Remaining Useful Life Prediction of Turbofan Engine in Varied Operational Conditions Considering Change Point: A Novel Deep Learning Approach with Optimum Features
In the era of Internet of Things (IoT), remaining useful life (RUL) prediction of turbofan engines is crucial. Various deep learning (DL) techniques proposed recently to predict RUL for such systems have remained silent on the effect of environmental changes on machine reliability. This paper aims (...
Saved in:
Main Authors: | Subrata Rath, Deepjyoti Saha, Subhashis Chatterjee, Ashis Kumar Chakraborty |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2024-12-01
|
Series: | Mathematics |
Subjects: | |
Online Access: | https://www.mdpi.com/2227-7390/13/1/130 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Research on Chinese predicate head recognition based on Highway-BiLSTM network
by: Ruizhang HUANG, et al.
Published: (2021-01-01) -
An Efficient and Hybrid Deep Learning-Driven Model to Enhance Security and Performance of Healthcare Internet of Things
by: Muhammad Babar, et al.
Published: (2025-01-01) -
A Semantic-Context Embedding Enhanced Attention Fusion BiLSTM: Unraveling Multilingual Sentiments in Product Reviews with Advanced Deep Learning
by: Amit Purohit, et al.
Published: (2024-01-01) -
Forecasting Ionospheric foF2 Using Bidirectional LSTM and Attention Mechanism
by: Jun Tang, et al.
Published: (2023-11-01) -
Neural network and Markov based combination prediction algorithm of video popularity
by: Xuesen MA, et al.
Published: (2021-08-01)