Hochschule Bonn-Rhein-Sieg

Publikationsserver der Hochschule Bonn-Rhein-Sieg - pub H-BRS
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    7939 research outputs found

    Focus on what matters: improved feature selection techniques for personal thermal comfort modelling

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    Occupants' personal thermal comfort (PTC) is indispensable for their well-being, physical and mental health, and work efficiency. Predicting PTC preferences in a smart home can be a prerequisite to adjusting the indoor temperature for providing a comfortable environment. In this research, we focus on identifying relevant features for predicting PTC preferences. We propose a machine learning-based predictive framework by employing supervised feature selection techniques. We apply two feature selection techniques to select the optimal sets of features to improve the thermal preference prediction performance. The experimental results on a public PTC dataset demonstrated the efficiency of the feature selection techniques that we have applied. In turn, our PTC prediction framework with feature selection techniques achieved state-of-the-art performance in terms of accuracy, Cohen's kappa, and area under the curve (AUC), outperforming conventional methods

    Richtlinie zur Korruptionsprävention der Hochschule Bonn-Rhein-Sieg vom 15.02.2022

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    Modellbildung-und-Simulation: Online Lehrbuch

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    Dies ist ein interaktives Übungsbuch zur Vorlesung Modellbildung und Simulation an der Hochschule Bonn-Rhein-Sieg. Es dient zur Übermittlung von Kenntnissen der Modellierung und Simulation ingenieurstechnischer Probleme unter der Verwendung von Matlab bzw. Octave

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    Publikationsserver der Hochschule Bonn-Rhein-Sieg - pub H-BRS is based in Germany
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