Securing industrial control systems: components, cyber threats, and machine learning-driven defense strategies
Industrial Control Systems (ICS), which include Supervisory Control and Data Acquisition
(SCADA) systems, Distributed Control Systems (DCS), and Programmable Logic Controllers …
(SCADA) systems, Distributed Control Systems (DCS), and Programmable Logic Controllers …
Gradient boosting feature selection with machine learning classifiers for intrusion detection on power grids
D Upadhyay, J Manero, M Zaman… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Smart grids rely on SCADA (Supervisory Control and Data Acquisition) systems to monitor
and control complex electrical networks in order to provide reliable energy to homes and …
and control complex electrical networks in order to provide reliable energy to homes and …
Intrusion detection in SCADA based power grids: Recursive feature elimination model with majority vote ensemble algorithm
D Upadhyay, J Manero, M Zaman… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
We propose an integrated framework for an intrusion detection system for SCADA
(Supervisory Control and Data Acquisition)-based power grids. Our scheme combines RFE …
(Supervisory Control and Data Acquisition)-based power grids. Our scheme combines RFE …
An Ensemble‐Based Multiclass Classifier for Intrusion Detection Using Internet of Things
Internet of Things (IoT) is the fastest growing technology that has applications in various
domains such as healthcare, transportation. It interconnects trillions of smart devices through …
domains such as healthcare, transportation. It interconnects trillions of smart devices through …
Predicting drug risk level from adverse drug reactions using SMOTE and machine learning approaches
J Wei, Z Lu, K Qiu, P Li, H Sun - IEEE Access, 2020 - ieeexplore.ieee.org
Adverse drug reactions (ADRs) are the major source of morbidity and mortality. The
prediction of drug risk level based on ADRs is few. Our study aims at predicting the drug risk …
prediction of drug risk level based on ADRs is few. Our study aims at predicting the drug risk …
Noise-immune extreme ensemble learning for early diagnosis of neuropsychiatric systemic lupus erythematosus
Y Yuan, T Quan, Y Song, J Guan… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Early diagnosis is currently the most effective way of saving the life of patients with
neuropsychiatric systemic lupus erythematosus (NPSLE). However, it is rather difficult to …
neuropsychiatric systemic lupus erythematosus (NPSLE). However, it is rather difficult to …
Maximum margin and global criterion based-recursive feature selection
X Ding, Y Li, S Chen - Neural Networks, 2024 - Elsevier
In this research paper, we aim to investigate and address the limitations of recursive feature
elimination (RFE) and its variants in high-dimensional feature selection tasks. We identify …
elimination (RFE) and its variants in high-dimensional feature selection tasks. We identify …
A novel hypoglycemia alarm framework for type 2 diabetes with high glycemic variability
X Wang, Z Yang, N Ma, X Sun, H Li… - … Journal for Numerical …, 2024 - Wiley Online Library
In patients with type 2 diabetes (T2D), accurate prediction of hypoglycemic events is crucial
for maintaining glycemic control and reducing their frequency. However, individuals with …
for maintaining glycemic control and reducing their frequency. However, individuals with …
Drug–target interaction prediction via multiple classification strategies
Q Ye, X Zhang, X Lin - BMC bioinformatics, 2022 - Springer
Background Computational prediction of the interaction between drugs and protein targets is
very important for the new drug discovery, as the experimental determination of drug-target …
very important for the new drug discovery, as the experimental determination of drug-target …
Quantifying regional variability of machine-learning-based snow water equivalent estimates across the Western United States
Seasonal snow-derived water is a critical component of the water supply in the mountains
and downstream regions, and the accurate characterization of available water in the form of …
and downstream regions, and the accurate characterization of available water in the form of …