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  ---
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  title: Master Thesis
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  ---
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  Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  title: Master Thesis
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+ emoji: πŸ“š
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  Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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+ ## Overview
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+ This is the web verison of my master thesis - the title of the master thesis is: Flow predictions using control-oriented cluster-based network modeling.
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+ The web version of the master thesis, available at [https://jav-ed.github.io/master_Thesis/](https://jav-ed.github.io/master_Thesis/) and is aimed to offer an interactive reading experience.
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+
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+ <br/>
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+ <br/>
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+ <p align="center">
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+ <img src="https://jav-ed.github.io/master_Thesis/Data/6_Html_Data/1_Logo_Img/1_Tornado.svg" />
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+ </p>
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+ <br/>
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+ <br/>
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+ type: Master thesis - TU Braunschweig (Germany)\newline
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+ title: Flow predictions using control-oriented cluster-based network modeling\newline
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+ access: https://jav-ed.github.io/master_Thesis/ πŸ“š
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+ The used license is: [![Hippocratic License HL3-BDS-CL-ECO-EXTR-MEDIA-MIL-SV-XUAR](https://img.shields.io/static/v1?label=Hippocratic%20License&message=HL3-BDS-CL-ECO-EXTR-MEDIA-MIL-SV-XUAR&labelColor=5e2751&color=bc8c3d)](https://firstdonoharm.dev/version/3/0/bds-cl-eco-extr-media-mil-sv-xuar.html)
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+
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+
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+ ## Abstract
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+ Note, to see the content without \gls{var}, please have a look at [https://jav-ed.github.io/master_Thesis/Data/1_Writing/0_Deco/2_1_Abstract.html](https://jav-ed.github.io/master_Thesis/Data/1_Writing/0_Deco/2_1_Abstract.html).
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+ In this master thesis, a data-driven modeling technique is proposed.
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+ It enables making predictions for general dynamic systems for unknown model parameter values or operating conditions.
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+ The tool is denoted as \gls{cnmc}.
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+ The most recent developed version delivered promising results for the chaotic Lorenz system [@lorenz1963deterministic].
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+ Since, the earlier work was restricted to the application of only one dynamical system, with this contribution the first major improvement was to allow \gls{cnmc} to be utilized for any general dynamical system.
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+ For this, \gls{cnmc} was written from scratch in a modular manner.
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+ The limitation of the number of the dimension and the shape of the trajectory of the dynamical systems are removed.
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+ Adding a new dynamic system was designed such that it should be as straightforward as possible.
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+ To affirm this point, 10 dynamic systems, most of which are chaotic systems, are included by default.
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+ To be able to run \gls{cnmc} on arbitrary dynamic systems in an automated way, a parameter study for the modal decomposition method \gls{nmf} was implemented.
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+ However, since a single \gls{nmf} solution took up to hours, a second option was added, i.e., \gls{svd}.
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+ With \gls{svd} the most time-consuming task could be brought to a level of seconds.
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+ The improvements introduced, allow \gls{cnmc} to be executed on a general dynamic system on a normal computer in a reasonable time.
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+ Furthermore, \gls{cnmc} comes with its integrated post-processor in form of HTML files to inspect the generated plots in detail.
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+ All the parameters used in \gls{cnmc} some additional beneficial features can be controlled via one settings file.