Anomaly detection solutions: The dynamic loss approach in VAE for manufacturing and IoT environment
Anomaly detection is critical for enhancing operational efficiency, safety, and maintenance in industrial applications, particularly in the era of Industry 4.0 and IoT. While traditional anomaly detection approaches face limitations such as scalability issues, high false alarm rates, and reliance on...
Saved in:
Main Authors: | Praveen Vijai, Bagavathi Sivakumar P |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2025-03-01
|
Series: | Results in Engineering |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025003627 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Explanatory LSTM-AE-Based Anomaly Detection for Time Series Data in Marine Transportation
by: Zhan Wang, et al.
Published: (2025-01-01) -
Unlocking Potential Score Insights of Sentimental Analysis with a Deep Learning Revolutionizes
by: Ibrahim R. Alzahrani
Published: (2025-02-01) -
Suggesting a Novel Hybrid Approach for Predicting Solar Irradiance in the Qinghai Province of China
by: Baran Yılmaz, et al.
Published: (2024-09-01) -
Photovoltaic-Power Prediction Model Based on Quantum Long Short-Term Memory Network
by: PAN Dong, YANG Xin, SHI Tiancheng, FANG Yuan, WANG Xuli, DOU Menghan
Published: (2025-01-01) -
Photovoltaic solar energy prediction using the seasonal-trend decomposition layer and ASOA optimized LSTM neural network model
by: Venkatachalam Mohanasundaram, et al.
Published: (2025-02-01)