Applying Rough Set Theory to Find Relationships between Personal Demographic Attributes and Long Distance Travel Mode Choices

This study investigates the feasibility of applying rough set theory to find relationships between personal demographic attributes and long distance travel mode choices. Originated from artificial intelligence, the rough set theory has been applied to classify objects and discover hidden facts from incomplete information system without the constraints of statistical assumptions. Also it has the ability to extract decision rules expressed in natural language to help policymakers in the decision making process. This paper analyzed the collected data by surveys based on the rough set theory and the results of validation test were very promising, which showed that the induced decision rules could represent the relationships between data with accuracy of 74.59%.