Machine Learning in Transportation Data Analytics

Parth Bhavsar; Ilya Safro; Nidhal Bouaynaya; Robi Polikar; Dimah Dera

doi:10.1016/B978-0-12-809715-1.00012-2

Machine Learning in Transportation Data Analytics

Parth Bhavsar, Ilya Safro, Nidhal Bouaynaya, Robi Polikar, Dimah Dera

Research output: Chapter in Book/Report/Conference proceeding › Chapter

94 Scopus citations

Abstract

The primary goal of this chapter is to provide a basic understanding of the machine learning methods for transportation-related applications. This chapter discusses how the machine learning methods can be utilized to improve performance of transportation data analytics tools. The chapter focuses on selected machine learning methods and importance of quality and quantity of available data. An example is provided along with the MATLAB code to present how the machine learning method can improve performance of data-driven transportation system by predicting a speed of the roadway section.

Original language	English (US)
Title of host publication	Data Analytics for Intelligent Transportation Systems
Publisher	Elsevier Inc.
Pages	283-307
Number of pages	25
ISBN (Electronic)	9780128098516
ISBN (Print)	9780128097151
DOIs	https://doi.org/10.1016/B978-0-12-809715-1.00012-2
State	Published - Apr 14 2017

All Science Journal Classification (ASJC) codes

General Social Sciences

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10.1016/B978-0-12-809715-1.00012-2

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BT - Data Analytics for Intelligent Transportation Systems

PB - Elsevier Inc.

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Machine Learning in Transportation Data Analytics

Abstract

All Science Journal Classification (ASJC) codes

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