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Synopsis
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.
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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Predictability and Nonlinear Modelling in Natural Sciences and Economics
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Predictability and Nonlinear Modelling in Natural Sciences and Economics
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Predictability and Nonlinear Modelling in Natural Sciences and Economics
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Predictability and Nonlinear Modelling in Natural Sciences and Economics
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Predictability and Nonlinear Modelling in Natural Sciences and Economics
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Predictability and Nonlinear Modelling in Natural Sciences and Economics
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. For research workers at universities and (semi)governmental institutes for the environment, agriculture, ecology, meteorology and water management, and theoretical economists. 664 pp. Englisch. Seller Inventory # 9780792329435
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Predictability and Nonlinear Modelling in Natural Sciences and Economics
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Predictability and Nonlinear Modelling in Natural Sciences and Economics
Published by
Kluwer Academic Publishers, 1994
ISBN 10: 0792329430
ISBN 13: 9780792329435
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Hardback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 526. Seller Inventory # C9780792329435
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Predictability and Nonlinear Modelling in Natural Sciences and Economics
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Kluwer Academic Publishers, US, 1994
ISBN 10: 0792329430
ISBN 13: 9780792329435
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Hardback. Condition: New. 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. Seller Inventory # LU-9780792329435
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Predictability and Nonlinear Modelling in Natural Sciences and Economics
Published by
Springer Netherlands|Springer, Berlin, 1994
ISBN 10: 0792329430
ISBN 13: 9780792329435
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Gebunden. Condition: New. 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 predictabili. Seller Inventory # 898696285
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