Reliability Evaluation Model of Embedded System Based on Machine Learning Method

Abstract

Embedded system is widely used in all walks of life, and its reliability has become the focus of attention. According to the embedded system reliability evaluation problem, we propose a reliability evaluation model based on machine learning, classification and analysis of the model based on the gradient descent method in machine learning, adaptability of the model itself, which has a strong versatility. The experimental results show that this method has higher accuracy rate and average accuracy of 91.15%. It can provide good support for the reliability evaluation of embedded system.