Data science and big data analytics: A systematic review of methodologies used in the supply chain and logistics research
Data science and big data analytics (DS &BDA) methodologies and tools are used
extensively in supply chains and logistics (SC &L). However, the existing insights are …
extensively in supply chains and logistics (SC &L). However, the existing insights are …
Intelligent financial fraud detection practices in post-pandemic era
The great losses caused by financial fraud have attracted continuous attention from
academia, industry, and regulatory agencies. More concerning, the ongoing coronavirus …
academia, industry, and regulatory agencies. More concerning, the ongoing coronavirus …
On the class overlap problem in imbalanced data classification
Class imbalance is an active research area in the machine learning community. However,
existing and recent literature showed that class overlap had a higher negative impact on the …
existing and recent literature showed that class overlap had a higher negative impact on the …
When machine learning meets privacy in 6G: A survey
The rapid-develo** Artificial Intelligence (AI) technology, fast-growing network traffic, and
emerging intelligent applications (eg, autonomous driving, virtual reality, etc.) urgently …
emerging intelligent applications (eg, autonomous driving, virtual reality, etc.) urgently …
Physics-guided, physics-informed, and physics-encoded neural networks in scientific computing
Recent breakthroughs in computing power have made it feasible to use machine learning
and deep learning to advance scientific computing in many fields, including fluid mechanics …
and deep learning to advance scientific computing in many fields, including fluid mechanics …
An interpretable machine learning approach for hepatitis b diagnosis
Hepatitis B is a potentially deadly liver infection caused by the hepatitis B virus. It is a serious
public health problem globally. Substantial efforts have been made to apply machine …
public health problem globally. Substantial efforts have been made to apply machine …
Application placement in Fog computing with AI approach: Taxonomy and a state of the art survey
With the increasing use of the Internet of Things (IoT) in various fields and the need to
process and store huge volumes of generated data, Fog computing was introduced to …
process and store huge volumes of generated data, Fog computing was introduced to …
[HTML][HTML] Machine learning prediction of the mechanical properties of γ-TiAl alloys produced using random forest regression model
S Kwak, J Kim, H Ding, X Xu, R Chen, J Guo… - Journal of Materials …, 2022 - Elsevier
The mechanical properties of a directionally solidified (DS) TiAl alloy were predicted through
a random forest regression (RFR) machine learning algorithm. The prediction results were …
a random forest regression (RFR) machine learning algorithm. The prediction results were …
Class weights random forest algorithm for processing class imbalanced medical data
M Zhu, J **a, X **, M Yan, G Cai, J Yan, G Ning - IEEE Access, 2018 - ieeexplore.ieee.org
The classification in class imbalanced data has drawn significant interest in medical
application. Most existing methods are prone to categorize the samples into the majority …
application. Most existing methods are prone to categorize the samples into the majority …
[HTML][HTML] Sub-surface geospatial intelligence in carbon capture, utilization and storage: a machine learning approach for offshore storage site selection
This study introduces an innovative data-driven and machine-learning framework designed
to accurately predict site scores in the site screening study for specific offshore CO 2 storage …
to accurately predict site scores in the site screening study for specific offshore CO 2 storage …