Outputs (3)

Keep Your Distance: Determining Sampling and Distance Thresholds in Machine Learning Monitoring (2022)
Presentation / Conference Contribution
Farhad, A. H., Sorokos, I., Schmidt, A., Akram, M. N., Aslansefat, K., & Schneider, D. (2022). Keep Your Distance: Determining Sampling and Distance Thresholds in Machine Learning Monitoring. In C. Seguin, M. Zeller, & T. Prosvirnova (Eds.), Model-Based Safety and Assessment 8th International Symposium, IMBSA 2022, Proceedings. Lecture Notes in Computer Science (LNCS, volume 13525) (13525, pp. 219-234). Springer (part of Springer Nature). https://doi.org/10.1007/978-3-031-15842-1_16

Machine Learning (ML) has provided promising results in recent years across different applications and domains. However, in many cases, qualities such as reliability or even safety need to be ensured. To this end, one important aspect is to determine... Read More about Keep Your Distance: Determining Sampling and Distance Thresholds in Machine Learning Monitoring.

Automated Question-Answering for Interactive Decision Support in Operations & Maintenance of Wind Turbines (2022)
Journal Article
Chatterjee, J., & Dethlefs, N. (2022). Automated Question-Answering for Interactive Decision Support in Operations & Maintenance of Wind Turbines. IEEE Access, 10, 84710-84737. https://doi.org/10.1109/ACCESS.2022.3197167

Intelligent question-answering (QA) systems have witnessed increased interest in recent years, particularly in their ability to facilitate information access, data interpretation or decision support. The wind energy sector is one of the most promisin... Read More about Automated Question-Answering for Interactive Decision Support in Operations & Maintenance of Wind Turbines.

A Deep Learning Framework for Wind Turbine Repair Action Prediction Using Alarm Sequences and Long Short Term Memory Algorithms (2022)
Journal Article
Walker, C., Rothon, C., Aslansefat, K., Papadopoulos, Y., & Dethlefs, N. (2022). A Deep Learning Framework for Wind Turbine Repair Action Prediction Using Alarm Sequences and Long Short Term Memory Algorithms. Lecture notes in computer science, 13525 LNCS, 189-203. https://doi.org/10.1007/978-3-031-15842-1_14

With an increasing emphasis on driving down the costs of Operations and Maintenance (O &M) in the Offshore Wind (OSW) sector, comes the requirement to explore new methodology and applications of Deep Learning (DL) to the domain. Condition-based monit... Read More about A Deep Learning Framework for Wind Turbine Repair Action Prediction Using Alarm Sequences and Long Short Term Memory Algorithms.