Joint and individual variations in heterogeneous traffic data sets
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...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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2014
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| Online Access: | http://hdl.handle.net/10356/61471 |
| _version_ | 1811685423194308608 |
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| author | Jere, Shashank Harish |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Jere, Shashank Harish |
| author_sort | Jere, Shashank Harish |
| collection | NTU |
| description | 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 Explained (JIVE) for Integrated Analysis of Multiple Data Types, and Common Orthogonal Basis Extraction (COBE), and apply them to smart card data available for passengers in Singapore. Using Origin-Destination (O-D) passenger count matrices for two days of the week for MRT stations in Singapore, we are able to arrive at the “joint” travel patterns, i.e., patterns seen on both days, as well as “individual” travel patterns, i.e., patterns seen only on a particular day but not the other, simply from the O-D pair data for two days. The methodologies to identify, quantify and visualize the travel patterns that have been utilized and their scope been expanded in this project, could aid Transportation Authorities in short-term resource allocation and long-term facilities planning. |
| first_indexed | 2024-10-01T04:44:17Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/61471 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:44:17Z |
| publishDate | 2014 |
| record_format | dspace |
| spelling | ntu-10356/614712023-07-07T17:31:25Z Joint and individual variations in heterogeneous traffic data sets Jere, Shashank Harish School of Electrical and Electronic Engineering Singapore-MIT Alliance for Research and Technology Justin Dauwels DRNTU::Engineering::Computer science and engineering::Information systems::Models and principles 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 Explained (JIVE) for Integrated Analysis of Multiple Data Types, and Common Orthogonal Basis Extraction (COBE), and apply them to smart card data available for passengers in Singapore. Using Origin-Destination (O-D) passenger count matrices for two days of the week for MRT stations in Singapore, we are able to arrive at the “joint” travel patterns, i.e., patterns seen on both days, as well as “individual” travel patterns, i.e., patterns seen only on a particular day but not the other, simply from the O-D pair data for two days. The methodologies to identify, quantify and visualize the travel patterns that have been utilized and their scope been expanded in this project, could aid Transportation Authorities in short-term resource allocation and long-term facilities planning. Bachelor of Engineering 2014-06-10T07:46:47Z 2014-06-10T07:46:47Z 2014 2014 Final Year Project (FYP) http://hdl.handle.net/10356/61471 en Nanyang Technological University 70 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Computer science and engineering::Information systems::Models and principles Jere, Shashank Harish Joint and individual variations in heterogeneous traffic data sets |
| title | Joint and individual variations in heterogeneous traffic data sets |
| title_full | Joint and individual variations in heterogeneous traffic data sets |
| title_fullStr | Joint and individual variations in heterogeneous traffic data sets |
| title_full_unstemmed | Joint and individual variations in heterogeneous traffic data sets |
| title_short | Joint and individual variations in heterogeneous traffic data sets |
| title_sort | joint and individual variations in heterogeneous traffic data sets |
| topic | DRNTU::Engineering::Computer science and engineering::Information systems::Models and principles |
| url | http://hdl.handle.net/10356/61471 |
| work_keys_str_mv | AT jereshashankharish jointandindividualvariationsinheterogeneoustrafficdatasets |