5 papers
An Innovative Next Activity Prediction Using Process Entropy and Dynamic Attribute-Wise-Transformer in Predictive Business Process Monitoring
Hadi Zare, Mostafa Abbasi, Maryam Ahang +1
Next activity prediction in predictive business process monitoring is crucial for operational efficiency and informed decision-making. While machine learning and Artificial Intelli…
Intelligent Condition Monitoring of Industrial Plants: An Overview of Methodologies and Uncertainty Management Strategies
Maryam Ahang, Todd Charter, Mostafa Abbasi +3
Condition monitoring is essential for ensuring the safety, reliability, and efficiency of modern industrial systems. With the increasing complexity of industrial processes, artific…
An Innovative Data-Driven and Adaptive Reinforcement Learning Approach for Context-Aware Prescriptive Process Monitoring
Mostafa Abbasi, Maziyar Khadivi, Maryam Ahang +3
The application of artificial intelligence and machine learning in business process management has advanced significantly, however, the full potential of these technologies remains…
Multi-Channel Swin Transformer Framework for Bearing Remaining Useful Life Prediction
Ali Mohajerzarrinkelk, Maryam Ahang, Mehran Zoravar +2
Precise estimation of the Remaining Useful Life (RUL) of rolling bearings is an important consideration to avoid unexpected failures, reduce downtime, and promote safety and effici…
Feature-Weighted MMD-CORAL for Domain Adaptation in Power Transformer Fault Diagnosis
Hootan Mahmoodiyan, Maryam Ahang, Mostafa Abbasi +1
Ensuring the reliable operation of power transformers is critical to grid stability. Dissolved Gas Analysis (DGA) is widely used for fault diagnosis, but traditional methods rely o…