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A systematic presentation of the randomized machine learning
problem: from data processing, through structuring randomized
models and algorithmic procedure, to the solution of
applications-relevant problems in different fields. Provides new
numerical methods for random global optimization and computation of
multidimensional integrals. A universal algorithm for randomized
machine learning.
This monograph aspires to lay the foundations of a new scientific
discipline, demoeconomics, representing the synthesis of demography
and spatial economics. This synthesis is performed in terms of
interaction between population and its economic activity. The
monograph appears a unique research work having no analogs in
scientific literature. Demoeconomic systems are studied involving
the macrosystems approach which combines the generalized entropy
maximization principle and the local equilibria principle.
Demoeconomic systems operate in an uncertain environment; thus and
so, the monograph develops the methodology and technique of
probabilistic modeling and forecasting of their evolution.
Macrosystems are systems in which the stochastic behaviour of the
elements is transformed into deterministic behaviour of the system
as a whole. This publication discusses equilibrium in these
systems. Mathematical models of stationary states using the
principle of maximum entropy are presented. This is developed and
generalized for macrosystems with constrained resources. Parametric
properties which characterize a model's response to data variations
are discussed. The author has developed new computational methods
for the computer-aided realization of stationary state models.
Algorithms and computer experiments are evaluated. Mathematical
modelling methods are applied to problems of hierarchical
structures, interregional product exchange and image
reconstruction.
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