提出一种基于支持向量经验模态分解(SVEMD)的预测方法。
A prediction method based on support vector empirical mode decomposition (SVEMD) is proposed to deal with the non-linearity and non-stationarity of failure rate data.
将小波分析理论、灰色预测理论和时间序列预测法组合进行需水量的预测，为原始非平稳时间序列的预测应用拓展了空间。
The space of prediction and application of non-stationary time series were expanded through the combined model of wavelet analysis, gray and time series prediction methods.
先将非平稳时间序列进行经验模式分解，再对各个分量分别建模，最后将各分量预测结果进行组合。
Empirical mode decomposition is used for pre-processing. Decompose time series, then make models separately and combine all the values.
先将非平稳时间序列进行经验模式分解，再对各个分量分别建模，最后将各分量预测结果进行组合。
Empirical mode decomposition is used for pre-processing. Decompose time series, then make models separately and combine all the values.
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