Mobile user movement prediction using bayesian learning for neural networks

IWCMC 2007: Proceedings of the 2007 International Wireless Communications and Mobile Computing Conference

Volumn , Issue , 2007, Pages 191-196

  Akoush, Sherif ^a   Sameh, Ahmed ^a  

^a The American University in Cairo   (Egypt)

Author keywords

Bayesian network; Markov chain; Monte Carlo methods; Neural networks

Indexed keywords

BAYESIAN NETWORKS; LEARNING SYSTEMS; MARKOV PROCESSES; MONTE CARLO METHODS; NEURAL NETWORKS; USER INTERFACES; WI-FI;

MOBILE USERS; MOVEMENT PREDICTION; PREDICTION ACCURACY;

TRACKING (POSITION);

EID: 36849052330     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1280940.1280982     Document Type: Conference Paper

References (6)

1. Hassan Karimi and Xiong Liu. A Predictive Location Model for Location-Based Services. GIS'03, November 7-8, 2003, New Orleans, Louisiana, USA.
2. Alejandro Quintero. A User Pattern Learning Strategy for Managing Users' Mobility in UMTS Networks. IEEE Transactions on Mobile Computing, VOL. 4, NO. 6, November/December 2005.
3. Jarno Vanhatalo and Aki Vehtari. MCMC Methods for MLP-network and Gaussian Process and Stuff- A documentation for Matlab Toolbox MCMCstuff. Laboratory of Computational Engineering, Helsinki University of Technology.
4. Radford Neal. Bayesian Methods for Machine Learning. NIPS Tutorial, 13 December 2004, University of Toronto.
5. Jouko Lampinen and Aki Vehtari. Bayesian Approach for Neural Networks - Review and Case Studies. Laboratory of Computational Engineering, Helsinki University of Technology.
6. Aki Vehtari, Simo Särkkä, and Jouko Lampinen. On MCMC Sampling in Bayesian MLP Neural Networks. Laboratory of Computational Engineering, Helsinki University of Technology.