A survey on educational data mining methods used for predicting students' performance

W **ao, P Ji, J Hu - Engineering Reports, 2022 - Wiley Online Library
Predicting students' performance is one of the most important issues in educational data
mining (EDM), which has received more and more attention. By predicting students' …

Proactive and reactive engagement of artificial intelligence methods for education: a review

S Mallik, A Gangopadhyay - Frontiers in artificial intelligence, 2023 - frontiersin.org
The education sector has benefited enormously through integrating digital technology driven
tools and platforms. In recent years, artificial intelligence based methods are being …

Spatio-temporal feature encoding for traffic accident detection in VANET environment

Z Zhou, X Dong, Z Li, K Yu, C Ding… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In the Vehicular Ad hoc Networks (VANET) environment, recognizing traffic accident events
in the driving videos captured by vehicle-mounted cameras is an essential task. Generally …

[PDF][PDF] Performance of machine learning algorithms with different K values in K-fold CrossValidation

IK Nti, O Nyarko-Boateng, J Aning - International Journal of …, 2021 - researchgate.net
The numerical value of k in a k-fold cross-validation training technique of machine learning
predictive models is an essential element that impacts the model's performance. A right …

Predicting household electric power consumption using multi-step time series with convolutional LSTM

L Cascone, S Sadiq, S Ullah, S Mirjalili, HUR Siddiqui… - Big Data Research, 2023 - Elsevier
Energy consumption prediction has become an integral part of a smart and sustainable
environment. With future demand forecasts, energy production and distribution can be …

Pothole and plain road classification using adaptive mutation dipper throated optimization and transfer learning for self driving cars

AA Alhussan, DS Khafaga, ESM El-Kenawy… - IEEE …, 2022 - ieeexplore.ieee.org
Self-driving car plays a crucial role in implementing traffic intelligence. Road smoothness in
front of self-driving cars has a significant impact on the car's driving safety and comfort …

An MRI scans-based Alzheimer's disease detection via convolutional neural network and transfer learning

KT Chui, BB Gupta, W Alhalabi, FS Alzahrani - Diagnostics, 2022 - mdpi.com
Alzheimer's disease (AD) is the most common type (> 60%) of dementia and can wreak
havoc on the psychological and physiological development of sufferers and their carers, as …

Examining ICT attitudes, use and support in blended learning settings for students' reading performance: Approaches of artificial intelligence and multilevel model

Y Peng, Y Wang, J Hu - Computers & Education, 2023 - Elsevier
The increasing importance of learning context digitalization has necessitated investigations
into the effects of information and communication technology (ICT)-related factors in blended …

Predicting student performance and its influential factors using hybrid regression and multi-label classification

A Alshanqiti, A Namoun - Ieee Access, 2020 - ieeexplore.ieee.org
Understanding, modeling, and predicting student performance in higher education poses
significant challenges concerning the design of accurate and robust diagnostic models …

[HTML][HTML] Development and innovation of enterprise knowledge management strategies using big data neural networks technology

Y Zhao, S Wen, T Zhou, W Liu, H Yu, H Xu - Journal of Innovation & …, 2022 - Elsevier
To strengthen the development of enterprises and optimize knowledge management
strategies, the current situation of enterprise knowledge management (EKM) is investigated …