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.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
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.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
EUR 23,00 per la spedizione da Germania a U.S.A.
Destinazione, tempi e costiDa: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 164 pp. Englisch. Codice articolo 9783031299643
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Da: moluna, Greven, Germania
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 reade. Codice articolo 1612335588
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Da: AHA-BUCH GmbH, Einbeck, Germania
Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Codice articolo 9783031299643
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Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. 2023rd edition NO-PA16APR2015-KAP. Codice articolo 26401133228
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 164 pp. Englisch. Codice articolo 9783031299643
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Da: Majestic Books, Hounslow, Regno Unito
Condizione: New. Print on Demand. Codice articolo 396325235
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Da: Biblios, Frankfurt am main, HESSE, Germania
Condizione: New. PRINT ON DEMAND. Codice articolo 18401133222
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