Raghad Al-Shabandar

According to our database, Raghad Al-Shabandar authored at least 13 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

A Risk Model for Assessing Exposure Factors Influence Oil Price Fluctuations.

Raghad Al-Shabandar, Ali Jaddoa, Abir Hussain

Proceedings of the Advanced Intelligent Computing Technology and Applications, 2023

Intelligent Measuring for a Customer Satisfaction Level Inspired by Transformation Language Model.

Raghad Al-Shabandar, Ali Jaddoa, A. H. Mohammed, Abir Jaafar Hussain

Proceedings of the 16th International Conference on Developments in eSystems Engineering, 2023

Multivariate Comparative Analysis of Statistical and Deep Learning Models for Prediction Hardware Failure.

Saurabh Gupta, Raghad Al-Shabandar, Chong Kim Loy, Ammar H. Mohammed

Proceedings of the Data Science and Emerging Technologies, 2023

Telecom Customer Experience Analysis Using Sentiment Analysis and Natural Language Processing - Comparative Study.

Ahmed Mohamed Abdou Ahmed, Abdulaziz Al-Nahari, Raghad Al-Shabandar, Chong Kim Loy, A. H. Mohammed

Proceedings of the Data Science and Emerging Technologies, 2023

2020

Lossy and Lossless Video Frame Compression: A Novel Approach for High-Temporal Video Data Analytics.

Zayneb Ahmed, Abir Jaafar Hussain, Wasiq Khan, Thar Baker, Haya Al-Askar, Janet Lunn, Raghad Al-Shabandar, Dhiya Al-Jumeily, Panos Liatsis

Remote. Sens., 2020

Students Performance Prediction in Online Courses Using Machine Learning Algorithms.

Raghad Al-Shabandar, Abir Hussain, Robert Keight, Wasiq Khan

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

2019

The application of machine learning for early detection of at-risk learners in Massive Open Online Courses.

Raghad Al-Shabandar

PhD thesis, 2019

Detecting At-Risk Students With Early Interventions Using Machine Learning Techniques.

Raghad Al-Shabandar, Abir Jaafar Hussain, Panos Liatsis, Robert Keight

IEEE Access, 2019

The Application of Artificial Intelligence in Financial Compliance Management.

Raghad Al-Shabandar, Gaye Lightbody, Fiona Browne, Jun Liu, Haiying Wang, Huiru Zheng

Proceedings of the 2019 International Conference on Artificial Intelligence and Advanced Manufacturing, 2019

2018

Analyzing Learners Behavior in MOOCs: An Examination of Performance and Motivation Using a Data-Driven Approach.

Raghad Al-Shabandar, Abir Jaafar Hussain, Panos Liatsis, Robert Keight

IEEE Access, 2018

The Application of Gaussian Mixture Models for the Identification of At-Risk Learners in Massive Open Online Courses.

Raghad Al-Shabandar, Abir Hussain, Robert Keight, Andy Laws, Thar Baker

Proceedings of the 2018 IEEE Congress on Evolutionary Computation, 2018

2017

Machine learning approaches to predict learning outcomes in Massive open online courses.

Raghad Al-Shabandar, Abir Hussain, Andy Laws, Robert Keight, Janet Lunn, Naeem Radi

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Towards the Differentiation of Initial and Final Retention in Massive Open Online Courses.

Raghad Al-Shabandar, Abir Hussain, Andy Laws, Robert Keight, Janet Lunn

Proceedings of the Intelligent Computing Theories and Application, 2017