Cargando…

Surrogate Modelling for Oxygen Uptake Prediction Using LSTM Neural Network

Oxygen uptake ([Formula: see text] [Formula: see text]) is an important metric in any exercise test including walking and running. It can be measured using portable spirometers or metabolic analyzers. Those devices are, however, not suitable for constant use by consumers due to their costs, difficul...

Descripción completa

Detalles Bibliográficos
Autores principales:	Davidson, Pavel, Trinh, Huy, Vekki, Sakari, Müller, Philipp
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2023
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9964573/ https://www.ncbi.nlm.nih.gov/pubmed/36850848 http://dx.doi.org/10.3390/s23042249

Ejemplares similares

Urban Flooding Prediction Method Based on the Combination of LSTM Neural Network and Numerical Model
por: Chen, Jian, et al.
Publicado: (2023)

Dual Memory LSTM with Dual Attention Neural Network for Spatiotemporal Prediction
por: Li, Teng, et al.
Publicado: (2021)

Application of PSO-based LSTM Neural Network for Outpatient Volume Prediction
por: Lu, Wenjing, et al.
Publicado: (2021)

Prediction of SO(2) Concentration Based on AR-LSTM Neural Network
por: Ju, Jie, et al.
Publicado: (2022)

A Novel Bitcoin and Gold Prices Prediction Method Using an LSTM-P Neural Network Model
por: Zhang, Xinchen, et al.
Publicado: (2022)

Advertising Click-Through Rate Prediction Based on CNN-LSTM Neural Network
por: Zhu, Danqing
Publicado: (2021)

Multi-Section Traffic Flow Prediction Based on MLR-LSTM Neural Network
por: Shi, Ruizhe, et al.
Publicado: (2022)

TD-LSTM: Temporal Dependence-Based LSTM Networks for Marine Temperature Prediction
por: Liu, Jun, et al.
Publicado: (2018)

Hydrological Process Surrogate Modelling and Simulation with Neural Networks
por: Zhang, Ruixi, et al.
Publicado: (2020)

Predicting Energy Consumption Using LSTM, Multi-Layer GRU and Drop-GRU Neural Networks
por: Mahjoub, Sameh, et al.
Publicado: (2022)

PM2.5 concentration prediction using weighted CEEMDAN and improved LSTM neural network
por: Zhang, Li, et al.
Publicado: (2023)

Copper price prediction using LSTM recurrent neural network integrated simulated annealing algorithm
por: Chen, Jiahao, et al.
Publicado: (2023)

The Application of Automatic Identification System Information and PSO-LSTM Neural Network in CRI Prediction
por: Zhou, Wei, et al.
Publicado: (2022)

Retracted: Advertising Click-Through Rate Prediction Based on CNN-LSTM Neural Network
por: Intelligence and Neuroscience, Computational
Publicado: (2023)

Using LSTM recurrent neural networks for monitoring the LHC superconducting magnets
por: Wielgosz, Maciej, et al.
Publicado: (2016)

Time series prediction of COVID-19 by mutation rate analysis using recurrent neural network-based LSTM model
por: Pathan, Refat Khan, et al.
Publicado: (2020)

Spatio-temporal prediction of the COVID-19 pandemic in US counties: modeling with a deep LSTM neural network
por: Nikparvar, Behnam, et al.
Publicado: (2021)

Predictions for COVID-19 with deep learning models of LSTM, GRU and Bi-LSTM
por: Shahid, Farah, et al.
Publicado: (2020)

Research on PM2.5 Spatiotemporal Forecasting Model Based on LSTM Neural Network
por: Zhao, Fang, et al.
Publicado: (2021)

Predicting machine's performance record using the stacked long short‐term memory (LSTM) neural networks
por: Ma, Min, et al.
Publicado: (2022)

Stacked LSTM based deep recurrent neural network with kalman smoothing for blood glucose prediction
por: Rabby, Md Fazle, et al.
Publicado: (2021)

Comparison of LSTM, Transformers, and MLP-mixer neural networks for gaze based human intention prediction
por: Pettersson, Julius, et al.
Publicado: (2023)

LSTM and GRU Neural Networks as Models of Dynamical Processes Used in Predictive Control: A Comparison of Models Developed for Two Chemical Reactors
por: Zarzycki, Krzysztof, et al.
Publicado: (2021)

Forecast of the Employment Situation of College Graduates Based on the LSTM Neural Network
por: Li, Xing, et al.
Publicado: (2021)

LSTM Neural Network for Inferring Conduction Velocity Distribution in Demyelinating Neuropathies
por: Nodera, Hiroyuki, et al.
Publicado: (2021)

Scene Text Recognition Based on Bidirectional LSTM and Deep Neural Network
por: Kantipudi, MVV Prasad, et al.
Publicado: (2021)

Application of LSTM Neural Network Technology Embedded in English Intelligent Translation
por: Yang, Yifang
Publicado: (2022)

Neutron transport calculation for the BEAVRS core based on the LSTM neural network
por: Ren, Changan, et al.
Publicado: (2023)

Convolutional LSTM models to estimate network traffic
por: Waczynska, Joanna
Publicado: (2021)

Convolutional LSTM models to estimate network traffic
por: Waczynska, Joanna, et al.
Publicado: (2021)

Model of the Austenite Decomposition during Cooling of the Medium Carbon Steel Using LSTM Recurrent Neural Network
por: Kulawik, Adam, et al.
Publicado: (2021)

Surrogate Modeling of the CLIC Final-Focus System using Artificial Neural Networks
por: Ögren, J., et al.
Publicado: (2020)

Using the LSTM Neural Network and the UWB Positioning System to Predict the Position of Low and High Speed Moving Objects
por: Paszek, Krzysztof, et al.
Publicado: (2023)

An Advanced Long Short-Term Memory (LSTM) Neural Network Method for Predicting Rate of Penetration (ROP)
por: Ji, Hui, et al.
Publicado: (2022)

Temporal Prediction of Paralytic Shellfish Toxins in the Mussel Mytilus galloprovincialis Using a LSTM Neural Network Model from Environmental Data
por: Shin, Jisun, et al.
Publicado: (2022)

Improving Post-Filtering of Artificial Speech Using Pre-Trained LSTM Neural Networks
por: Coto-Jiménez, Marvin
Publicado: (2019)

ECG Identification For Personal Authentication Using LSTM-Based Deep Recurrent Neural Networks
por: Kim, Beom-Hun, et al.
Publicado: (2020)

The use of machine translation algorithm based on residual and LSTM neural network in translation teaching
por: Ren, Beibei
Publicado: (2020)

Classification of Bladder Emptying Patterns by LSTM Neural Network Trained Using Acoustic Signatures
por: Jin, Jie, et al.
Publicado: (2021)

Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition
por: Ordóñez, Francisco Javier, et al.
Publicado: (2016)

Cannot write session to /tmp/vufind_sessions/sess_fijm7768r2u8i6it4t2g3h5gd7