He Liu

TL;DR: The largest Lyapunov index is used to reveal the maximum prediction range of RUL, and the prediction results of the comparative case show that the prediction performance of the GC degradation model is better than Brownianmotion, fractional Brownian motion, and long short-term memory neural network.

TL;DR: In this article, the authors used the fractional Levy stable motion (fLsm) to establish a finite iterative forecasting model with Long Range Dependent (LRD) characteristics, which considers the influence of current and past trends in stochastic sequences on future trends.

TL;DR: In this article, the authors proposed a new heavy tail degradation model, in which the fractional L e − vy stable motion is used as a diffusion term to establish a degradation model with power rate drift.

TL;DR: In this paper, a new long-range-dependent degradation model is described based on the generalized Cauchy (GC) process, which describes local irregularities and global correlation characteristics of the data time sequence by the Hurst parameter $H$ and fractal dimension $D$.

TL;DR: In this article, a generalized Cauchy (GC) process is used for simulation and forecasting of wind speed, where the fractal dimension D and the Hurst parameter H can be combined arbitrarily to describe the local irregularity and global correlation of the wind speed.