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Springer - Bayesian Networks for Reliability Engineering Book

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Description

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.

Key Features

Comprehensive review of Bayesian network applications in reliability over the last ten years.

Detailed examination of twelve important issues in BN-based reliability methodologies.

In-depth coverage of BN structure modeling and BN parameter modeling techniques.

Exploration of essential processes including BN inference, validation, and verification.

Focus on engineering systems to provide practical context for probabilistic modeling.

Valuable resource for researchers studying probabilistic knowledge representation and inference.

Product Specifications

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

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No barcode data available

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