Joint and individual variations in heterogeneous traffic data sets

• Main Author: Jere, Shashank Harish
• Other Authors: School of Electrical and Electronic Engineering
• Format: Final Year Project
• Language: English
• Published: 2014
• Subjects: DRNTU::Engineering::Computer science and engineering::Information systems::Models and principles
• Online Access: http://hdl.handle.net/10356/61471
• Institution: Nanyang Technological University

With a rise in the population of the world’s cities, understanding the dynamics of the commuters’ transportation patterns has become crucial in planning and management of urban facilities and services. In this paper, we explore two novel data mining techniques, namely, Joint and Individual Variation...