Results 11 to 20 of about 6,008 (208)

A Bidirectional LSTM-RNN and GRU Method to Exon Prediction Using Splice-Site Mapping

Applied Sciences, 2022
Deep Learning techniques (DL) significantly improved the accuracy of predictions and classifications of deoxyribonucleic acid (DNA). On the other hand, identifying and predicting splice sites in eukaryotes is difficult due to many erroneous discoveries ...
Peren Jerfi CANATALAY, Osman Nuri Ucan
doaj   +2 more sources

Advanced Network Traffic Prediction Using Deep Learning Techniques: A Comparative Study of SVR, LSTM, GRU, and Bidirectional LSTM Models [PDF]

ITM Web of Conferences
Accurate prediction of network traffic patterns is essential for optimizing network resource allocation, managing congestion, and strengthening cybersecurity. This study examines the effectiveness of four machine learning models—Support Vector Regression
Wang Yuxin
doaj   +2 more sources

GRU-BERT for NILM: A Hybrid Deep Learning Architecture for Load Disaggregation

AI
Non-Intrusive Load Monitoring (NILM) aims to disaggregate a household’s total aggregated power consumption into appliance-level usage, enabling intelligent energy management without the need for intrusive metering.
Annysha Huzzat, Ahmed S. Khwaja, Ali A. Alnoman, Bhagawat Adhikari, Alagan Anpalagan, Isaac Woungang   +5 more
doaj   +2 more sources

Comparison of the Forecast Accuracy of Total Electron Content for Bidirectional and Temporal Convolutional Neural Networks in European Region

Remote Sensing, 2023
Machine learning can play a significant role in bringing new insights in GNSS remote sensing for ionosphere monitoring and modeling to service. In this paper, a set of multilayer architectures of neural networks is proposed and considered, including both
Artem Kharakhashyan, Olga Maltseva
doaj   +2 more sources

Bidirectional convolutional recurrent neural network architecture with group-wise enhancement mechanism for text sentiment classification

Journal of King Saud University: Computer and Information Sciences, 2022
Sentiment analysis has been a well-studied research direction in computational linguistics. Deep neural network models, including convolutional neural networks (CNN) and recurrent neural networks (RNN), yield promising results on text classification ...
Aytuğ Onan
doaj   +2 more sources

Depth prediction of urban waterlogging based on BiTCN-GRU modeling.

PLoS ONE
With China's rapid urbanization and the increasing frequency of extreme weather events, heavy rainfall-induced urban waterlogging has become a persistent and pressing challenge.
Quan Wang, Mingjie Tang, Pei Shi
doaj   +2 more sources

LSTM and Bidirectional GRU Comparison for Text Classification

sinkron, 2023
Although the phrases machine learning and AI are frequently used interchangeably and are frequently discussed together, they do not have the same meanings. While all artificial intelligence (AI) is machine learning, not all AI is machine learning, which is a key distinction.
Hannan Asrawi, Ema Utami, Ainul Yaqin
openaire   +1 more source

Categorizing 15 kV High-Voltage HDPE Insulator’s Leakage Current Surges Based on Convolution Neural Network Gated Recurrent Unit

Energies, 2023
The leakage currents are appropriate for determining the contamination level of insulators in the power distribution system, which are efficiently cleaned or replaced during the maintenance schedule.
Wen-Bin Liu, Phuong Nguyen Thanh, Ming-Yuan Cho, Thao Nguyen Da   +3 more
doaj   +1 more source

Comparing Machine and Deep Learning Methods for the Phenology-Based Classification of Land Cover Types in the Amazon Biome Using Sentinel-1 Time Series

Remote Sensing, 2022
The state of Amapá within the Amazon biome has a high complexity of ecosystems formed by forests, savannas, seasonally flooded vegetation, mangroves, and different land uses. The present research aimed to map the vegetation from the phenological behavior
Ivo Augusto Lopes Magalhães, Osmar Abílio de Carvalho Júnior, Osmar Luiz Ferreira de Carvalho, Anesmar Olino de Albuquerque, Potira Meirelles Hermuche, Éder Renato Merino, Roberto Arnaldo Trancoso Gomes, Renato Fontes Guimarães   +7 more
doaj   +1 more source

Benchmarking of eight recurrent neural network variants for breath phase and adventitious sound detection on a self-developed open-access lung sound database-HF_Lung_V1.

PLoS ONE, 2021
A reliable, remote, and continuous real-time respiratory sound monitor with automated respiratory sound analysis ability is urgently required in many clinical scenarios-such as in monitoring disease progression of coronavirus disease 2019-to replace ...
Fu-Shun Hsu, Shang-Ran Huang, Chien-Wen Huang, Chao-Jung Huang, Yuan-Ren Cheng, Chun-Chieh Chen, Jack Hsiao, Chung-Wei Chen, Li-Chin Chen, Yen-Chun Lai, Bi-Fang Hsu, Nian-Jhen Lin, Wan-Ling Tsai, Yi-Lin Wu, Tzu-Ling Tseng, Ching-Ting Tseng, Yi-Tsun Chen, Feipei Lai   +17 more
doaj   +1 more source