The optimization of solution is carried out by Iterated Conditional Mode (ICM) method. The initial segmentation label fields is gotten using vector histogram.
最小能量的优化求解用迭代条件模式(ICM)方法，初始分割标记场用矢量直方图法得到。
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.
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.
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。
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