Authors: Brenda McCabe
Addresses: Department of Civil Engineering, University of Toronto, Toronto, Ontario M5S 1A4, Canada
Abstract: A relatively new form of artificial intelligence, namely belief networks, provides flexible modelling structures for capturing and evaluating uncertainty. The belief network consists of nodes to model the variables of the domain, and arcs to represent conditional dependence between variables. The development of a belief network requires four major steps: variable definition, identification of conditional relationships, definition of the states of the variables, and determination of the probabilistic values of the conditional relationships. The evaluation of a singly connected belief network is provided. Two applications for belief networks are discussed. One application involves the integration of a belief network with computer simulation resulting in an automated system for performance improvement. The second application is focused on assessing productivity of construction operations.
Keywords: belief networks; uncertainty in reasoning; decision support; probabilistic modelling; simulation modelling; performance improvement.
International Journal of Technology Management, 2001 Vol.21 No.3/4, pp.257-270
Published online: 08 Jul 2003 *Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article