6 citations · 7 across the 3 of their papers we have counts for
4 papers
ReCycle: Fast and Efficient Long Time Series Forecasting with Residual Cyclic Transformers
Arvid Weyrauch, Thomas Steens, Oskar Taubert +6
Transformers have recently gained prominence in long time series forecasting by elevating accuracies in a variety of use cases. Regrettably, in the race for better predictive perfo…
Electricity Demand Forecasting with Hybrid Statistical and Machine Learning Algorithms: Case Study of Ukraine
Tatiana Gonzalez Grandon, Johannes Schwenzer, Thomas Steens +1
This article presents a novel hybrid approach using statistics and machine learning to forecast the national demand of electricity. As investment and operation of future energy sys…
A Non-Intrusive Load Monitoring Approach for Very Short Term Power Predictions in Commercial Buildings
Karoline Brucke, Stefan Arens, Jan-Simon Telle +4
This paper presents a new algorithm to extract device profiles fully unsupervised from three phases reactive and active aggregate power measurements. The extracted device profiles…
A Forecast Based Load Management Approach For Commercial Buildings -- Comparing LSTM And Standardized Load Profile Techniques
Thomas Steens, Jan-Simon Telle, Benedikt Hanke +5
Load-forecasting problems have already been widely addressed with different approaches, granularities and objectives. Recent studies focus not only on deep learning methods but als…