Abstract
The paper introduces the main measures of uncertainty and discusses some of the problems associated with conventional uncertainty propagation methods, such as those based on independent probabilities and the methods used with certainty factors, belief, and possibility functions. Some examples show the importance of the associated errors. Alternative methods, such as log‐linear regression and causal networks or influence diagram models, are discussed. Finally, their structural and parametric learning possibilities are analyzed.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Computer-Aided Civil and Infrastructure Engineering
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
