Multivariate time series classification in time-sensitive environments using deep learning
Elektriker och servicepersonal vistas frekvent inom områden där högspänningskomponenter förekommer. Detta arbete undersöker möjligheten att utnyttja maskininlärning, mer specifikt djupinlärning som grund i ett system som varnar elektriker och servicepersonal om strömförande komponenter och ledningar.In this thesis, sensor data from substations and distribution centrals in Sweden and Germany is analysed and used to predict the voltage environment which the device is within. The theory needed for understanding the measured values is explained, and the notion of multivariate time series is introduced along with the reason for using deep learning to solve the problem at hand. Several ways of extr
