1.204 Computer Modeling: From Human Mobility to Transportation Networks
Introduces methods for modeling individual travels at a country scale. Reviews basic concepts of data analysis, modeling, and visualization techniques. Topics include data mining to identify the structure inherent in daily behavior; introduction to fractals, random walks and methods to analyze trajectories. Algorithms to model and characterize complex networks, and their applications to daily commuting, air travels, and roads. Includes weekly open laptop exercises based on the data sets and methods from the research papers covered in class. Exposes students to the current challenges and opportunities in networks applied to human mobility.
1.204 will be offered this semester (Spring 2019). It is instructed by M. C. Gonzalez.
This class counts for a total of 12 credits. This is a graduate-level class.
You can find more information at the http://www.google.com/search?&q=MIT+%2B+1.204&btnG=Google+Search&inurl=https site or on the 1.204 Stellar site.
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