Data visualization and optimization methods for placing entities within urban areas
Name
894353952-MIT.pdf
Description
Full printable version
Size
5.06 MB
Format
Adobe PDF
Checksum (MD5)
489b6383d950e32154b612ccf61fe1e3
Author(s)
Ramkrishnan, Pranav
Advisor(s)
Sepandar D. Kamvar.
Date Issued
2014
Publisher
Massachusetts Institute of Technology
Abstract
In the first part of this thesis, I present a portfolio of web-based visualizations that illustrate different data-driven ideas about urban environments. These visualizations are intended to provide the user with unique perspectives about cities and the way they function. I detail the conceptualization, data aspects, and implementation of each of these map visualizations. In the second part of this thesis, I describe an interesting optimization problem of placing entities such as trees or shops within a city. The location of these placements needs to conform to certain constraints enforced by spatial distributions of variables such as population, income, travel times, etc. I then present a heuristic-based optimization strategy, that combines some aspects of Gradient-ascent and Simulated Annealing, to address this problem and attempt to generalize this approach to finding the optimal placements of any entity within a given city. I present some initial results of my optimization algorithm and discuss ways in which it can be further improved.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014.
Cataloged from PDF version of thesis.
Includes bibliographical references (page 83).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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