Hydrological Data Driven Modelling: A Case Study Approach - Renji Remesan,Jimson Mathew
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This book explores a new realm in data-based modeling with applications to hydrology. Pursuing a case study approach, it presents a rigorous evaluation of state-of-the-art input selection methods on the basis of detailed and comprehensive experimentation and comparative studies that employ emerging hybrid techniques for modeling and analysis. Advanced computing offers a range of new options for hydrologic m ... Full description
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Description
This book explores a new realm in data-based modeling with applications to hydrology. Pursuing a case study approach, it presents a rigorous evaluation of state-of-the-art input selection methods on the basis of detailed and comprehensive experimentation and comparative studies that employ emerging hybrid techniques for modeling and analysis. Advanced computing offers a range of new options for hydrologic modeling with the help of mathematical and data-based approaches like wavelets, neural networks, fuzzy logic, and support vector machines. Recently machine learning/artificial intelligence techniques have come to be used for time series modeling. However, though initial studies have shown this approach to be effective, there are still concerns about their accuracy and ability to make predictions on a selected input space.
More Information
| Author | Renji Remesan, Jimson Mathew |
|---|---|
| Publisher | Springer Nature Switzerland |
| Series | Earth Systems Data and Models |
| Release year | 2014 |
| Cover type | Hardcover |
| EAN | 9783319092348 |