By Ayşe Özmen
adaptive regression splines (MARS) and Conic MARS which will handle
uncertainty and non-linearity. The proposed suggestions are applied and
explained in two-model regulatory structures that may be present in the financial
sector and within the contexts of banking, environmental security, procedure biology
and medication. The ebook presents necessary
background info on multi-model regulatory networks, optimization
and regression. It provides the speculation of and ways to powerful (conic)
multivariate adaptive regression splines - R(C)MARS – and powerful (conic)
generalized partial linear types – R(C)GPLM – below polyhedral uncertainty. Further,
it introduces spline regression versions for multi-model regulatory networks and
interprets (C)MARS effects in keeping with diversified datasets for the implementation.
It explains strong optimization in those versions when it comes to either the speculation and
methodology. during this context it stories R(C)MARS effects with different
uncertainty situations for a numerical instance. finally, the booklet demonstrates
the implementation of the strategy in a couple of purposes from the
financial, power, and environmental sectors, and gives an outlook on future
Read or Download Robust Optimization of Spline Models and Complex Regulatory Networks: Theory, Methods and Applications (Contributions to Management Science) PDF
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