A new two-step ensemble learning model for improving stress prediction of automobile drivers

G Issa - The International Arab Journal of …, 2021 - research.skylineuniversity.ac.ae
Commuting when there is a significant volume of traffic congestion has been acknowledged
as one of the key factors causing stress. Significant levels of stress whilst driving are seen to …

ARTC: feature selection using association rules for text classification

MM Saeed, Z Al Aghbari - Neural Computing and Applications, 2022 - Springer
Feature vectors are extracted to represent objects in many classification tasks, such as text
classification. Due to the high dimensionality of these raw feature vectors, the classification …

[PDF][PDF] A comparative study for different resampling techniques for imbalanced datasets

AM Elsobky, AEL Keshk, MG Malhat - IJCI. International Journal of …, 2023 - journals.ekb.eg
The imbalanced data is a significant challenge forresearchers in supervised machine
learning. Current data mining algorithms are not effective for processing imbalanced data. In …

Predicting stress levels of automobile drivers using classical machine learning classifiers

M Alnashashibi, W Hadi… - … Conference on Business …, 2022 - ieeexplore.ieee.org
Traffic congestion has been found to be a substantial source of stress for many people. To
put it another way, driving under the influence of high amounts of stress could result in …

Enhancing EV charging station security: A multi-stage approach

ED Buedi - 2024 - unbscholar.lib.unb.ca
Abstract The deployment of Electric Vehicle (EV) charging stations is pivotal to the global
shift towards eco-friendly transportation. Nevertheless, as these systems become …