In this paper the description of the ship motion with ar model, the selection of the order of the ar model and the construction of the K steps advanced adaptive predictor are discussed.
本文讨论了船舶在不规则海浪中运动的AR模型描述方法和AR模型阶的选择，并用自适应预报的方法提出了超前k步的自适应预报器。
Furthermore, in order to solve the model selection problems of unsupervised image segmentation, the sum of squared error criterion with penalty term is proposed.
而且，针对无监督图像分割的模型选择问题提出了带惩罚项的误差平方和阶次判定准则。
In the feature selection stage, the computing approximate gains in parallel is adopted in order to solve the computational expensiveness of the model and system spending.
在特征选择阶段，采用计算近似增益的平行算法，解决模型计算量过大和系统开销问题。
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