Advances in Data-based Approaches for Hydrologic Modeling and Forecasting

This book comprehensively accounts the advances in data-based approaches for hydrologic modeling and forecasting.

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This book comprehensively accounts the advances in data-based approaches for hydrologic modeling and forecasting. Eight major and most popular approaches are selected, with a chapter for each — stochastic methods, parameter estimation techniques, scaling and fractal methods, remote sensing, artificial neural networks, evolutionary computing, wavelets, and nonlinear dynamics and chaos methods.
These approaches are chosen to address a wide range of hydrologic system characteristics, processes, and the associated problems. Each of these eight approaches includes a comprehensive review of the fundamental concepts, their applications in hydrology, and a discussion on potential future directions. "Advs in Data based Apprs for Hydrologic Mdlg Forecasting B Sivakumar et al World ". "Advs in Data based Apprs for Hydrologic Mdlg Forecasting B Sivakumar et al World .pdf" Size: "3.85 MB"

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