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Titlebook: Chaos in Hydrology; Bridging Determinism Bellie Sivakumar Book 2017 Springer Science+Business Media Dordrecht 2017 Chaos.Complexity.Hydrolo

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31#
發(fā)表于 2025-3-26 22:23:25 | 只看該作者
32#
發(fā)表于 2025-3-27 05:11:26 | 只看該作者
Current Status and data issues. The review also reveals that we now possess an ample level of understanding of the concepts and methods and are far more confident in applying the methods and interpreting the outcomes. This chapter discusses the current status of chaos theory in hydrology. In particular, five diff
33#
發(fā)表于 2025-3-27 06:45:21 | 只看該作者
34#
發(fā)表于 2025-3-27 13:17:20 | 只看該作者
35#
發(fā)表于 2025-3-27 17:17:29 | 只看該作者
hydrology; and (4) the scope and potential directions for the future..This book bridges the divide between the deterministic and the stochastic schools in hydrology, and is well suited as a textbook for hydrology courses..978-94-024-1314-4978-90-481-2552-4
36#
發(fā)表于 2025-3-27 19:38:51 | 只看該作者
Intermediate languages: Current status, of these characteristics in hydrologic system dynamics and the methods for their identification. At the end, a particularly interesting property of hydrologic systems, wherein simple nonlinear deterministic systems with sensitive dependence on initial conditions can give rise to complex and ‘random
37#
發(fā)表于 2025-3-28 01:48:10 | 只看該作者
Portability of Numerical Softwarel structure, and it is essentially determined from the data themselves. This chapter presents an overview of stochastic time series methods in hydrology. First, a brief account of the history of development of stochastic methods is presented. Next, the concept of time series and relevant statistical
38#
發(fā)表于 2025-3-28 05:36:40 | 只看該作者
39#
發(fā)表于 2025-3-28 10:06:34 | 只看該作者
40#
發(fā)表于 2025-3-28 10:59:43 | 只看該作者
https://doi.org/10.1007/978-3-8350-9433-8s four important issues in the applications of chaos methods to real time series, especially those that have particular relevance and gained considerable interest in hydrology: selection of delay time in phase space reconstruction, minimum data size required for correlation dimension estimation, inf
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