Statistical modeling of the required space for inland vessels
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
Abstract
One of the most important factors in the design of fairways for inland waterway traffic is the width vessels require for safe navigation. This is not only given by the constant dimensions of the vessel, but highly influenced by the vessel’s surroundings. Furthermore, it heavily depends on the vessel’s speed being regulated by the steersman. We investigate a complex physical model given as a “black-box,” that describes these dependencies and look for simpler, purely data driven regression based approaches: parametric, non-parametric, and kernel supervised principal component. Some models allow to reduce the dimensionality and identify the most important influencing variables.
Details
Original language | English |
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Pages (from-to) | 167-190 |
Number of pages | 24 |
Journal | Communications in Statistics : Case Studies Data Analysis and Applications |
Volume | 6 |
Issue number | 2 |
Publication status | Published - 2 Apr 2020 |
Peer-reviewed | Yes |
External IDs
ORCID | /0000-0002-8909-4861/work/149081765 |
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Keywords
ASJC Scopus subject areas
Keywords
- Kernel supervised, nonlinear dependency, principal components, waterway traffic