Mixed Skewness Probability Modeling and Extreme Value Predicting for Physical System Input/Output Based on Full Bayesian Generalized Maximum-Likelihood Estimation

Dynamic parameterization of the statistical characteristics of structural systems' measured input and output data is an important task for the digital twin modeling and intelligent risk assessment of transportation infrastructures. Characteristics of mixed skewness probability are common in str...

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Bibliographic Details
Published in:	IEEE transactions on instrumentation and measurement Vol. 73; p. 1
Main Authors:	Zhang, Xiaonan, Ding, Youliang, Zhao, Hanwei, Yi, Letian, Guo, Tong, Li, Aiqun, Zou, Yang
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.01.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Accuracy Bayes methods Bayesian analysis Bridges Digital twin Digital twins Extreme value prediction Extreme values Intelligent monitoring Load modeling Maximum likelihood estimation Mixed probability modeling Modelling Parameterization Parameterization of dynamic system Predictive models Probabilistic logic Probabilistic models Probability theory Risk assessment Skewness Statistical analysis Transportation infrastructures Vehicle dynamics
ISSN:	0018-9456, 1557-9662
Online Access:	Get full text
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