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This book explores a new realm in data based modelling issues with application to Hydrology. Using a case study approach it is the first book to give rigorous evaluation of the state-of-the-art input selection methods through detailed and comprehensive experimentation and comparative studies employing emerging hybrid techniques for modelling and analysis. The advent of digital computers has brought new possibilities in hydrologic modelling with the help of mathematical and data based approaches like wavelets, Neural Networks, Fuzzy Logic and Support Vector Machines. Recently machine learning/arti cial intelligence techniques have been used for time series modelling. Although earlier studies have shown this approach to be effective, there are still concerns about their accuracy and how these techniques perform prediction upon selected input space. The book appropriately fills this gap with an aim to be suitable for students, engineers and researchers.§
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