The drastic reduction in the geometric dimension leads to great simplification in mathematical analysis.
几何维数的急剧减少导致数字分析的极大简化。
A mapping-based dimension-reduction algorithm for probability density evolution analysis of stochastic structural responses is proposed.
提出了随机结构响应密度演化分析的映射降维算法。
Singular Value Decomposition (SVD) is a dimension reduction method, and Symbolic data Analysis (SDA) is a new analytical approach to processing mass data.
奇异值分解(SVD)是一种对数据进行降维处理的方法，符号数据分析(SDA)是一种处理海量数据的全新数据分析思路。
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