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Moscow Metro Traffic Optimization

Student: Nikita Fileev

Supervisor: Dmitry Neklyudov

Faculty: Graduate School of Business

Educational Programme: Business Informatics (Bachelor)

Year of Graduation: 2019

The modern world is more and more filled with various electronic devices, sensors. In developed countries, almost everyone has a smartphone. All of those create the so-called Internet of Things, which in turn produces a colossal cloud of data. Big Data requires the invention of a unique approach for every problem case. This project aims to delve into the study of the passenger traffic of subway which is a narrow sphere of Big Data. The key idea is to develop a solution to optimize the train schedule from the standpoint of the costs of the subway and its risks both reputation and operational. This work will describe the trending approaches to modeling and work with data as well as an overview of existing methodologies and conditions and principles of their applicability.

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