Secondly, time series trend analysis models in common use are introduced, whose illative process and applicability are also expatiated.
其次，研究了常用的时序数据趋势分析模型，并对它们的推理过程和适用性进行了详细的阐述。
As one of the branches of statistics, time series analysis focuses on the variation characters and trend of discrete ordered data series mainly.
时间序列分析是统计学的分支之一，它的研究对象是离散有序数列的变化特征和变化趋势。
The characteristics of this method are analyzed, and the difficulties in time-series trend analysis are discussed, too.
分析了该方法的特点，指出时间序列趋势分析的难点所在。
Time series analysis is a branch of statistics and widely used in trend prediction.
时间序列分析是统计学的一个重要分支，灰色系统理论是一种动态趋势预测理论。
Theoretic analysis and simulation indicate that the algorithm has better performance for sub-trend searching in temporal and space, and is useful in time series dynamic feature analysis.
理论分析和仿真结果表明，该算法对基于趋势表示的子序列搜索在时间和空间上都具有更优的性能，适用于时间序列的动态特征分析。
Based on random process theory and time series analysis, the paper advanced the adaptive combined smoothing model suiting to seasonality, trend and randomness of water consumption series.
利用随机过程及时间序列分析手段，根据用水量序列季节性、趋势性及随机扰动性的特点，建立了用水量预测的自适应组合平滑模型。
Based on random process theory and time series analysis, the paper advanced the adaptive combined smoothing model suiting to seasonality, trend and randomness of water consumption series.
利用随机过程及时间序列分析手段，根据用水量序列季节性、趋势性及随机扰动性的特点，建立了用水量预测的自适应组合平滑模型。
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