Title

Identifying Hourly Traffic Patterns With Python Deep Learning

Author(s) Information

Christopher L. Leavitt, California Polytechnic State University, San Luis ObispoFollow

College - Author 1

College of Engineering

Department - Author 1

Computer Engineering Department

Degree Name - Author 1

BS in Computer Engineering

Date

6-2019

Primary Advisor

Davide Falessi

Abstract/Summary

This project was designed to explore and analyze the potential abilities and usefulness of applying machine learning models to data collected by parking sensors at a major metro shopping mall. By examining patterns in rates at which customer enter and exit parking garages on the campus of the Bellevue Collection shopping mall in Bellevue, Washington, a recurrent neural network will use data points from the previous hours will be trained to forecast future trends.

URL: https://digitalcommons.calpoly.edu/cpesp/298