Výsledky vyhľadávania - "long short-term memory (LSTM) autoencoder"

Development of anomaly detector for motor bearing condition monitoring using Fast Fourier Transform (FFT) and Long Short Term Memory (LSTM)-Autoencoder Autor Sulaimon, A. Bashir, Oladebo, Suliat Jimoh, Idris, Mohammed Kolo, Enesi, Femi Aminu

“… This paper proposes a novel approach for anomaly detection using Fast Fourier Transform (FFT) and Long Short-Term Memory…”
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Degradation-Aware Remaining Useful Life Prediction With LSTM Autoencoder Autor Wu, Ji-Yan, Wu, Min, Chen, Zhenghua, Li, Xiao-Li, Yan, Ruqiang

“… To improve the RUL prediction accuracy with various degradation trends, this article proposes an algorithm dubbed degradation-aware long short-term memory (LSTM) autoencoder (AE) (DELTA…”
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Real-Time Deep Anomaly Detection Framework for Multivariate Time-Series Data in Industrial IoT Autor Nizam, Hussain, Zafar, Samra, Lv, Zefeng, Wang, Fan, Hu, Xiaopeng

“…The data produced by millions of connected devices and smart sensors in the Industrial Internet of Things (IIoT) is highly dynamic, large-scale, heterogeneous,…”
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Data-Driven Detection of Stealth Cyber-Attacks in DC Microgrids Autor Takiddin, Abdulrahman, Rath, Suman, Ismail, Muhammad, Sahoo, Subham

“…Cyber-physical systems such as microgrids contain numerous attack surfaces in communication links, sensors, and actuators forms. Manipulating the communication…”
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GCN-Based LSTM Autoencoder with Self-Attention for Bearing Fault Diagnosis Autor Lee, Daehee, Choo, Hyunseung, Jeong, Jongpil

“…The manufacturing industry has been operating within a constantly evolving technological environment, underscoring the importance of maintaining the efficiency…”
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Enhancing collision avoidance in mixed waterborne transport: Human-mimic navigation and decision-making by autonomous vessels Autor Song, Rongxin, Papadimitriou, Eleonora, Negenborn, Rudy R., van Gelder, Pieter

“… We first model human-controlled ship navigational preferences using a Long Short-Term Memory (LSTM…”
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LSTM-Autoencoder Network for the Detection of Seismic Electric Signals Autor Xue, Jiyan, Huang, Qinghua, Wu, Sihong, Nagao, Toshiyasu

“…Seismic electric signals (SESs) are essential short-term precursors of earthquakes. Accurate and efficient detection of SESs is significant to short-term…”
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Degradation State Assessment of IGBT Module Based on Interpretable LSTM-AE Modeling Under Changing Working Conditions Autor Xie, Feng, Xiao, Fei, Tang, Xin, Luo, Yifei, Shen, Haolan, Shi, Zenan

“…Researches indicate that the insulated gate bipolar transistor (IGBT) module is a crucial yet failure-prone constituent of power electronic devices. As a…”
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Long Short-Term Memory Auto-Encoder-Based Position Prediction Model for Fixed-Wing UAV During Communication Failure Autor Kant, Ravi, Saini, Poonam, Kumari, Julee

“…Unmanned aerial vehicles (UAV's) safe flight is one of the most important tasks of ground control stations (GCS). However, sometimes due to communication…”
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A Wearable LSTM Autoencoder-based ECG Detection System to Predict Myocardial Infarction Autor I., Fernando I.A.S., S., Induwara M., N., Isuranga T.H., D., Chithrani P.A., D., Wickramathilaka D.A., A., Rajapaksha R.M.D.H., L., Wijewardhana U., B., Balagalla U.

“…: Long Short-Term Memory (LSTM) autoencoder and a mobile application for displaying the final result, the condition of the patient…”
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Machine Learning Methods for Small Data Challenges in Molecular Science Autor Dou, Bozheng, Zhu, Zailiang, Merkurjev, Ekaterina, Ke, Lu, Chen, Long, Jiang, Jian, Zhu, Yueying, Liu, Jie, Zhang, Bengong, Wei, Guo-Wei

“…Small data are often used in scientific and engineering research due to the presence of various constraints, such as time, cost, ethics, privacy, security, and…”
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Multitask Air-Quality Prediction Based on LSTM-Autoencoder Model Autor Xu, Xinghan, Yoneda, Minoru

“… In response to this problem, this article proposes a long short-term memory (LSTM) autoencoder multitask learning model to predict <inline-formula> <tex-math notation="LaTeX">{\textrm {PM}}_{2.5} </tex-math></inline-formula…”
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A real-time deep machine learning approach for sudden tool failure prediction and prevention in machining processes Autor Hassan, Mahmoud, Sadek, Ahmad, Attia, Helmi

“… A long short-term memory (LSTM) autoencoder was developed to compress and reconstruct the DWT features…”
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Identifying acute kidney injury subphenotypes using an outcome-driven deep-learning approach Autor Tan, Yongsen, Huang, Jiahui, Zhuang, Jinhu, Huang, Haofan, Jiang, Song, She, Miaowen, Tian, Mu, Liu, Yong, Yu, Xiaxia

“…Acute kidney injury (AKI), a common condition on the intensive-care unit (ICU), is characterized by an abrupt decrease in kidney function within a few hours or…”
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Motion Artifact Removal in Functional Near‐Infrared Spectroscopy Based on Long Short‐Term Memory‐Autoencoder Model Autor Yang, Pan, Wang, Junhong, Wang, Ting, Li, Lihua, Xu, Dongjuan, Xi, Xugang

“… In this paper, we propose a deep learning denoising model based on long short‐term memory (LSTM)‐autoencoder (viz., LSTM‐AE) to reduce motion artifacts…”
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Anomaly detection in groundwater monitoring data using LSTM-Autoencoder neural networks Autor Rezaiezadeh Roukerd, Fatemeh, Rajabi, Mohammad Mahdi

“…Groundwater monitoring data can be prone to errors and biases due to various factors like borehole and equipment malfunctions, or human mistakes. These…”
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Unsupervised anomaly detection with LSTM autoencoders using statistical data-filtering Autor Maleki, Sepehr, Maleki, Sasan, Jennings, Nicholas R.

“… This enables the labelling of the data on the fly. Non-anomalous data is passed to train a deep Long Short-Term Memory (LSTM…”
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Unravelling the Dynamics of Seizure-Like Activity in Neuronal Networks using Machine Learning Autor Mufti, Shatha J, Verma, Shourya, Martinez, Jhon, Gupta, Prerit, Bera, Aniket, Grama, Ananth, Shi, Riyi

“…) pipeline to investigate bicuculline-induced seizure-like activity. Our multistep analysis approach, which consists of using a Long Short-Term Memory (LSTM…”
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Developing health indicators and RUL prognostics for systems with few failure instances and varying operating conditions using a LSTM autoencoder Autor de Pater, Ingeborg, Mitici, Mihaela

“… There are thus very few labelled data samples available. We therefore propose a Long Short-Term Memory (LSTM…”
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Energy-Efficient Anomaly Detection and Chaoticity in Electric Vehicle Driving Behavior Autor Savran, Efe, Karpat, Esin, Karpat, Fatih

“… The anomaly detection performances of hybrid models created with the combination of Long Short-Term Memory (LSTM…”
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