Axioms for probability and belief-function propagation
Readings in uncertain reasoning
Mixtures of Truncated Exponentials in Hybrid Bayesian Networks
ECSQARU '01 Proceedings of the 6th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Simulation Approaches to General Probabilistic Inference on Belief Networks
UAI '89 Proceedings of the Fifth Annual Conference on Uncertainty in Artificial Intelligence
Inference in hybrid Bayesian networks using dynamic discretization
Statistics and Computing
Inference in hybrid Bayesian networks with mixtures of truncated exponentials
International Journal of Approximate Reasoning
Nonuniform dynamic discretization in hybrid networks
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Engineering Applications of Artificial Intelligence
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We present a hybrid Bayesian network (HBN) framework to model the availability of renewable systems. We use an approximate inference algorithm for HBNs that involves dynamically discretizing the domain of all continuous variables and use this to obtain accurate approximations for the renewal or repair time distributions for a system. We show how we can use HBNs to model corrective repair time, logistics delay times and scheduled maintenance time distributions and combine these with time-to-failure distributions to derive system availability. Example models are presented and are accompanied by detailed descriptions of how repair (renewal) distributions might be modelled using HBNs.