Implementation of Ensemble Learning Methods in Autoencoder Architecture for Anomaly Detection in Natural Gas Pipeline Operational Data

Pipeline monitoring plays crucial role in ensuring safety and efficiency of natural gas transportation systems. Undetected anomalies may result in severe environmental and financial consequences, emphasizing need for robust monitoring systems. Research implements an ensemble of autoen-coders (EoAE)...

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Bibliographic Details

Published in:	2025 International Conference on Data Science and Its Applications (ICoDSA) pp. 281 - 286
Main Authors:	Azzaka, Muhammad Rivaditya, Firman Ihsan, Aditya, Astuti, Widi
Format:	Conference Proceeding
Language:	English
Published:	IEEE 03.07.2025
Subjects:	anomaly Anomaly detection autoencoder Autoencoders Ensemble learning Monitoring Natural gas Noise reduction pipeline Pipelines Reliability Sensitivity
Online Access:	Get full text
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