Results 21 to 30 of about 5,451,620 (296)

Recurrent neural network (RNN)-based model architecture.

, 2022
Recurrent neural network (RNN)-based model architecture.
Ana Cho (12800195), Sang Hyun Kim (8720874), You Jin Kang (12800192), Min Seo Choi (10199757), Young-Seob Jeong (12800186), Gati Lother Martin (12800189), Bon Sung Koo (12800198), Yang-Hoon Chung (12696094), Misoon Lee (8720868), Sung Hwan Cho (765712)   +9 more
core   +1 more source

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   +1 more source

Lithium Battery State-of-Charge Estimation Based on AdaBoost.Rt-RNN

Energies, 2022
Real-time and accurate state-of-charge estimation performs an important role in the smooth operation of various electric vehicle battery management systems.
Ran Li, Hui Sun, Xue Wei, Weiwen Ta, Haiying Wang   +4 more
doaj   +1 more source

SORN : a self-organizing recurrent neural network [PDF]

, 2009
Understanding the dynamics of recurrent neural networks is crucial for explaining how the brain processes information. In the neocortex, a range of different plasticity mechanisms are shaping recurrent networks into effective information processing ...
Pipa, Gordon, Andreea Lazar, Triesch, Jochen, Lazar, Andreea, Gordon Pipa, Jochen Triesch   +5 more
core   +1 more source

Convergence and Robustness Analysis of the Exponential-Type Varying Gain Recurrent Neural Network for Solving Matrix-Type Linear Time-Varying Equation

IEEE Access, 2018
To solve matrix-type linear time-varying equation more efficiently, a novel exponentialtype varying gain recurrent neural network (EVG-RNN) is proposed in this paper. Being distinguished from the traditional fixed-parameter gain recurrent neural network (
Zhijun Zhang, Zheng Fu, Lunan Zheng, Min Gan   +3 more
doaj   +1 more source

Predicting machine failure using recurrent neural network-gated recurrent unit (RNN-GRU) through time series data [PDF]

, 2021
Time series data often involves big size environment that lead to high dimensionality problem. Many industries are generating time series data that continuously update each second. The arising of machine learning may help in managing the data.
E. A., P. Akhir, M. H., Hasan, P. Akhir E. A., Z., Zainuddin, Zainuddin Z., Hasan M. H.   +5 more
core   +1 more source

Machine translation of English speech: Comparison of multiple algorithms

Journal of Intelligent Systems, 2022
In order to improve the efficiency of the English translation, machine translation is gradually and widely used. This study briefly introduces the neural network algorithm for speech recognition.
Wu Yijun, Qin Yonghong
doaj   +1 more source

TS-RNN: Text Steganalysis Based on Recurrent Neural Networks [PDF]

IEEE Signal Processing Letters, 2019
IEEE Signal Processing ...
Zhongliang Yang, Ke Wang 0033, Jian Li, Yongfeng Huang 0001, Yu-Jin Zhang   +4 more
openaire   +3 more sources

A Scheme with Acoustic Emission Hit Removal for the Remaining Useful Life Prediction of Concrete Structures

Sensors, 2021
In this study, a scheme of remaining useful lifetime (RUL) prognosis from raw acoustic emission (AE) data is presented to predict the concrete structure’s failure before its occurrence, thus possibly prolong its service life and minimizing the risk of ...
Tuan-Khai Nguyen, Zahoor Ahmad, Jong-Myon Kim   +2 more
doaj   +1 more source

Behavioural pattern identification and prediction in intelligent environments [PDF]

, 2013
In this paper, the application of soft computing techniques in prediction of an occupant's behaviour in an inhabited intelligent environment is addressed.
Mahmoud, S, Lotfi, A, Langensiepen, C
core   +1 more source