This paper proposes a multi-scale convolutional neural network (CNN) fault diagnosis
model incorporating multiple attention mechanisms (MMCNN) to address the limitations of …

Water supply pipeline leaks have significant impacts on urban areas and daily life. Acoustic
techniques are widely applied in its leak detection, but there is a lack of research on …

Accurate prediction of stock price indices is crucial for market participants to obtain valuable
information and mitigate risks. For more accurate forecasting of stock price indices, this study …

(1) Background: Rolling bearings are important components in mechanical equipment, but
they are also components with a high failure rate. Once a malfunction occurs, it will cause …

The transmission system of a tractor is a crucial component, so it is crucial to promptly
identify and correctly diagnose faults in it. However, due to the limited samples of faults …

This paper introduces a novel parametric-logarithmic-modulus-based activation function
(PLM-AF) designed to significantly enhance the nonlinear expression capabilities of high …

Accurate estimation of forest canopy height is crucial for biomass inversion, carbon storage
assessment, and forestry management. However, deep learning methods are underutilized …

Recently, deep learning has achieved remarkable success in the field of rolling bearing fault
diagnosis. However, two issues cannot be ignored: 1) Deep learning models typically …

Coal-gangue recognition technology plays an important role in the intelligent realization of
integrated working faces and coal quality improvement. However, the existing methods are …

Deep learning has greatly promoted intelligent fault diagnosis for bearings and has led to
the development of many intelligent fault recognition methods based on deep neural …