Simon Letzgus

TL;DR: An overview of the most important publications that discuss the application of ANN for condition monitoring in wind turbines and a method utilizing the Mahalanobis distance is presented, which improves the anomaly detection by considering the correlation between ANN model errors and the operating condition.

TL;DR: The leakage identification and localization algorithm (LILA) as discussed by the authors identifies potential leakages via semisupervised linear regression of pairwise sensor pressure data and provides the location of their nearest sensors.

TL;DR: An appropriate SCADA data preprocessing procedure is introduced to ensure their feasibility and conduct comprehensive comparisons across several hyperparameter choices, and the combination of Laplace kernels with a newly introduced bandwidth and regularisation-penalty selection heuristic robustly outperforms existing methods.

TL;DR: This review clarifies the fundamental conceptual differences of XAI for regression and classification tasks, establishes novel theoretical insights and analysis for XAIR, provides demonstrations of XAIR on genuine practical regression problems, and discusses challenges remaining for the field.

TL;DR: In this article, a case study for a neighborhood energy model, the load profiles were assigned to buildings in an example town using public data on locations, building age and energetic refurbishment variants.