Web-based data visualization and optimization methods for applications in urban planning
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2016
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| Online Access: | http://hdl.handle.net/1721.1/100667 |
| _version_ | 1826202368650248192 |
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| author | Manassra, Wesam |
| author2 | Sepandar D. Kamvar. |
| author_facet | Sepandar D. Kamvar. Manassra, Wesam |
| author_sort | Manassra, Wesam |
| collection | MIT |
| description | Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014. |
| first_indexed | 2024-09-23T12:06:22Z |
| format | Thesis |
| id | mit-1721.1/100667 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T12:06:22Z |
| publishDate | 2016 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1006672019-04-11T06:00:02Z Web-based data visualization and optimization methods for applications in urban planning Manassra, Wesam Sepandar D. Kamvar. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014. Cataloged from PDF version of thesis. Includes bibliographical references (pages 95-96). This thesis deals with the problem of enhancing the understanding of urban information through interactive data-driven visualization and planning tools. In the first part of the thesis, I present a series of web-based data visualizations through maps to provide users with thorough understanding of their living environments, and highlight patterns and trends to raise their awareness of how cities evolve over time. In the second part, I focus on tools that support the planning of interventions on the urban level. Specifically, I tackle the problem of selecting the most optimal locations for placing new entities within the city using a modified k-means algorithm. by Wesam Manassra. M. Eng. 2016-01-04T20:51:39Z 2016-01-04T20:51:39Z 2014 2014 Thesis http://hdl.handle.net/1721.1/100667 932126732 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 96 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Manassra, Wesam Web-based data visualization and optimization methods for applications in urban planning |
| title | Web-based data visualization and optimization methods for applications in urban planning |
| title_full | Web-based data visualization and optimization methods for applications in urban planning |
| title_fullStr | Web-based data visualization and optimization methods for applications in urban planning |
| title_full_unstemmed | Web-based data visualization and optimization methods for applications in urban planning |
| title_short | Web-based data visualization and optimization methods for applications in urban planning |
| title_sort | web based data visualization and optimization methods for applications in urban planning |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/100667 |
| work_keys_str_mv | AT manassrawesam webbaseddatavisualizationandoptimizationmethodsforapplicationsinurbanplanning |