Springer - Bayesian Networks for Reliability Engineering Book

Bayesian Networks for Reliability Engineering by Springer provides a comprehensive bibliographical review of how Bayesian networks have been applied to reliability over the last decade. As one of the most powerful models for probabilistic knowledge representation and inference, Bayesian networks are becoming a standard tool in the reliability field. This book starts by focusing on engineering systems before moving into a detailed discussion of twelve essential topics. It covers vital methodologies including BN structure modeling, BN parameter modeling, BN inference, validation, and verification. It serves as a practical resource for those looking to understand the evolving role of probabilistic models in modern engineering. Whether you are researching new methodologies or applying existing models to complex systems, this text offers the technical background necessary to master BN-based reliability approaches.