Zobrazeno 1 - 10
of 41
pro vyhledávání: '"Hopf, Konstantin"'
Information systems (IS) are frequently designed to leverage the negative effect of anchoring bias to influence individuals' decision-making (e.g., by manipulating purchase decisions). Recent advances in Artificial Intelligence (AI) and the explanati
Externí odkaz:
http://arxiv.org/abs/2405.04972
Publikováno v:
The 14th ACM International Conference on Future Energy Systems (e-Energy '23), June 20--23, 2023, Orlando, FL, USA
Forecasting electricity demand plays a critical role in ensuring reliable and cost-efficient operation of the electricity supply. With the global transition to distributed renewable energy sources and the electrification of heating and transportation
Externí odkaz:
http://arxiv.org/abs/2305.18550
Publikováno v:
The 14th ACM International Conference on Future Energy Systems (e-Energy '23), June 20--23, 2023, Orlando, FL, USA
Recent developments related to the energy transition pose particular challenges for distribution grids. Hence, precise load forecasts become more and more important for effective grid management. Novel modeling approaches such as the Transformer arch
Externí odkaz:
http://arxiv.org/abs/2305.10559
Autor:
Hopf, Konstantin1 (AUTHOR) konstantin.hopf@uni-bamberg.de, Müller, Oliver2 (AUTHOR) oliver.mueller@uni-paderborn.de, Shollo, Arisa3 (AUTHOR) ash.digi@cbs.dk, Thiess, Tiemo4 (AUTHOR) t.thiess@outlook.com
Publikováno v:
California Management Review. Nov2023, Vol. 66 Issue 1, p23-47. 25p.
Machine learning (ML) methods can effectively analyse data, recognize patterns in them, and make high-quality predictions. Good predictions usually come along with "black-box" models that are unable to present the detected patterns in a human-readabl
Externí odkaz:
http://arxiv.org/abs/2208.11408
The advance of Machine Learning (ML) has led to a strong interest in this technology to support decision making. While complex ML models provide predictions that are often more accurate than those of traditional tools, such models often hide the reas
Externí odkaz:
http://arxiv.org/abs/2208.11404
Autor:
Hopf, Konstantin, Reifenrath, Sascha
The amount of data for machine learning (ML) applications is constantly growing. Not only the number of observations, especially the number of measured variables (features) increases with ongoing digitization. Selecting the most appropriate features
Externí odkaz:
http://arxiv.org/abs/2111.12140
Publikováno v:
In Energy Policy October 2022 169
Publikováno v:
In Journal of Strategic Information Systems September 2022 31(3)
Autor:
Hopf, Konstantin1 (AUTHOR) konstantin.hopf@uni-bamberg.de, Weigert, Andreas1 (AUTHOR), Staake, Thorsten1 (AUTHOR)
Publikováno v:
Journal of Decision Systems. 2023, Vol. 32 Issue 2, p289-325. 37p.