Overview

The 1990s have witnessed a flurry of hydrologic research activity related to artificial neural networks (ANNs). This volume is a compilation of chapters that have been contributed by researchers from several countries, and represents a spectrum of ANN applications in hydrology. Future potential of ANN applications has been identified at appropriate places. Readers of the book will find chapters dealing with preliminary aspects as well as advanced features of ANNs. With a focus towards hydrologic applications, this book should serve as a useful reference for graduate students, research workers, and professionals interested in learning more about this computational tool.

Full Product Details

Author:   R.S. Govindaraju ,  A.R. Rao
Publisher:   Springer
Imprint:   Springer
Edition:   2000 ed.
Volume:   36
Dimensions:   Width: 15.50cm , Height: 2.00cm , Length: 23.50cm
Weight:   1.490kg
ISBN:  

9780792362265

ISBN 10:   0792362268
Pages:   332
Publication Date:   31 May 2000
Audience:   College/higher education ,  Professional and scholarly ,  Undergraduate ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

1. Effective and Efficient Modeling for Streamflow Forecasting.- 2. Streamflow Forecasting Based on Artificial Neural Networks.- 3. Real Time Forecasting Using Neural Networks.- 4. Modular Neural Networks for Watershed Runoff.- 5. Radial-Basis Function Networks.- 6. Artificial Neural Networks in Subsurface Characterization.- 7. Optimal Groundwater Remediation Using Artificial Neural Networks.- 8. Adaptive Neural Networks in Regulation of River Flows.- 9. Identification of Pollution Sources via Neural Networks.- 10. Spatial Organization and Characterization of Soil Physical Properties Using Self-Organizing Maps.- 11. Rainfall Estimation from Satellite Imagery.- 12. Streamflow Data Infilling Techniques Based on Concepts of Groups and Neural Networks.- 13. Spatial Analysis of Hydrologic and Environmental Data Based on Artificial Neural Networks.- 14. Application of Artificial Neural Networks to Forecasting of Surface Water Quality Variables: Issues, Applications and Challenges.- 15. Long Range Precipitation Prediction in California: A Look Inside The “Black Box” of a Trained Network.

Reviews

The book can be recommended as an important (but not the only) source of information on applications of artificial neural networks to hydrological problems. It would be useful for graduate students, researchers and hyrologists.' World Meteorological Organization Bulletin, 50: 3 (2001)

'The book can be recommended as an important (but not the only) source of information on applications of artificial neural networks to hydrological problems. It would be useful for graduate students, researchers and hyrologists.' World Meteorological Organization Bulletin, 50:3 (2001)

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