Search Results - "TCN–Autoencoder"

Anomaly Detection of Gas Pipeline Operational Data Using TCN-Autoencoder and LSTM-Autoencoder Models

Authors: Anak Agung Gde Pradnyana Aditya Firman Ihsan null Hasmawati

Source: 2025 International Conference on Data Science and Its Applications (ICoDSA). :1347-1352

AE-TCN: Autoencoder-Driven Temporal Convolutional Networks for Secure and Efficient Cold Chain Monitoring

Authors: EZIAMA, ELVIN Solomon Goldman, Olumba Gerald, Ibe Okwe et al.

AE-TCN: Autoencoder-Driven Temporal Convolutional Networks for Secure and Efficient Cold Chain Monitoring

Authors: Eziama, Elvin Ugonna Olumba, Solomon Goldman Okwe, Gerald Ibe et al.

Process data based estimation of tool wear on punching machines using TCN-Autoencoder from raw time-series information

Authors: Satoshi Tamura Shota Asahi Mathias Liewald et al.

Source: IOP Conference Series: Materials Science and Engineering. 1157:012078

Subject Terms: 0209 industrial biotechnology, 0203 mechanical engineering, 02 engineering and technology

Access URL: https://ui.adsabs.harvard.edu/abs/2021MS&E.1157a2078A/abstract

Multi-output TCN autoencoder for long-term pollution forecasting for multiple sites

Authors: Korra Sathya Babu Santos Kumar Das K. Krishna Rani Samal et al.

Source: Urban Climate. 39:100943

Subject Terms: 13. Climate action, 11. Sustainability, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 6. Clean water, 3. Good health

Access URL: https://www.sciencedirect.com/science/article/pii/S2212095521001735

Advancements in Gas Turbine Fault Detection: A Machine Learning Approach Based on the Temporal Convolutional Network–Autoencoder Model

Authors: Al-Tekreeti Watban Khalid Fahmi Kazem Reza Kashyzadeh Siamak Ghorbani

Source: Applied Sciences, Vol 14, Iss 11, p 4551 (2024)

Subject Terms: fault diagnosis, TCN–Autoencoder, predictive maintenance, power plant, gas turbine, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999

Relation: https://www.mdpi.com/2076-3417/14/11/4551; https://doaj.org/toc/2076-3417; https://doaj.org/article/b6dea9cac87741288d1e56289b9142b6

Availability: https://doi.org/10.3390/app14114551
https://doaj.org/article/b6dea9cac87741288d1e56289b9142b6

Multi-output TCN autoencoder for long-term pollution forecasting for multiple sites.

Authors: Samal, K. Krishna Rani Panda, Ankit Kumar Babu, Korra Sathya et al.

Source: Urban Climate. Sep2021, Vol. 39, pN.PAG-N.PAG. 1p.

Advancements in Gas Turbine Fault Detection: A Machine Learning Approach Based on the Temporal Convolutional Network–Autoencoder Model.

Authors: Fahmi, Al-Tekreeti Watban Khalid Reza Kashyzadeh, Kazem Ghorbani, Siamak

Source: Applied Sciences (2076-3417); Jun2024, Vol. 14 Issue 11, p4551, 17p

Subject Terms: GAS turbines, STANDARD deviations, FAULT diagnosis

Geographic Terms: KIRKUK (Iraq)

Integrating Prior Knowledge Using Transformer for Gene Regulatory Network Inference.

Authors: Weng, Guangzheng Martin, Patrick Kim, Hyobin et al.

Source: Advanced Science; 1/20/2025, Vol. 12 Issue 3, p1-12, 12p

Subject Terms: LANGUAGE models, GENE regulatory networks, REGULATOR genes, AUTOENCODERS, TRANSFORMER models

Dynamic Surface Deformation Prediction in Urban Shield Tunneling Based on Hybrid Machine Learning Method.

Authors: Chen, Shengzhao Wang, Yuan Huang, Jingqi et al.

Source: Transportation Infrastructure Geotechnology; Oct2025, Vol. 12 Issue 7, p1-28, 28p

A novel similarity-based remaining useful life prediction method under multiple failure modes with variable sensors.

Authors: Xie, Kaixuan Zhang, Qiang Yang, Peixuan et al.

Source: Measurement (02632241). Jan2026:Part C, Vol. 258, pN.PAG-N.PAG. 1p.

