University of Twente Student Theses


Data-driven kitchen fire prediction based on environmental variables

Leeuwen, D. van (2022) Data-driven kitchen fire prediction based on environmental variables.

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Abstract:Efficient prediction is crucial to preventing harm caused by kitchen fires. In this paper, we propose a kitchen fire model using the data collected by the Twente Fire Brigade. Specifically, we utilize the permutation techniques of random forests and perform classic stepwise regression methods to select the explainable environmental variables. For unstable results, we propose stabilization methods. Moreover, we build a Poisson generalized linear model which successfully captures the spatial patterns seen in the data.
Item Type:Essay (Bachelor)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:31 mathematics
Programme:Applied Mathematics BSc (56965)
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