Publications

Adrian Eisenmann, Tim Streubel, und Krzysztof Rudion. Power Quality Prediction by way of Parallel Computing - A New Approach Based On A Long Short-Term Memory Network. 2019. [PUMA: forecasting myown power prediction quality]

Adrian Eisenmann, Tim Streubel, und Krzysztof Rudion. PQ classification by way of parallel computing - A sensitivity analysis for a real-time LSTM approach using waveform and RMS data. 2019. [PUMA: Analysis Classification LSTM Power Quality Sensitivity]

Adrian Eisenmann, Tim Streubel, und Krzysztof Rudion. Development of Handy Tools for Power Quality Analysis. 2019. [PUMA: Power Quality Tools]

Adrian Eisenmann, Tim Streubel, und Krzysztof Rudion. PQ Prediction by Way of Parallel Computing - Benchmark and Sensitivity Analysis for Classical Machine Learning Approaches. 2019. [PUMA: Forecasting Learning Machine Power Quality Series Time myown]