Zobrazeno 1 - 10
of 79
pro vyhledávání: '"Ting-Li Su"'
Autor:
Sarah Mackie, Ting-Li Su, James Yates, Basil G Issa, Brian McMillan, Michelle Harvie, Andrea Pilkington, Fahmy Hanna, Avni Vyas, Cheryl Lombardelli, Womba Mubita, Elizabeth Dapre, Benjamin Evans
Publikováno v:
BMJ Open, Vol 14, Iss 2 (2024)
Introduction The prevalence of gestational diabetes mellitus (GDM) is rising in the UK and is associated with maternal and neonatal complications. National Institute for Health and Care Excellence guidance advises first-line management with healthy e
Externí odkaz:
https://doaj.org/article/c7f724a219c049539079863c50261f20
Publikováno v:
Frontiers in Neurorobotics, Vol 17 (2023)
IntroductionGlobal navigation satellite system (GNSS) signals can be lost in viaducts, urban canyons, and tunnel environments. It has been a significant challenge to achieve the accurate location of pedestrians during Global Positioning System (GPS)
Externí odkaz:
https://doaj.org/article/3c34fd997281483aa1c1e11812971996
Publikováno v:
Sensors, Vol 23, Iss 20, p 8650 (2023)
GPS-based maneuvering target localization and tracking is a crucial aspect of autonomous driving and is widely used in navigation, transportation, autonomous vehicles, and other fields.The classical tracking approach employs a Kalman filter with prec
Externí odkaz:
https://doaj.org/article/468009a608b54b909bcfe5508e8edcd5
Publikováno v:
Applied Sciences, Vol 13, Iss 8, p 5088 (2023)
Deep learning effectively identifies and predicts modes but faces performance reduction under few-shot learning conditions. In this paper, a time series prediction framework for small samples is proposed, including a data augmentation algorithm, time
Externí odkaz:
https://doaj.org/article/ccd556f350ba42d2994618c4c52f106c
Nonstationary Time Series Prediction Based on Deep Echo State Network Tuned by Bayesian Optimization
Publikováno v:
Mathematics, Vol 11, Iss 6, p 1503 (2023)
The predictions from time series data can help us sense development trends and make scientific decisions in advance. The commonly used forecasting methods with backpropagation consume a lot of computational resources. The deep echo state network (Dee
Externí odkaz:
https://doaj.org/article/7bcecedeaea140f59ee063547c060b59
Publikováno v:
Agronomy, Vol 13, Iss 3, p 625 (2023)
Weather is an essential component of natural resources that affects agricultural production and plays a decisive role in deciding the type of agricultural production, planting structure, crop quality, etc. In field agriculture, medium- and long-term
Externí odkaz:
https://doaj.org/article/7f9c43e1a3a54106ba5a327d5ad81a8b
Variational Bayesian Network with Information Interpretability Filtering for Air Quality Forecasting
Autor:
Xue-Bo Jin, Zhong-Yao Wang, Wen-Tao Gong, Jian-Lei Kong, Yu-Ting Bai, Ting-Li Su, Hui-Jun Ma, Prasun Chakrabarti
Publikováno v:
Mathematics, Vol 11, Iss 4, p 837 (2023)
Air quality plays a vital role in people’s health, and air quality forecasting can assist in decision making for government planning and sustainable development. In contrast, it is challenging to multi-step forecast accurately due to its complex an
Externí odkaz:
https://doaj.org/article/9190d0c9c9d14ab5b821f1d2aec4e308
Autor:
Xue-Bo Jin, Zhong-Yao Wang, Jian-Lei Kong, Yu-Ting Bai, Ting-Li Su, Hui-Jun Ma, Prasun Chakrabarti
Publikováno v:
Entropy, Vol 25, Iss 2, p 247 (2023)
The environment and development are major issues of general concern. After much suffering from the harm of environmental pollution, human beings began to pay attention to environmental protection and started to carry out pollutant prediction research
Externí odkaz:
https://doaj.org/article/a04bb1fa432c4ee4a04b0ad108c90ba0
Autor:
Chun-Ming Xu, Jia-Shuai Zhang, Ling-Qiang Kong, Xue-Bo Jin, Jian-Lei Kong, Yu-Ting Bai, Ting-Li Su, Hui-Jun Ma, Prasun Chakrabarti
Publikováno v:
Mathematics, Vol 10, Iss 22, p 4283 (2022)
Effective prediction of wastewater treatment is beneficial for precise control of wastewater treatment processes. The nonlinearity of pollutant indicators such as chemical oxygen demand (COD) and total phosphorus (TP) makes the model difficult to fit
Externí odkaz:
https://doaj.org/article/188d25f2a6104e2c83a6808634b569dc
Publikováno v:
Mathematics, Vol 10, Iss 17, p 3188 (2022)
Time series forecasting provides a vital basis for the control and management of various systems. The time series data in the real world are usually strongly nonstationary and nonlinear, which increases the difficulty of reliable forecasting. To full
Externí odkaz:
https://doaj.org/article/7c05b78cab424474b16b91841f15c1bc