Results 71 to 80 of about 79,032 (283)

Uncertainty quantification-based framework for predicting degradation trends of proton exchange membrane fuel cell

Green Energy and Intelligent Transportation
Accurately predicting the degradation trends of proton exchange membrane fuel cells (PEMFCs) can provide a solid basis for optimizing the control of vehicles and stations based on PEMFCs.
Bingxin Guo, Changjun Xie, Wenchao Zhu, Yang Yang, Hao Li, Yang Li, Hangyu Wu   +6 more
doaj   +1 more source

Wireless Channel Prediction of GRU Based on Experience Replay and Snake Optimizer

Sensors, 2023
Aiming at the problem of poor prediction accuracy of Channel State Information (CSI) caused by fast time-varying channels in wireless communication systems, this paper proposes a gated recurrent network based on experience replay and Snake Optimizer for ...
Qingli Liu, Peiling Wang, Jiaxu Sun, Rui Li, Yangyang Li   +4 more
doaj   +1 more source

Age‐Related Characteristics of SYT1‐Associated Neurodevelopmental Disorder

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives We describe the clinical manifestations and developmental abilities of individuals with SYT1‐associated neurodevelopmental disorder (Baker‐Gordon syndrome) from infancy to adulthood. We further describe the neuroradiological and electrophysiological characteristics of the condition at different ages, and explore the associations ...
Sam G. Norwitz, Josefine Eck, Joel S. Winston, Kate Baker   +3 more
wiley   +1 more source

Dual-Gated Graph Convolutional Recurrent Unit with Integrated Graph Learning (DG3L): A Novel Recurrent Network Architecture with Dynamic Graph Learning for Spatio-Temporal Predictions

Entropy
Spatio-temporal prediction is crucial in intelligent transportation systems (ITS) to enhance operational efficiency and safety. Although Transformer-based models have significantly advanced spatio-temporal prediction performance, recent research ...
Yuxuan Wang, Zhouyuan Zhang, Shu Pi, Haishan Zhang, Jiatian Pi   +4 more
doaj   +1 more source

A conditional random field based feature learning framework for battery capacity prediction

Scientific Reports, 2022
This paper proposes a network model framework based on long and short-term memory (LSTM) and conditional random field (CRF) to promote Li-ion battery capacity prediction results.
Hai-Kun Wang, Yang Zhang, Mohong Huang
doaj   +1 more source

Gated Recurrent Fuzzy Neural Network Sliding Mode Control of a Micro Gyroscope

Mathematics, 2023
This paper proposes a non-singular fast terminal sliding mode control (NFTSMC) method for micro gyroscopes with unknown uncertainty based on gated recurrent fuzzy neural networks (GRFNNs).
Jiapeng Xie, Juntao Fei, Cuicui An
doaj   +1 more source

Digging Deeper into Egocentric Gaze Prediction

, 2019
This paper digs deeper into factors that influence egocentric gaze. Instead of training deep models for this purpose in a blind manner, we propose to inspect factors that contribute to gaze guidance during daily tasks. Bottom-up saliency and optical flow
Borji, Ali, Kannala, Juho, Rahtu, Esa, Tavakoli, Hamed R.   +3 more
core   +1 more source

A Gated Recurrent Unit Approach to Bitcoin Price Prediction [PDF]

SSRN Electronic Journal, 2019
In today’s era of big data, deep learning and artificial intelligence have formed the backbone for cryptocurrency portfolio optimization. Researchers have investigated various state of the art machine learning models to predict Bitcoin price and volatility.
Dutta, Aniruddha, Kumar, Saket, Basu, Meheli   +2 more
openaire   +4 more sources

Clinical Practice Guideline for Evaluation and Management of Peripheral Nervous System Manifestations in Sjögren's Disease

Arthritis Care &Research, EarlyView.
Objective Sjögren's disease is an autoimmune disorder that can impact multiple organ systems, including the peripheral nervous system (PNS). PNS manifestations, which can exist concurrently, include mononeuropathies, polyneuropathies, and autonomic nervous system neuropathies.
Anahita Deboo, Robert Fox, Katherine M. Hammitt, Julie Frantsve‐Hawley, Matthew C. Baker, Stamatina Danielides, Eduardo De Sousa, Brent P. Goodman, Jennifer K. King, Steven Mandel, Ghaith Noaiseh, Pantelis P. Pavlakis, George Sarka, R. Hal Scofield, Arun Varadhachary, Daniel J. Wallace, Matt Makara, Nancy Carteron, Steven Carsons, in collaboration with the Consensus Expert Panel (CEP) members, G. Alden Adkins, Brittany Adler, Hossein Ansari, Senada Arabelovic, Alan Baer, Denis Balaban, Shamik Bhattacharyya, Evelyn Bromet, Krishna Chaganti, Kamal Chemali, Melissa Cortez, Schartess Culpepper, Paul Dellaripa, Dana Direnzo, Daniel El Bogdadi, Robert Fearon, Mehrnez Fischbach, Judi Furlong, Christopher Gibbons, Rachael Gordon, Thomas Grader Beck, Syed Haider, Larry Hollenbeck, Chadwick R. Johr, Stuart S. Kassan, Brian King, Octavia Kincaid, Eugene Kissin, Vasileios Kyttaris, Lindsay Lally, Brandon M. Law, Janet Lewis, Scott M. Lieberman, Amanda Lusa, Joseph Lutt, Rashmi Maganti, Arthur M. Mandelin, Sara McCoy, Kerry Neall, Timothy Niewold, Anne Louise Oaklander, Ruben A. Peredo‐Wende, Lynn Petruzzi, Mark A. Porter, Guada Respicio Duque, Tania Reyna, Nathaniel M. Robbins, Elliot D. Rosenstein, Laura Rosow, Breanna Ruthrauff, Amit Sachdev, Nora Sandorfi, Sarah Schafer, Elena Schiopu, Chokkalingam Siva, Daniel Small, Sara M. Stern, Lauren Stiles, Susan Stoddard, Jinny Tavee, Donald Thomas, Edward L. Treadwell, Nagagopal Venna, Steven Vernino, Frederick B. Vivino, Brittany Weber, Sepideh Yadollahi, Huiying Yu, Scott Zashin   +88 more
wiley   +1 more source

Simplified minimal gated unit variations for recurrent neural networks [PDF]

2017 IEEE 60th International Midwest Symposium on Circuits and Systems (MWSCAS), 2017
5 pages, 3 Figures, 5 ...
Heck, Joel, Salem, Fathi M.
openaire   +2 more sources