Machine learning to predict pregnancy outcomes: a systematic review, synthesizing framework and future research agenda
Abstract Machine Learning (ML) has been widely used in predicting the mode of childbirth
and assessing the potential maternal risks during pregnancy. The primary aim of this review …
and assessing the potential maternal risks during pregnancy. The primary aim of this review …
A review of intelligent computation offloading in multiaccess edge computing
H Jin, MA Gregory, S Li - IEEE Access, 2022 - ieeexplore.ieee.org
Multi-Access Edge Computing (MEC) is a standardized architecture that enables cloud
computing capabilities at the edge of heterogeneous networks. The concept is to reduce …
computing capabilities at the edge of heterogeneous networks. The concept is to reduce …
Dynamic pricing strategy of electric vehicle aggregators based on DDPG reinforcement learning algorithm
D Liu, W Wang, L Wang, H Jia, M Shi - IEEE access, 2021 - ieeexplore.ieee.org
The fixed service charge pricing model adopted by traditional electric vehicle aggregators
(EVAs) is difficult to effectively guide the demand side resources to respond to the power …
(EVAs) is difficult to effectively guide the demand side resources to respond to the power …
Digital twins-boosted intelligent maintenance of ageing bridge hangers exposed to coupled corrosion–fatigue deterioration
J Heng, Y Dong, L Lai, Z Zhou, DM Frangopol - Automation in Construction, 2024 - Elsevier
The corrosion–fatigue coupled deterioration of ageing steel bridge hangers presents
significant structural challenges, demanding rigorous condition assessments and timely …
significant structural challenges, demanding rigorous condition assessments and timely …
Survey of recent multi-agent reinforcement learning algorithms utilizing centralized training
PK Sharma, R Fernandez, E Zaroukian… - … learning for multi …, 2021 - spiedigitallibrary.org
Much work has been dedicated to the exploration of Multi-Agent Reinforcement Learning
(MARL) paradigms implementing a centralized learning with decentralized execution …
(MARL) paradigms implementing a centralized learning with decentralized execution …
Blockchain-based computing resource trading in autonomous multi-access edge network slicing: A dueling double deep Q-learning approach
T Kwantwi, G Sun, NAE Kuadey… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
We investigate the computing resource allocation in multi-access edge network slicing (NS)
in the context of revenue and multi-access edge computing (MEC) resource management …
in the context of revenue and multi-access edge computing (MEC) resource management …
Development of an HVAC system control method using weather forecasting data with deep reinforcement learning algorithms
Heating, ventilation, and air conditioning (HVAC) systems account for a significant
proportion of the energy consumption of a building. With the global energy demand …
proportion of the energy consumption of a building. With the global energy demand …
Design of experiments for the calibration of history-dependent models via deep reinforcement learning and an enhanced Kalman filter
R Villarreal, NN Vlassis, NN Phan, TA Catanach… - Computational …, 2023 - Springer
Experimental data are often costly to obtain, which makes it difficult to calibrate complex
models. For many models an experimental design that produces the best calibration given a …
models. For many models an experimental design that produces the best calibration given a …
The state-of-the-art in air pollution monitoring and forecasting systems using IoT, big data, and machine learning
The quality of air is closely linked with the life quality of humans, plantations, and wildlife. It
needs to be monitored and preserved continuously. Transportations, industries, construction …
needs to be monitored and preserved continuously. Transportations, industries, construction …
Research on bidding strategy of thermal power companies in electricity market based on multi-agent deep deterministic policy gradient
D Liu, Y Gao, W Wang, Z Dong - IEEE access, 2021 - ieeexplore.ieee.org
With the continuous improvement of new energy penetration in the power system, the price
of the spot market of power frequently fluctuates greatly, which damages the income of a …
of the spot market of power frequently fluctuates greatly, which damages the income of a …