Results 291 to 300 of about 7,083,147 (335)

Long Short-Term Memory Recurrent Neural Network for Remaining Useful Life Prediction of Lithium-Ion Batteries

IEEE Transactions on Vehicular Technology, 2018
Remaining useful life (RUL) prediction of lithium-ion batteries can assess the battery reliability to determine the advent of failure and mitigate battery risk. The existing RUL prediction techniques for lithium-ion batteries are inefficient for learning
Yong-Zhi Zhang, R. Xiong, Hong-Wen He, M. Pecht   +3 more
semanticscholar   +1 more source

Pruning in Recurrent Neural Networks

1994
Recurrent neural networks are attracting considerable interest within the neural network domain especially because of their potential in such problems as pattern completion and temporal sequence processing (Almeida, 1987; Hertz et al., 1991). As for feed-forward networks, in virtually all problems of interest the proper number of hidden units is not ...
CASTELLANO G, FANELLI A. M, PELILLO, Marcello   +2 more
openaire   +2 more sources

A spiking recurrent neural network

IEEE Computer Society Annual Symposium on VLSI, 2004
A spiking recurrent neural network implementing an associative memory is proposed. The circuit including four integrate-and-fire (IF) and Willshaw-type binary synapses is designed with the AMI 0.5/spl mu/m CMOS process. A large-scale network is simulated with Matlab and its storage capacity is calculated and analyzed.
Yuan Li, John G. Harris
openaire   +2 more sources

Dropout for Recurrent Neural Networks

2019
Neural networks are computational structures which can be trained to perform tasks based on training examples or patterns. Recurrent neural networks are a type of network designed to process time-series data. Dropout is a neural network regularization technique.
Nathan Watt, Mathys C. du Plessis
openaire   +2 more sources

Self-Recurrent Neural Network

Substance Use & Misuse, 1998
(1998). Self-Recurrent Neural Network. Substance Use & Misuse: Vol. 33, No. 2, pp. 495-501.
openaire   +2 more sources

Gated recurrent unit based recurrent neural network for remaining useful life prediction of nonlinear deterioration process

Reliability Engineering & System Safety, 2019
Remaining useful life (RUL) prediction is a key process for prognostics and health management (PHM). However, conventional model-based methods and data-driven methods for RUL prediction are bad at a very complex system with multiple components, multiple ...
Jinglong Chen, H. Jing, Yuan-Hong Chang, Li-Yu Daisy Liu   +3 more
semanticscholar   +1 more source

ASRNN: A recurrent neural network with an attention model for sequence labeling

Knowledge-Based Systems, 2020
Natural language processing (NLP) is useful for handling text and speech, and sequence labeling plays an important role by automatically analyzing a sequence (text) to assign category labels to each part.
Chun-Wei Lin, Yinan Shao, Youcef Djenouri, Unil Yun   +3 more
semanticscholar   +1 more source

Recurrent Neural Network for Storytelling

2016 Joint 8th International Conference on Soft Computing and Intelligent Systems (SCIS) and 17th International Symposium on Advanced Intelligent Systems (ISIS), 2016
Storytelling is the act of passing on what you want to tell other people as so interesting and true-to-life story. As the study in text mining progresses to express words, sentences and paragraphs as vector, it is possible to classify text and generate text using vectors.
YunSeok Choi, Suah Kim, Jee-Hyong Lee 0001   +2 more
openaire   +2 more sources

Solar radiation prediction using recurrent neural network and artificial neural network: A case study with comparisons

, 2020
With the rapid advancement of the high-performance computing technology and the increasing availability of the mass-storage memory device, the application of the data-driven models (e.g., the artificial neural network (ANN) model) for solar radiation ...
Zhihong Pang, Fu-Xin Niu, Zheng O'Neill
semanticscholar   +1 more source

Predicting ultrafast nonlinear dynamics in fibre optics with a recurrent neural network

Nature Machine Intelligence, 2020
The propagation of ultrashort pulses in optical fibre plays a central role in the development of light sources and photonic technologies, with applications from fundamental studies of light–matter interactions to high-resolution imaging and remote ...
L. Salmela, Nikolaos Tsipinakis, A. Foi, C. Billet, J. Dudley, G. Genty   +5 more
semanticscholar   +1 more source