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Books > Computing & IT > Applications of computing > Artificial intelligence
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Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining (Paperback, Softcover reprint of the original 1st ed. 2019)
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Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining (Paperback, Softcover reprint of the original 1st ed. 2019)
Series: Intelligent Systems Reference Library, 146
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Dynamic programming is an efficient technique for solving
optimization problems. It is based on breaking the initial problem
down into simpler ones and solving these sub-problems, beginning
with the simplest ones. A conventional dynamic programming
algorithm returns an optimal object from a given set of objects.
This book develops extensions of dynamic programming, enabling us
to (i) describe the set of objects under consideration; (ii)
perform a multi-stage optimization of objects relative to different
criteria; (iii) count the number of optimal objects; (iv) find the
set of Pareto optimal points for bi-criteria optimization problems;
and (v) to study relationships between two criteria. It considers
various applications, including optimization of decision trees and
decision rule systems as algorithms for problem solving, as ways
for knowledge representation, and as classifiers; optimization of
element partition trees for rectangular meshes, which are used in
finite element methods for solving PDEs; and multi-stage
optimization for such classic combinatorial optimization problems
as matrix chain multiplication, binary search trees, global
sequence alignment, and shortest paths. The results presented are
useful for researchers in combinatorial optimization, data mining,
knowledge discovery, machine learning, and finite element methods,
especially those working in rough set theory, test theory, logical
analysis of data, and PDE solvers. This book can be used as the
basis for graduate courses.
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