Time Series Analysis: Forecasting and Control
Time Series Analysis: Forecasting and Control
Modeling Moving Objects over Multiple Granularities
Annals of Mathematics and Artificial Intelligence
W4: Who? When? Where? What? A Real Time System for Detecting and Tracking People
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Geo-temporal tracking and analysis of tourist movement
Mathematics and Computers in Simulation - Special issue: Second special issue: Selected papers of the MSSANZ/IMACS 15th biennial conference on modelling and simulation
Efficient mining of group patterns from user movement data
Data & Knowledge Engineering
Application of ant K-means on clustering analysis
Computers & Mathematics with Applications
Mining travel patterns from GPS-tagged photos
MMM'11 Proceedings of the 17th international conference on Advances in multimedia modeling - Volume Part I
Mining Travel Patterns from Geotagged Photos
ACM Transactions on Intelligent Systems and Technology (TIST)
Hi-index | 0.00 |
This paper presents a novel method for modelling the spatio-temporal movements of tourists at the macro-level using Markov chains methodology. Markov chains are used extensively in modelling random phenomena which results in a sequence of events linked together under the assumption of first-order dependence. In this paper, we utilise Markov chains to analyse the outcome and trend of events associated with spatio-temporal movement patterns. A case study was conducted on Phillip Island, which is situated in the state of Victoria, Australia, to test whether a stationary discrete absorbing Markov chain could be effectively used to model the spatio-temporal movements of tourists. The results obtained showed that this methodology can indeed be effectively used to provide information on tourist movement patterns. One significant outcome of this research is that it will assist park managers in developing better packages for tourists, and will also assist in tracking tourists' movements using simulation based on the model used.