Results 101 to 110 of about 6,008 (208)

Prediction of small-scale leak flow rate in LOCA situations using bidirectional GRU

It is difficult to detect a small-scale leakage in a nuclear power plant (NPP) quickly and take appropriate action. Delaying these procedures can have adverse effects on NPPs.
Man Gyun Na, Hye Seon Jo, Sang Hyun Lee
core   +1 more source

DAB-GRU: A Dynamic Attention-Based Bidirectional Network for Anomaly Detection of On-Board Time-Series Data in High-Speed Rail

IEEE Access
Time-series data from the Chinese Train Control System (CTCS) exhibits complex multidimensional correlations. Traditional statistical and machine learning methods are limited by local statistical features, failing to capture the underlying associative ...
Wenbing Zhu, Ming Xu, Zhiyang Yu, Yang Wang, Xinjun Gao, Xiaoming Chen   +5 more
doaj   +1 more source

Enhancing Film Genre Classification Using FastText Embeddings, Bidirectional GRU (BiGRU), and Attention Mechanisms

This research aims to enhance the classification of film genres using advanced natural language processing techniques. By integrating FastText embeddings with Bidirectional Gated Recurrent Units (Bi-GRU) and attention mechanisms, the proposed model ...
Muhammad Fairuzabadi, Munandar, Tb Ai
core   +1 more source

GRU-SCANET: unleashing the power of GRU-based sinusoidal capture network for precision-driven named entity recognition

International audienceMotivation Pre-trained Language Models (PLMs) have achieved remarkable performance across various natural language processing tasks.
Larmande, Pierre, Symeonidou, Danai, Happi Happi, Bill, Gates, Pelap, Geraud, Fokou   +3 more
core   +2 more sources

Publication Only

HemaSphere, Volume 10, Issue S1, June 2026.
wiley   +1 more source

Deep learning driven prediction and comparative study of surrounding rock deformation in high speed railway tunnels

Scientific Reports
To tackle the challenge of discrete and complex monitoring data generated during high-speed rail tunnel construction, this study proposes a hybrid deep learning model for deformation forecasting.
Zeping Yang, Zhikai Cheng, Da Wu
doaj   +1 more source

Hybrid CNN-GRU Models for Improved EEG Motor Imagery Classification

Brain–computer interfaces (BCIs) based on electroencephalography (EEG) enable neural activity interpretation for device control, with motor imagery (MI) serving as a key paradigm for decoding imagined movements.
Wei Guo, Shuojin Yang, Mouna Bouchane
core   +1 more source

PEMODELAN STACKING ENSEMBLE BIDIRECTIONAL LSTM DAN BIDIRECTIONAL GRU UNTUK PREDIKSI SUHU UDARA DI KABUPATEN NGAWI

Jaringan saraf tiruan telah berkembang pesat dan diterapkan dalam peramalan, klasifikasi, dan regresi dengan meniru cara kerja otak manusia dalam mengolah data.
Nike Yustina Oktaviani, 4111420025
core  

COMPARATIVE ANALYSIS OF LSTM, BILSTM, GRU, CNN, AND RNN FOR DEPRESSION DETECTION IN SOCIAL MEDIA

The prevalence of mental health issues and the increasing use of social media provide an opportunity to leverage technology for early detection of depression.
Shidik, Guruh Fajar, Muhammad Huda, Alam, Praskatama, Vincentius   +2 more
core   +2 more sources

An Enhanced LSTM Approach for Detecting IoT-Based DDoS Attacks Using Honeypot Data

International Journal of Computational Intelligence Systems
One of the widening perils in network security is the Distributed Denial of Service (DDoS) attacks on the Internet of Things (IoT) ecosystem. This paper presents an enhanced Intrusion Detection System (IDS) through the proposal of an enhanced version of ...
Arjun Kumar Bose Arnob, M. F. Mridha, Mejdl Safran, Md Amiruzzaman, Md. Rajibul Islam   +4 more
doaj   +1 more source