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These later papers, by they way, use a variety of methodologies for dealing with non-linearity and also for trying to determine causation.
A number of technical advances will likely improve the usefulness of models, including rigorous methodologies for dealing with missing and uncertain information; improved methods for interpretation of multivariate data sets and for multi-objective decision making involving trade-offs among conflicting goals; and novel modelling methods as alternatives to traditional mathematical models.
We anticipate that more and more pathway-based methodologies for dealing with this new data type will appear in the near future.
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Xue and Ji (2001) proposed a methodology for dealing with angular features in tolerance charting.
It thus provides a methodology for dealing with uncertainty in the prior knowledge.
This paper presents a novel methodology for dealing with decision-making problems in product design fields.
The main contribution of the paper is to propose a fully statistical methodology for dealing with non-linear nuisance parameters.
It has long been a problem of finding out a proper methodology for dealing with multiscale complex systems, including processes and products.
Recently, the combination of sliding mode and fuzzy logic techniques has emerged as a promising methodology for dealing with nonlinear, uncertain, dynamical systems.
Our team has previously described our data merging methodology for dealing with missing data in APPROACH.
We present a pragmatic first step towards a methodology for dealing with transient behaviours in non-autonomous systems.
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