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.
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.

Intelligent Reliability and Maintainability of Energy Infrastructure Assets
148
Intelligent Reliability and Maintainability of Energy Infrastructure Assets
148Product Details
ISBN-13: | 9783031299612 |
---|---|
Publisher: | Springer Nature Switzerland |
Publication date: | 05/04/2023 |
Series: | Studies in Systems, Decision and Control , #473 |
Edition description: | 2023 |
Pages: | 148 |
Product dimensions: | 6.10(w) x 9.25(h) x (d) |