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Predictability and Nonlinear Modelling in Natural Sciences and Economics (Hardcover)
Loot Price: R2,703
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Predictability and Nonlinear Modelling in Natural Sciences and Economics (Hardcover)
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Researchers in the natural sciences are faced with problems that
require a novel approach to improve the quality of forecasts of
processes that are sensitive to environmental conditions.
Nonlinearity of a system may significantly complicate the
predictability of future states: a small variation of parameters
can dramatically change the dynamics, while sensitive dependence of
the initial state may severely limit the predictability horizon.
Uncertainties also play a role. This volume addresses such problems
by using tools from chaos theory and systems theory, adapted for
the analysis of problems in the environmental sciences. Sensitive
dependence on the initial state (chaos) and the parameters are
analyzed using methods such as Lyapunov exponents and Monte Carlo
simulation. Uncertainty in the structure and the values of
parameters of a model is studied in relation to processes that
depend on the environmental conditions. These methods also apply to
biology and economics. This text aims to be suitable for research
workers at universities and (semi-) governmental institutes for the
environment, agriculture, ecology, meteorology and water
management, and theoretical economists.
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