Search Results - RNN-LSTM autoencoder
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Data-feature-driven nonlinear process monitoring based on joint deep learning models with dual-scale
ISSN: 0020-0255, 1872-6291Published: Elsevier Inc 01.04.2022Published in Information sciences (01.04.2022)“…The interactions among the gauged data in most exiting real-life cases are correlative inevitably given the complicated behavior of process systems, that is…”
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Variational Autoencoders for Anomaly Detection and Transfer Knowledge in Electricity and District Heating Consumption
ISSN: 0093-9994, 1939-9367, 1939-9367Published: New York IEEE 01.09.2024Published in IEEE transactions on industry applications (01.09.2024)“…Real-time anomaly detection in energy consumption supports identifying issues related to technical and user behaviour that result in significant energy waste…”
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Autoencoders for Anomaly Detection in Electricity and District Heating Consumption: A Case Study in School Buildings in Sweden
ISBN: 9798350347449, 9798350347432Published: IEEE 06.06.2023Published in 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) (06.06.2023)“… We evaluated the performance of three proposed models, stacked RNN-LSTM autoencoder, CNN-LSTM autoencoder, and LSTM Variational Autoencoder (VAE…”
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Conference Proceeding -
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Short-Term Fault Prediction of Wind Turbines Based on Integrated RNN-LSTM
ISSN: 2169-3536, 2169-3536Published: Piscataway IEEE 2024Published in IEEE access (2024)“…This paper presents a data-driven approach to short-term wind turbine fault prediction and condition monitoring based on a hybrid architecture of recurrent…”
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5
RNN-based Method for Fault Diagnosis of Grinding System
Published: IEEE 01.07.2017Published in 2017 IEEE 7th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER) (01.07.2017)“… Aiming at the above problems, a RNN-LSTM based deep learning method is proposed in the paper, which realizes the intelligent fault diagnosis of grinding system…”
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Conference Proceeding -
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A Novel Deep Learning Framework Based RNN-SAE for Fault Detection of Electrical Gas Generator
ISSN: 2169-3536, 2169-3536Published: Piscataway IEEE 2021Published in IEEE access (2021)“…The electrical generator is the key part of the electrical generation system for the oil and gas industry, and it is easy to fail, which disturbs the…”
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A Multi-Step Comparative Framework for Anomaly Detection in IoT Data Streams
Published: IEEE 16.04.2025Published in 2025 International Conference on New Trends in Computing Sciences (ICTCS) (16.04.2025)“…: RNN-LSTM, autoencoder neural networks (ANN), and Gradient Boosting (GBoosting). Experiments on the IoTID20 dataset shows that GBoosting consistently delivers…”
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Towards Efficient Predictive Maintenance: Evaluating LSTM Autoencoders, CNNs, and RNNs for Industrial Machinery Anomaly Detection
Published: IEEE 11.05.2025Published in 2025 IEEE Energy Conversion Congress & Exposition Asia (ECCE-Asia) (11.05.2025)“…This work investigates a variety of anomaly detection models in the scope of machinery faults including the 1D CNN, LSTM Autoencoders, RNN architectures…”
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Comparative analysis of speaker identification performance using deep learning, machine learning, and novel subspace classifiers with multiple feature extraction techniques
ISSN: 1051-2004Published: Elsevier Inc 01.01.2025Published in Digital signal processing (01.01.2025)“…•For the first time in the literature, speaker identification was achieved using HCF.•Many hybrid algorithms were tested in the study.•Six different feature…”
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10
Zero-Day Malware Detection Using Autoencoder and Hybrid Deep Learning Model
Published: IEEE 16.05.2025Published in 2025 International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC) (16.05.2025)“… Known malware is classified using an RNN-LSTM model, while an Autoencoder detects unfamiliar threats by learning typical benign behavior and flagging anomalies…”
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11
Generative machine learning for de novo drug discovery: A systematic review
ISSN: 0010-4825, 1879-0534, 1879-0534Published: United States Elsevier Ltd 01.06.2022Published in Computers in biology and medicine (01.06.2022)“…Recent research on artificial intelligence indicates that machine learning algorithms can auto-generate novel drug-like molecules. Generative models have…”
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Predicting the Risk of Depression Based on ECG Using RNN
ISSN: 1687-5265, 1687-5273, 1687-5273Published: United States Hindawi 2021Published in Computational intelligence and neuroscience (2021)“…). This proposed model uses a Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) autoencoder to predict normal, abnormal, and PVC heartbeats…”
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A Systematic Review of Deep Learning Methodologies Used in the Drug Discovery Process with Emphasis on In Vivo Validation
ISSN: 1422-0067, 1661-6596, 1422-0067Published: Switzerland MDPI AG 31.03.2023Published in International journal of molecular sciences (31.03.2023)“…The discovery and development of new drugs are extremely long and costly processes. Recent progress in artificial intelligence has made a positive impact on…”
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14
Comparative study of deep learning models for Parkinson’s disease detection
ISSN: 2772-4859, 2772-4859Published: Elsevier B.V 01.06.2025Published in BenchCouncil Transactions on Benchmarks, Standards and Evaluations (01.06.2025)“…•Models evaluated include: MLP, RNN-LSTM, GRU,GAN and Autoencoder using voice data.•Performance assessed using standard metrics such as accuracy, precision, recall, and F1-score…”
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15
Deep Learning Paradigms for Multi-Dimensional Big Data Analytics: A Critical Assessment
ISSN: 2468-4376, 2468-4376Published: 18.04.2025Published in Journal of information systems engineering & management (18.04.2025)“…), and autoencoders in transaction fraud detection over the Kaggle “Credit Card Fraud Detection” dataset that contains more than 284000 transactions…”
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AI for Threat Detection & Response
ISSN: 2582-3930, 2582-3930Published: 06.09.2025Published in INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT (06.09.2025)“… (CNN, RNN/LSTM, Autoencoders…”
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An improved long short-term memory with denoising autoencoder for solving text classification problems
ISSN: 0254-7821Published: Mehran University of Engineering and Technology 01.07.2024Published in Mehran University research journal of engineering and technology (01.07.2024)“…, weak, and chaotic components. This paper proposes a new model referred to as DAE-LSTM for reducing data dimension through the use of a denoising autoencoder…”
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Intrusion Detection System in Wireless Sensor Networks using Modified Recurrent Neural Network with Long Short-Term Memory
Published: IEEE 23.02.2024Published in 2024 International Conference on Integrated Circuits and Communication Systems (ICICACS) (23.02.2024)“… This paper introduces a novel approach: a modified Recurrent Neural Network with Long Short-Term Memory (RNN-LSTM…”
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Deep Learning-Based Autonomous Anomaly Detection for Security in SDN-IoT Networks
ISSN: 2644-125X, 2644-125XPublished: New York IEEE 2025Published in IEEE open journal of the Communications Society (2025)“…Converging Software-Defined Networking (SDN) and the Internet of Things (IoT) has directed innovative network architectures and applications. However, this…”
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A Predictive Approach For Assessing Medication Responsiveness in Breast Cancer Through Analysis of Gene Data
Published: IEEE 13.02.2025Published in 2025 International Conference on Intelligent Control, Computing and Communications (IC3) (13.02.2025)“…Breast cancer remains one of the leading causes of cancer-related deaths worldwide, with treatment responses varying wildly among patients. The inability to…”
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