We present a linearly regressive prediction model for noisy chaotic time series phase space based on variational Bayesian and phase space reconstructive theory.
基于变分贝叶斯及相空间重构理论，提出了含噪混沌时间序列相空间域线性回归预测模型。
Experimental study on ship motion prediction using auto regressive model was carried out.
利用自回归模型对船舶运动进行了预报试验研究。
The results from two cases of model prediction in water environment show better prediction effect and are compared with the project pursuit regressive (PPR) model.
通过水环境中的两个实例进行了预测应用，结果表明，预测效果较好，并与投影寻踪回归模型（PPR）进行了对比。
In order to check the prediction effect, the stepwise regressive equation prediction model was established with the same prediction elements and historical samples.
为了检验其预报效果，根据相同的预报因子和历史样本，建立了相应的逐步回归预报模型。
In order to check the prediction effect, the stepwise regressive equation prediction model was established with the same prediction elements and historical samples.
为了检验其预报效果，根据相同的预报因子和历史样本，建立了相应的逐步回归预报模型。
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