Remaining useful life (RUL) prediction plays a crucial role in bearing maintenance, as it directly affects the safe operation of equipment. This article presents a rolling bearing RUL prediction ...

Sun, Y., Xue, B., Zhang, M. and Yen, G.G. (2019) A Particle Swarm Optimization-Based Flexible Convolutional Autoencoder for Image Classification. IEEE Transactions on Neural Networks and Learning ...

A comprehensive PyTorch-based system for predicting cryptocurrency prices using a state-of-the-art Spatial-Temporal Graph Neural Network (ST-GNN) model. This advanced implementation integrates ...

Multipath signal recognition is crucial to the ability to provide high-precision absolute-position services by the BeiDou Navigation Satellite System (BDS). However, most existing approaches to this ...

In the present study, three types of deep learning techniques, namely, stacked autoencoder (SAE) network, long short term memory (LSTM) network, and convolutional neural network (CNN) are applied to ...

The "Hello World" of image classification is a convolutional neural network (CNN) applied to the MNIST digits dataset. A good way to see where this article is headed is to take a look at the ...

The Data Science Lab Autoencoder Anomaly Detection Using PyTorch Dr. James McCaffrey of Microsoft Research provides full code and step-by-step examples of anomaly detection, used to find items in a ...

Description This package contains Python scripts to build and/or deploy a variational autoencoder (VAE) for chemical data implemented in PyTorch. The encoder is based on a multilayer 1D convolutional ...