Overview
- edited overview about quantitative information fusion in hydrology
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Computational Intelligence (SCI, volume 79)
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Table of contents(8 chapters)
About this book
In a rapidly evolving world of knowledge and technology, do you ever wonder how hydrology is catching up? This book takes the angle of computational hydrology and envisions one of the future directions, namely, quantitative integration of high-quality hydrologic field data with geologic, hydrologic, chemical, atmospheric, and biological information to characterize and predict natural systems in hydrological sciences.
Intelligent computation and information fusion are the key words. The aim is to provide both established scientists and graduate students with a summary of recent developments in this topic. The chapters of this edited volume cover some of the most important ingredients for quantitative hydrological information fusion, including data fusion techniques, interactive computational environments, and supporting mathematical and numerical methods. Real-life applications of hydrological information fusion are also addressed.
Editors and Affiliations
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Simula Research Laboratory, Lysaker, Norway
Xing Cai
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Department of Informatics, University of Oslo, Oslo, Norway
Xing Cai
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Department of Hydrology and Water Resources, The University of Arizona, Tucson, USA
T. -C. Jim Yeh
Bibliographic Information
Book Title: Quantitative Information Fusion for Hydrological Sciences
Editors: Xing Cai, T. -C. Jim Yeh
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-540-75384-1
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2008
Hardcover ISBN: 978-3-540-75383-4Published: 03 January 2008
Softcover ISBN: 978-3-642-09461-3Published: 20 November 2010
eBook ISBN: 978-3-540-75384-1Published: 12 January 2008
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: IX, 218
Topics: Hydrogeology, Mathematical and Computational Engineering, Hydrology/Water Resources, Geotechnical Engineering & Applied Earth Sciences, Artificial Intelligence