Now showing items 1-3 of 3
A comparative study of surrogate based learning methods in solving power flow problem
Due to increasing volume of measurements in smart grids, surrogate based learning approaches for modeling the power grids are becoming popular. This paper uses regression based models to find the unknown state variables ...
Unsupervised Anomaly Detection in Multivariate Spatio-Temporal Data Using Deep Learning: Early Detection of COVID-19 Outbreak in Italy
(Ieee-Inst Electrıcal Electronıcs Engıneers Inc, 2020)
Unsupervised anomaly detection for spatio-temporal data has extensive use in a wide variety of applications such as earth science, traffic monitoring, fraud and disease outbreak detection. Most real-world time series data ...
Random CapsNet forest model for imbalanced malware type classification task
Behavior of malware varies depending the malware types, which affects the strategies of the system protection software. Many malware classification models, empowered by machine and/or deep learning, achieve superior ...