Bayesian Neural Network-Based Equipment Operational Trend Prediction Method Using Channel Attention Mechanism
This paper proposes a Bayesian neural network method for predicting equipment operational trends based on a channel attention mechanism. Traditional time series prediction methods have limitations in handling complex data and nonlinear relationships. To enhance prediction accuracy and stability, the...
Main Authors: | Chang Ming-Yu, Tian Le, Maozu Guo |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2024-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10440339/ |
Similar Items
-
Stochastic Control for Bayesian Neural Network Training
by: Ludwig Winkler, et al.
Published: (2022-08-01) -
Probabilistic Attention Map: A Probabilistic Attention Mechanism for Convolutional Neural Networks
by: Yifeng Liu, et al.
Published: (2024-12-01) -
Multi-layered Bayesian Neural Networks for Simulation and Prediction Stress-Strain Time Series
by: Agnieszka Krok
Published: (2015-09-01) -
Bayesian Neural Networks via MCMC: A Python-Based Tutorial
by: Rohitash Chandra, et al.
Published: (2024-01-01) -
Bayesian Sparsification for Deep Neural Networks With Bayesian Model Reduction
by: Dimitrije Markovic, et al.
Published: (2024-01-01)