同时研究了噪声对关联维数计算结果的影响，并提出用采样迭代奇异值降噪算法对原始数据进行降噪处理。
The influence of noise on the computational precision of correlation dimension is discussed, and iterative singular value decomposition for reducing noise is introduced.
利用关联规则挖掘文献资源间的关联程度，从而产生近邻资源，可以很好的解决稀疏性以及奇异发现问题。
The association rule is used to analyze the relationship between reference resources, without sparsity and odd matching problems.
但用G P算法求关联维数存在抗干扰能力较差、可靠性不稳定、运算量巨大等缺点。先对相空间进行奇异谱分析，进而对原始相空间进行旋转，使其成为正交的等效空间，然后再使用G P算法。
But G-P algorithm which be used to calculate D2 have some shortages, such as being robust against noise, not stable, and needing a big operation.
但用G P算法求关联维数存在抗干扰能力较差、可靠性不稳定、运算量巨大等缺点。先对相空间进行奇异谱分析，进而对原始相空间进行旋转，使其成为正交的等效空间，然后再使用G P算法。
But G-P algorithm which be used to calculate D2 have some shortages, such as being robust against noise, not stable, and needing a big operation.
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