Intelligent Reliability and Maintainability of Energy Infrastructure Assets (Studies in Systems, Decision and Control, 473) von Li, He; Peng, Weiwen; Adumene, Sidum; Yazdi, Mohammad: New (2024)

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2023rd edition NO-PA16APR2015-KAP.

Bestandsnummer des Verk�ufers 26401133228

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Bibliografische Details

Titel: Intelligent Reliability and Maintainability of Energy Infrastructure Assets (Studies in Systems, Decision and Control, 473)
Verlag: Springer
Erscheinungsjahr: 2024
Sprache: Englisch
ISBN-10: 3031299647
ISBN-13: 9783031299643
Einband: Softcover
Zustand: New

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Inhaltsangabe

This book reviews and presents several advanced approaches to energy infrastructure assets' intelligent reliability and maintainability. Each introduced model provides case studies indicating high efficiency, robustness, and applicability, allowing readers to utilize them in their understudy intelligent reliability and maintainability of energy infrastructure assets domains.

The book begins by reviewing the state-of-the-art research on the reliability and maintainability of energy infrastructure assets and emphasizes the intelligent tools and methods proposed from a bibliometric and literature review point of view. It then progresses logically, dedicating a chapter to each approach, dynamic Bayesian modeling network, convolutional neural network model, global average pooling-based convolutional Siamese network, an integrated probabilistic model for the failure consequence assessment, and more.

This book interests professionals and researchers working in reliability and maintainability and postgraduate and undergraduate students studying intelligent reliability applications and energy infrastructure assets' maintainability.

Von der hinteren Coverseite

This book reviews and presents several advanced approaches to energy infrastructure assets' intelligent reliability and maintainability. Each introduced model provides case studies indicating high efficiency, robustness, and applicability, allowing readers to utilize them in their understudy intelligent reliability and maintainability of energy infrastructure assets domains.

The book begins by reviewing the state-of-the-art research on the reliability and maintainability of energy infrastructure assets and emphasizes the intelligent tools and methods proposed from a bibliometric and literature review point of view. It then progresses logically, dedicating a chapter to each approach, dynamic Bayesian modeling network, convolutional neural network model, global average pooling-based convolutional Siamese network, an integrated probabilistic model for the failure consequence assessment, and more.

This book interests professionals and researchers working in reliability and maintainability and postgraduate and undergraduate students studying intelligent reliability applications and energy infrastructure assets' maintainability.

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