| 書目名稱 | Predictability and Nonlinear Modelling in Natural Sciences and Economics | | 編輯 | J. Grasman,G. Straten | | 視頻video | http://file.papertrans.cn/755/754519/754519.mp4 | | 圖書封面 |  | | 描述 | Researchers in the natural sciences are faced with problemsthat require a novel approach to improve the quality of forecasts ofprocesses that are sensitive to environmental conditions. Nonlinearityof a system may significantly complicate the predictability of futurestates: a small variation of parameters can dramatically change thedynamics, while sensitive dependence of the initial state may severelylimit the predictability horizon. Uncertainties also play a role..This volume addresses such problems by using tools from chaos theoryand systems theory, adapted for the analysis of problems in theenvironmental sciences. Sensitive dependence on the initial state(chaos) and the parameters are analyzed using methods such as Lyapunovexponents and Monte Carlo simulation. Uncertainty in the structure andthe values of parameters of a model is studied in relation toprocesses that depend on the environmental conditions. These methodsalso apply to biology and economics. .For research workers at universities and (semi)governmental institutesfor the environment, agriculture, ecology, meteorology and watermanagement, and theoretical economists. . | | 出版日期 | Book 1994 | | 關(guān)鍵詞 | Atmospheric circulation; Chaos; Greenhouse gas; Meteorology; Regression; Scale; complex systems; ecosystem; | | 版次 | 1 | | doi | https://doi.org/10.1007/978-94-011-0962-8 | | isbn_softcover | 978-94-010-4416-5 | | isbn_ebook | 978-94-011-0962-8 | | copyright | Springer Science+Business Media Dordrecht 1994 |
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