The use of Bayesian learning of neural networks for mobile user position prediction

Proceedings of The 7th International Conference on Intelligent Systems Design and Applications, ISDA 2007

Volumn , Issue , 2007, Pages 441-446

  Akoush, Sherif ^a   Sameh, Ahmed ^a  

^a The American University in Cairo   (Egypt)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BAYESIAN NETWORKS; CELLULAR NEURAL NETWORKS; CELLULAR TELEPHONE SYSTEMS; DISTRIBUTED COMPUTER SYSTEMS; FORECASTING; GLOBAL SYSTEM FOR MOBILE COMMUNICATIONS; IMAGE CLASSIFICATION; INTELLIGENT CONTROL; INTELLIGENT SYSTEMS; INTERNET; LOCATION; MOBILE DEVICES; NETWORK MANAGEMENT; PAGING SYSTEMS; PROBABILITY DISTRIBUTIONS; PUBLIC KEY CRYPTOGRAPHY; STANDARDS; SYSTEMS ANALYSIS; TELECOMMUNICATION; TELECOMMUNICATION EQUIPMENT; TELECOMMUNICATION SYSTEMS; UBIQUITOUS COMPUTING; VEGETATION; WIRELESS NETWORKS; WIRELESS TELECOMMUNICATION SYSTEMS;

BACK PROPAGATION (BP); BAYESIAN; BAYESIAN LEARNING (BL); BAYESIAN NEURAL NETWORKS; CELLULAR NETWORKS; INTERNATIONAL CONFERENCES; KEY OPERATIONS; LOCATION UPDATE (LU); MOBILE USERS; MOBILITY MANAGEMENT (MM); NETWORK WEIGHTS; NEURAL NETWORK TECHNIQUES; PARALLEL IMPLEMENTATIONS; POSTERIOR DISTRIBUTIONS; PROBABILITY MODELING; SIGNALING COSTS; SYSTEMS DESIGN; TO MANY; TRACKING MOBILE USERS; TRADE OFFS; UBIQUITOUS COMMUNICATIONS; WIRELESS/MOBILE NETWORKS;

NEURAL NETWORKS;

EID: 48349120847     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISDA.2007.4389648     Document Type: Conference Paper

References (4)

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, 2006.
4. Radford Neal. Bayesian Methods for Machine Learning. NIPS Tutorial, 13 December 2004, University of Toronto.