Predictive strength measures, clustering

Measures for Predictive Strength and Cluster Stability This type of cluster validity focuses on the reliability of clusters, that is, whether cluster structure was predicted by chance (Jiang et al., 2004). In addition, the analysis of predictive power, particularly in biological data analysis, is performed by investigating whether clustering results obtained from one set of experimental condition can be related to the ones from another set (Zhao and Karypis, 2005). 

It is demonstrated that the quasi-static stress-strain cycles of carbon black as well as silica filled rubbers can be well described in the scope of the theoretic model of stress softening and filler-induced hysteresis up to large strain. The obtained microscopic material parameter appear reasonable, providing information on the mean size and distribution width of filler clusters, the tensile strength of filler-filler bonds, and the polymer network chain density. In particular it is shown that the model fulfils a plausibility criterion important for FE applications. Accordingly, any deformation mode can be predicted based solely on uniaxial stress-strain measurements, which can be carried out relatively easily. 

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