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Titlebook: Bayesian Networks for Reliability Engineering; Baoping Cai,Yonghong Liu,Lei Jiang Book 2020 Springer Nature Singapore Pte Ltd. 2020 Bayesi

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發(fā)表于 2025-3-21 18:19:07 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Bayesian Networks for Reliability Engineering
影響因子2023Baoping Cai,Yonghong Liu,Lei Jiang
視頻videohttp://file.papertrans.cn/182/181867/181867.mp4
發(fā)行地址Provides a detailed review of the BN-based reliability methodologies.Presents important theoretical methods for BN-based reliability.Uses 12 practical engineering cases to illustrate the proposed meth
圖書封面Titlebook: Bayesian Networks for Reliability Engineering;  Baoping Cai,Yonghong Liu,Lei Jiang Book 2020 Springer Nature Singapore Pte Ltd. 2020 Bayesi
影響因子?.This book presents a bibliographical review of the use of Bayesian networks in reliability over the last decade. Bayesian network (BN) is considered to be one of the most powerful models in probabilistic knowledge representation and inference, and it is increasingly used in the field of reliability. After focusing on the engineering systems, the book subsequently discusses twelve important issues in the BN-based reliability methodologies, such as BN structure modeling, BN parameter modeling, BN inference, validation, and verification. As such, it is a valuable resource for researchers and practitioners in the field of reliability engineering..
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發(fā)表于 2025-3-22 00:14:38 | 只看該作者
Luis Guerrero Martínez,Leticia Valadezworks (DBNs). A three-state Markov model is constructed to represent the state transition relationship of no faults, intermittent faults, and permanent faults for PV components. The model is subsequently fused into the DBNs. The reliability and availability of three simple PV systems with centralize
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978-981-13-6518-8Springer Nature Singapore Pte Ltd. 2020
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Application of Bayesian Networks in Reliability Evaluation,ility evaluation. This paper presents a bibliographic review of BNs that have been proposed for reliability evaluation in the last decades. Studies are classified from the perspective of the objects of reliability evaluation, i.e., hardware, structures, software, and humans. For each classification,
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