Background Maintaining machines effectively continues to be a challenge for industrial
organisations, which frequently employ reactive or premeditated methods. Recent research …

This paper introduces and formalizes the concept of T-shape data, which arises in several
engineering and natural contexts, where the initial data are richer and cover a wider range …

Satellite in-orbit temperature prediction is essential in satellite reliability evaluation and
health management. However, the non-stationary property of the time-series temperature …

It is critical to accurately predict the remaining useful life (RUL) of rolling bearings to avoid
severe accidents and financial losses in the industry. Nevertheless, accurately determining …

Today, a significant content of the system on chips (SOCs) is dedicated to static random
access memory (SRAM) cells. Due to the stress during SRAM operation, MOSFET aging is …

Remaining useful life (RUL) prediction and fault diagnosis are two major prognostic
activities in industrial field. Existing works focus on RUL prediction without considering the …

Maintaining equipment and machinery in industries is imperative for maximizing operational
efficiency and prolonging their lifespan. The adoption of predictive maintenance enhances …

An algorithm based on EMD-LSTM (Empirical Mode Decision–Long Short Term Memory) is
proposed for predicting short time series with uncertainty, rapid changes, and no following …

Currently bitcoin is considered an investment tools, the value of bitcoin itself is unstable so it
is difficult to predict which can cause losses for bitcoin traders. Some previous research …

Deep learning (DL) has proven highly effective for predicting the remaining useful life (RUL)
of systems. However, many DL-based prognostic models typically produce deterministic …