%0 Thesis %1 krauss17 %A Krauss, Torsten %C Am Hubland, Informatikgebäude, 97074 Würzburg, Germany %D 2017 %K Automated_model_learning LibReDE Multi-criteria_optimization Online_monitoring_and_forecasting Self-aware-computing Statistical_estimation_and_machine_learning Supervised_by_Nikolas_Herbst Thesis_supervised_by_Johannes_Grohmann Thesis_supervised_by_SE_member Tool descartes se2_mastersthesis t_studentthesis %T Evaluating Approaches for Online Resource Demand Estimation

@mastersthesis{krauss17, added-at = {2020-04-14T18:06:12.000+0200}, address = {Am Hubland, Informatikgeb{\"a}ude, 97074 W{\"u}rzburg, Germany}, author = {Krauss, Torsten}, biburl = {https://www.bibsonomy.org/bibtex/27ac4ba1a7f778253aae4165b864bdc99/joh.grohmann}, interhash = {1373bed783d4a1d77caa6675c052c693}, intrahash = {7ac4ba1a7f778253aae4165b864bdc99}, keywords = {Automated_model_learning LibReDE Multi-criteria_optimization Online_monitoring_and_forecasting Self-aware-computing Statistical_estimation_and_machine_learning Supervised_by_Nikolas_Herbst Thesis_supervised_by_Johannes_Grohmann Thesis_supervised_by_SE_member Tool descartes se2_mastersthesis t_studentthesis}, month = {September}, school = {University of W{\"u}rzburg}, timestamp = {2020-10-06T11:06:12.000+0200}, title = {{Evaluating Approaches for Online Resource Demand Estimation}}, type = {{Master Thesis}}, year = 2017 }