A Temporal Convolutional Network–Bidirectional Long Short-Term Memory (TCN-BiLSTM) Prediction Model for Temporal Faults in Industrial Equipment

A Temporal Convolutional Network–Bidirectional Long Short-Term Memory (TCN-BiLSTM) Prediction Model for Temporal Faults in Industrial Equipment

Traditional algorithms and single predictive models often face challenges such as limited prediction accuracy and insufficient modeling capabilities for complex time-series data in fault prediction tasks. To address these issues, this paper proposes a combined prediction model based on an improved t...

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Bibliographic Details
Main Authors: Jinyin Bai, Wei Zhu, Shuhong Liu, Chenhao Ye, Peng Zheng, Xiangchen Wang
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Applied Sciences
Subjects:
time-series fault
TCN
BiLSTM
fault prediction
hyperparameter optimization
Online Access:https://www.mdpi.com/2076-3417/15/4/1702
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