Incorporating the rough sets theory into travel demand analysis

Abstract

This research integrates the rough sets theory into tourism demand analysis. Originated from the area of Artificial Intelligence, the rough sets theory was introduced to reveal important structures and to classify objects. A rough sets approach can capture useful information from a set of raw hybrid data and discover knowledge from the data in a form of decision rules. This makes the rough sets approach a useful classification and pattern recognition technique. Because of its ability to accommodate hybrid data and its algorithms without rigorous theoretical and statistical assumptions, the theory could complement the orthodox demand framework. This paper introduces a new rough sets approach for deriving rules from an Information Table of tourist arrivals. The induced rules were able to forecast change in demand with 87% accuracy.