Predictability and nonlinear modelling in natural sciences and economics
Author(s)
Bibliographic Information
Predictability and nonlinear modelling in natural sciences and economics
Kluwer Academic Publishers, c1994
Available at 18 libraries
Note
"Papers presented at the International Conference on Predictability and Non-Linear Modelling in Natural Sciences and Economics, held at the occasion of the 75th anniversary of Wageningen Agricultural University ... 5-7 April 1993"--Pref
Includes bibliographical references and index
Description and Table of Contents
Description
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.
Table of Contents
1: Geophysics. 2: Agriculture. 3: Population Biology. 4: Systems Sciences. 5: Environmental Sciences. 6: Economics.
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