Abstract:

In modeling degradation path with small sampling, the parameter ε of the ε-support vector regression (ε -SVR) is difficult to select. In order to solve this problem, a degradation path modeling method is proposed, on the basis of v-support vector regression (v-SVR). The genetic algorithm (GA) is adopted to optimize parameters of the proposed model. The parameter v has property that it correlates with the number of support vectors and inaccuracy samples, so the range of v’s value can be determined, and v can be also used to control the number of support vectors and inaccuracy samples. The proposed method is applied to fatigue crack growth data, the result indicates that the proposed approach makes the selection of parameters much easier, and gains a higher modeling accuracy than some other methods in the existing literature.