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Biologically Inspired Model of the Swiss Railroad Network Depending on Population Growth

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MATLAB HS12 – Research Plan

  • Group Name: Slimy
  • Group participants names: Böttcher Lucas, Roth Simon, Schär Gabriela
  • Project Title: Trail formation with Physarum polycephalum

General Introduction

Generating a biologically inspired model of the Swiss railroad network depending on population growth. By using a biological (based on Physarum polycephalum) model, we want to simulate future scenarios of the Swiss railroad network. Probably a problem in future would be, that in fact of the population growth more people will use the public transport system. So we think it is necessary to simulate the main transport lines, to see where the system should be improved.

The Model

The mathematical model is based on (2). The urban areas (food sources) are the independent variables. By using theorems from hydro dynamics there exists three types of dependent variables for each node: conductivity, length and pressure.

As mentioned in (2), the flux prefers junctions with high efficiency (e.g. short connections). Because the flux in the system is constant, the junctions with high efficiency grow (getting thicker and more flux goes through), while the junctions with low efficiency shrink and disappear.

Fundamental Questions

  • (a) Is the simulated railroad network a good approximation of the real network?
  • (b) Are there inefficient junctions and are new junctions needed for the future?

Comment:

Question (a) should be proved with data from the swiss railroad (e.g. SBB) and some main nodes (e.g. Zurich/Bern/Geneva. By comparing the simulated matrix with the real trail matrix, we see the influence of the parameters of simulation. We see this part as our main task. If there is time after implementation and testing the software with a GIS (see Other) matrix, we want to do further tasks like (b). The efficiency is measurable, how described in (1). So the efficiency of each network is related to the total length, the average distance between nodes compared to the minimal spanning tree.

Expected Results

Because Switzerland has a special topography the model is maybe not fully adaptable. In general we assume that the junctions and their capacity show more or less the future network.

References

Research Methods

Cellular grid (matrix based on Swiss topography - GIS) with predefined rules from hydro dynamics, continuous modelling

Other

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Biologically Inspired Model of the Swiss Railroad Network Depending on Population Growth

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