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Springer Bayesian Networks for Reliability Engineering - Springer

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Description

Bayesian Networks for Reliability Engineering is a comprehensive guide to probabilistic knowledge representation and inference in modern engineering systems. This Springer publication examines the application of Bayesian networks across reliability methodologies developed over the past decade, offering researchers and practitioners a structured exploration of critical topics including BN structure modelling, parameter modelling, inference techniques, validation, and verification. The book serves as an essential resource for understanding how Bayesian networks address complex reliability challenges in engineering, bridging theory and practical implementation for those seeking to advance their expertise in probabilistic systems and machine learning approaches to reliability engineering.

Key Features

Bayesian Networks for Reliability Engineering covers twelve important methodological issues in BN-based reliability frameworks for modern engineering applications.

The Springer publication provides a decade-long bibliographical review of Bayesian network applications within the reliability engineering field.

This book addresses BN structure modelling and parameter modelling as core components of probabilistic reliability analysis.

Bayesian Networks for Reliability Engineering explores inference, validation, and verification techniques essential to deploying reliable probabilistic systems.

The text is designed specifically for researchers and practitioners seeking practical knowledge in implementing Bayesian networks for engineering reliability.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
08 March 2019
Listed Since
14 January 2019

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