The support vector machine (SVM), which has long-term prediction period, strong generalization ability and high prediction accuracy, provides an efficient new way for life prediction of accelerated degradation testing (ADT). In this paper, an intelligent prognostic model for step-stress ADT (SSADT) based on SVM is proposed. The SSADT data of superluminescent diode (SLD) is utilized to validate the proposed method.
