The traditional deep learning-based bearing fault diagnosis approaches assume that the
training and test data follow the same distribution. This assumption, however, is not always …

Battery degradation, caused by multiple coupled degradation mechanisms, severely affects
the safety and sustainability of a battery management system (BMS). The battery state of …

Generative adversarial network (GAN) is an overwhelming yet promising method to address
the data imbalance problem. However, most existing GANs that are usually inspired by …

In this paper, a lightweight printed circuit board (PCB) defects detection model (light-PDD) is
proposed, which mainly concentrates on overcoming the deficiencies of redundant …

Lower limb motor imagery (MI) classification is a challenging research topic in the area of
brain-computer interfaces (BCIs), and entails numerous signal channels to provide sufficient …

In this paper, hybrid models of Kalman filter and neural network for state estimation are
reviewed of their corresponding academic achievements, the creation of which is a …

In this article, a novel dynamic multiobjective optimization algorithm (DMOA) is proposed
based on a designed hierarchical response system (HRS). Named HRS-DMOA, the …

Cross-domain rotating machinery fault diagnosis has achieved great success recently with
the development of deep transfer learning. However, conventional deep transfer learning …

Cryptocurrency, as a typical application scene of blockchain, has attracted broad interests
from both industrial and academic communities. With its rapid development, the …

The development of Artificial intelligent (AI), deep learning and computer vision technologies
has enabled various new applications and features of intelligent vehicles. However, there …