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Applications of Bayesian Classifiers. Edition No. 1
VDM Publishing House, Oct 2008, Pages: 144
In this book, it is shown how pattern recognition
approaches developed in computer science can be
seamlessly combined with statistical techniques to
produce a knowledge driven search algorithm. Two
different classes of applications are used to
demonstrate the wide applicability of the algorithm.
The first class of applications is in global design
optimization. In design optimization applications,
Bayesian classification tree is used to generate
high-performing design alternatives. The second is in
the structural mechanics of systems with spatially
random properties. In applications involving
spatially random properties, the classification tree
provides pattern-based features that can be used to
identify regions of a system with desirable or
undesirable local properties. The theories and
example applications should be especially useful to
researchers and professionals in the field of
uncertainty modeling and design optimization.
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