FYI, please note that imprecise probability techniques are explicitly mentioned
***************************************************************
From Wei Gao
w.gao@unsw.edu.au
6th Asian-Pacific Symposium on Structural Reliability and Its
Applications APSSRA'2016
May 28-30, 2016, Tongji University, Shanghai, China
Abstract due May 30, 2015
Full paper due November 30, 2015
Mini-Symposium
Epistemic Uncertainties in Engineering -- Modelling, Methods and
Applications
Wei Gao (1), Hao Zhang (2), Michael Beer (3), and Vladik
Kreinovich (4)
(1) School of Civil and Environmental Engineering, University of
New South Wales, Sydney NSW 2052, Australia.
(2) School of Civil Engineering, University of Sydney, Sydney NSW
2006, Australia
(3) Institute for Risk & Uncertainty, University of Liverpool,
Brodie Tower, Brownlow Street, Liverpool L69 3GQ, UK
(4) Department of Computer Science, University of Texas at El
Paso, 500 W. University, El Paso, TX 79968, USA
E-mails:
w.gao@unsw.edu.au,
H.Zhang@civil.usyd.edu.au,
mbeer@liverpool.ac.uk,
vladik@utep.edu
Uncertainties are pervasive in engineering practice due to
inherent variability and lack of knowledge. Realistically
quantifying uncertainties in analysis and design of engineering
systems is crucial. Probabilistic methods have been developed
extensively for this purpose and have led to great achievements.
Significant research is increasingly devoted to problematic cases,
which involve, for example, limited information, human factors,
subjectivity and experience, linguistic assessments, imprecise
measurements, dubious information, unclear physics, etc. In this
context, two pathways have been proposed to account for epistemic
uncertainties. First, subjective probabilities are utilized to
quantify expert knowledge on an intuitive basis in form of a
belief. The most popular implementation of subjective
probabilities in engineering is observed in Bayesian approaches.
Second, alternative concepts have attracted considerable
attention, ranging from imprecise probabilities to interval and
fuzzy methods. Imprecise probabilities are most suitable when we
have partial information about probabilities, interval methods are
most suitable when we only know bounds, fuzzy methods are
appropriate when we have expert knowledge formulated in terms of
imprecise ("fuzzy") words from natural language. The usefulness of
all these concepts has been demonstrated in practical
applications. Quantification concepts and numerical methods for
processing subjective probabilities as well as fuzzy sets and
intervals in engineering analyses have already reached remarkable
capabilities.
This mini-symposium aims to bundle and disseminate the latest
developments of handling epistemic uncertainties in engineering.
Contributions are invited with emphasis on theory, numerical
methods and applications of both the non-probabilistic framework
and subjective probabilities. These may address specific technical
or mathematical details, conceptual developments and solution
strategies, individual solutions, and may also provide overviews
and comparative studies. Topics may include modelling,
quantification, analysis, design, decision-making, monitoring and
control in broad engineering areas.