A Neural Network Based Approach for Reliability Analysis of Software-Intensive Equipment

Software-Intensive Equipment is the system which includes software and hardware. In this paper, we analyze the characteristics of software-intensive equipment and propose a non-parametric system reliability model to study the failure data with time series technique. The model uses fuzzy neural network and a wavelet function as the membership function to adjust the shape on line so that the model has better learning and adaptive ability. Experimental results demonstrate that the predictability of the proposed model is acceptable, we expect the model feasible.