Results 11 to 20 of about 208,635 (216)

A Stock Prediction Method Based on Heterogeneous Bidirectional LSTM

Applied Sciences
LSTM (long short-term memory) networks have been proven effective in processing stock data. However, the stability of LSTM is poor, it is greatly affected by data fluctuations, and it is weak in capturing long-term dependencies in sequential data. BiLSTM
Shuai Sang, Lu Li
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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   +3 more sources

Bidirectional LSTM approach to image captioning with scene features [PDF]

, 2020
Generating sentence descriptions for images is an area of research combining computer vision and natural language processing. More recently, it has been driven by encoder decoder deep learning approaches where visual features are learned with a ...
Agughalam, Davis Munachimso
core   +3 more sources

Development of a TVF-EMD-based multi-decomposition technique integrated with Encoder-Decoder-Bidirectional-LSTM for monthly rainfall forecasting

, 2023
Accurate forecasting of rainfall is extremely important due to its complex nature and enormous impacts on hydrology, floods, droughts, agriculture, and monitoring of pollutant concentration levels.
Yaseen, Zaher Mundher, Malik, Anurag, Ali, Mumtaz, Rai, Priya, Karbasi, Masoud, Jamei, Mehdi   +5 more
core   +1 more source

Near real-time wind speed forecast model with bidirectional LSTM networks

, 2023
Wind is an important source of renewable energy, often used to provide clean electricity to remote areas. For optimal extraction of this energy source, there is a need for an accurate and robust wind speed forecasting.
Deo, Ravinesh C., Soar, Jeffrey, Joseph, Lionel P., Prasad, Ramendra, Salcedo-Sanz, Sancho, Raj, Nawin   +5 more
core   +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
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Deep learning-based method for sentiment analysis for patients’ drug reviews [PDF]

PeerJ Computer Science
This article explores the application of deep learning techniques for sentiment analysis of patients’ drug reviews. The main focus is to evaluate the effectiveness of bidirectional long-short-term memory (LSTM) and a hybrid model (bidirectional LSTM-CNN)
Sena Al-Hadhrami, Tamas Vinko, Tawfik Al-Hadhrami, Faisal Saeed, Sultan Noman Qasem   +4 more
doaj   +2 more sources

Applicative Bidirectional Programming with Lenses [PDF]

, 2015
A bidirectional transformation is a pair of mappings between source and view data objects, one in each direction. When the view is modified, the source is updated accordingly with respect to some laws.
Matsuda, Kazutaka, Meng Wang, Wang, Meng, Kazutaka Matsuda   +3 more
core   +1 more source

DG-based SPO tuple recognition using self-attention M-Bi-LSTM

ETRI Journal, 2022
This study proposes a dependency grammar-based self-attention multilayered bidirectional long short-term memory (DG-M-Bi-LSTM) model for subject?predicate?object (SPO) tuple recognition from natural language (NL) sentences. To add recent knowledge to the
Joon-young Jung
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Sentiment analysis from textual data using multiple channels deep learning models

Journal of Electrical Systems and Information Technology, 2023
Text sentiment analysis has been of great importance over the last few years. It is being widely used to determine a person’s feelings, opinions and emotions on any topic or for someone.
Adepu Rajesh, Tryambak Hiwarkar
doaj   +1 more source