| Feature extraction and filtering for household classification based on smart electricity meter data K Hopf, M Sodenkamp, I Kozlovkiy, T Staake Computer Science-Research and Development 31 (3), 141-148, 2016 | 37 | 2016 |
| Enhancing energy efficiency in the residential sector with smart meter data analytics K Hopf, M Sodenkamp, T Staake Electronic Markets 28 (4), 453-473, 2018 | 10 | 2018 |
| Predictive Customer Data Analytics–The Value of Public Statistical Data and the Geographic Model Transferability K Hopf, SJ Riechel, M Sodenkamp, T Staake 38. International Conference on Information Systems (ICIS), 2017 | 9 | 2017 |
| Energy Informatics for Environmental, Economic and Societal Sustainability: A Case of the Large-Scale Detection of Households With Old Heating Systems I Kozlovskiy, M Sodenkamp, K Hopf, T Staake 24th European Conference on Information Systems (ECIS), 2016 | 9 | 2016 |
| Using supervised machine learning to explore energy consumption data in private sector housing M Sodenkamp, K Hopf, T Staake Handbook of research on organizational transformations through big data …, 2014 | 9 | 2014 |
| Smart Meter Data Analytics for Enhanced Energy Efficiency in the Residential Sector M Sodenkamp, I Kozlovskiy, K Hopf, T Staake 13th International Conference on Wirtschaftsinformatik (WI2017), 2017 | 8 | 2017 |
| Energy Data Analytics for Improved Residential Service Quality and Energy Efficiency K Hopf, M Sodenkamp, I Kozlovskiy 24th European Conference on Information Systems (ECIS), 2016 | 7 | 2016 |
| Identifying the Geographical Scope of Prohibition Signs K Hopf, F Dageförde, D Wolter 12th International Conference on Spatial Information Theory, 247-267, 2015 | 7 | 2015 |
| Mining volunteered geographic information for predictive energy data analytics K Hopf Energy Informatics 1 (1), 1-21, 2018 | 5 | 2018 |
| A Decision Support System for Photovoltaic Potential Estimation K Hopf, M Kormann, M Sodenkamp, T Staake International Conference on Internet of Things and Machine Learning (IML 2017), 2017 | 5 | 2017 |
| Explaining and predicting annual electricity demand of enterprises–a case study from Switzerland C Stingl, K Hopf, T Staake Energy Informatics 1 (1), 149-166, 2018 | 2 | 2018 |
| Predictive Analytics for Energy Efficiency and Energy Retailing K Hopf Contributions of the Faculty of Information Systems and Applied Computer …, 2019 | 1 | 2019 |
| Detection of heat pumps from smart meter and open data A Weigert, K Hopf, N Weinig, T Staake Energy Informatics 3 (1), 1-14, 2020 | | 2020 |
| A Cognitive Computing Solution to Foster Retailing of Renewable Energy Systems A Weigert, K Hopf, T Staake AIS SIGGREEN Pre-ICIS Workshop, 2019 | | 2019 |
| Smart-Meter-Datenanalyse für automatisierte Energieberatungen (" Smart Grid Data Analytics")-Schlussbericht M Sodenkamp, K Hopf, I Kozlovskiy, T Staake OPUS, 2016 | | 2016 |
| Household classification using annual electricity consumption data K Hopf, M Sodenkamp, I Kozlovskiy, T Staake 4th D-A-CH Energieinformatik Conference, 2015 | | 2015 |
| SmartLoad–Smart Meter Data Analytics for Enhanced Energy Efficiency in the Residential Sector A Weigert, K Hopf, T Staake, A Rast, J Marckhoff Otto-Friedrich-Universität, 0 | | |
| Methoden der Energiedatenanalyse: Schlussbericht; Vorhaben im Rahmen des Eurostars Projekts E! 9859 BENginell" Energy Data Analytics: Increasing Service Quality and Energy … K Hopf, T Staake Otto-Friedrich-Universität Bamberg, 0 | | |
Thorsten StaakeProfessor, Chair of Information Systems and Energy Efficient Systems, University of BambergVerified email at uni-bamberg.de