Subject Terms: *REMAINING useful life, *FAILURE mode & effects analysis, *TRAJECTORY measurements, *MACHINE learning

An Improved TCN-BiGRU Architecture with Dual Attention Mechanisms for Spatiotemporal Simulation Systems: Application to Air Pollution Prediction.

Authors: Mao, Xinyi Liu, Gen Qin, Yinshuang et al.

Source: Applied Sciences (2076-3417); Sep2025, Vol. 15 Issue 17, p9274, 25p

Subject Terms: AIR pollution, PREDICTION models, FEATURE extraction, SPATIOTEMPORAL processes, ATTENTION, DEEP learning

PSCNet: Long sequence time-series forecasting for photovoltaic power via period selection and cross-variable attention: PSCNet: Long sequence time-series forecasting for photovoltaic power...: H. Tan et al.

Authors: Tan, Hao Qin, Jinghui Li, Zizheng et al.

Source: Applied Intelligence; May2025, Vol. 55 Issue 7, p1-17, 17p

A Mold Damage Monitoring Algorithm for Power Metallurgy Molding Machines Using Bidirectional Long Short-Term Memory on an Internet of Things Platform †.

Authors: Lin, Hao-Pu Chen, Yuan-Chieh Han, Chin-Chuan et al.

Source: Sensors (14248220); Apr2025, Vol. 25 Issue 7, p2143, 23p

Subject Terms: LONG short-term memory, DEEP learning, INTERNET of things, METALLURGY, POWDER metallurgy

AI-Driven Predictive Maintenance in Mining: A Systematic Literature Review on Fault Detection, Digital Twins, and Intelligent Asset Management.

Authors: Rojas, Luis Peña, Álvaro Garcia, José

Source: Applied Sciences (2076-3417); Mar2025, Vol. 15 Issue 6, p3337, 36p

Subject Terms: DIGITAL twin, DETECTION algorithms, MACHINE learning, REINFORCEMENT learning, CONVEYOR belts

Lean Data – Anwendungsspezifische Reduktion großer Datenmengen im Produktionsumfeld.

Alternate Title: Lean Data – Application-specific Reduction of Large Amounts of Data in the Production Environment. (English)

Authors: Baucks, Marina Mau, Marcus Ruppelt, Peter et al.

Source: ZWF Zeitschrift fur Wirtschaftlichen Fabrikbetrieb; 2025 Supplement 1, Vol. 120, p152-158, 7p

DHGAR: Multi-Variable-Driven Wind Power Prediction Model Based on Dynamic Heterogeneous Graph Attention Recurrent Network.

Authors: Xu, Mingrui Zhu, Ruohan Yu, Chengming et al.

Source: Applied Sciences (2076-3417); Feb2025, Vol. 15 Issue 4, p1862, 21p

Subject Terms: WIND power, WIND forecasting, DEEP learning, POWER series, FARM management

Time-to-Fault Prediction Framework for Automated Manufacturing in Humanoid Robotics Using Deep Learning.

Authors: Ali, Amir R. Kamal, Hossam

Source: Technologies (2227-7080); Feb2025, Vol. 13 Issue 2, p42, 37p

Subject Terms: LONG short-term memory, WHISPERING gallery modes, INDUSTRIAL robots, STANDARD deviations, HUMANOID robots, DEEP learning

Improving Short-Term Photovoltaic Power Generation Forecasting with a Bidirectional Temporal Convolutional Network Enhanced by Temporal Bottlenecks and Attention Mechanisms.

Authors: Gan, Jianhong Lin, Xi Chen, Tinghui et al.

Source: Electronics (2079-9292); Jan2025, Vol. 14 Issue 2, p214, 23p

Subject Terms: PHOTOVOLTAIC power generation, SMART power grids, STANDARD deviations, METEOROLOGICAL stations, FEATURE extraction

Deep Learning for Time Series Anomaly Detection: A Survey.

Authors: Zamanzadeh Darban, Zahra Webb, Geoffrey I. Pan, Shirui et al.

Source: ACM Computing Surveys; Jan2025, Vol. 57 Issue 1, p1-42, 42p

Subject Terms: ARTIFICIAL neural networks, ARTIFICIAL intelligence, REINFORCEMENT learning, CONVOLUTIONAL neural networks, GRAPH neural networks, DEEP learning, SUPERVISED learning