Predictability and Nonlinear Modelling in Natural Sciences and Economics
内容简介
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. Nonlineari...
(展开全部)
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.
您对《Predictability and Nonlinear Modelling in Natural Sciences and Economics》有什么评价吗,点击右上角“我想说两句”,说出你的看法吧。
有什么“读后感”吗?您可点击右上角“我要写长评”来进行评价噢。
猜您喜欢读
网友关注
网友关注
精品推荐
分类导航
评价“Predictability and Nonlinear Modelling in Natural Sciences and Economics”