Falls Sie nur an einem bestimmten Exempar interessiert sind, können Sie aus der folgenden Liste jenes wählen, an dem Sie interessiert sind:
Nur diese Ausgabe anzeigen…
Nur diese Ausgabe anzeigen…
Artificial Neural Networks in Hydrology (Water Science and Technology Library)
8 Angebote vergleichen
Bester Preis: € 193,08 (vom 08.03.2017)Artificial Neural Networks in Hydrology (Water Science and Technology Library) (2000)
ISBN: 9780792362265 bzw. 0792362268, in Englisch, Springer, gebundenes Buch.
Von Händler/Antiquariat, Book Deals [60506629], Lewiston, NY, U.S.A.
This Book is in Good Condition. Clean Copy With Light Amount of Wear. 100% Guaranteed. Summary: Acknowledgements. List of Contributors. Introduction; R.S. Govindaraju, A. Ramachandra Rao. 1. Effective and Efficient Modeling for Streamflow Forecasting; H.V. Gupta, et al. 2. Streamflow Forecasting Based on Artificial Neural Networks; J.D. Salas, et al. 3. Real Time Forecasting Using Neural Networks; M.C. Deo, K. Thirumalaiah. 4. Modular Neural Networks for Watershed Runoff; B. Zhang, R.S. Govindaraju. 5. Radial-Basis Function Networks; R.S. Govindaraju, B. Zhang. 6. Artificial Neural Networks in Subsurface Characterization; D.M. Rizzo, D.E. Dougherty. 7. Optimal Groundwater Remediation Using Artificial Neural Networks; L.L. Rogers, et al. 8. Adaptive Neural Networks in Regulation of River Flows; J.M. Reddy, B.M. Wilamowski. 9. Identification of Pollution Sources Via Neural Networks; G.M. Brion, S. Lingireddy. 10. Spatial Organization and Characterization of Soil Physical Properties Using Self-Organizing Maps; S. Islam, R. Kothari. 11. Rainfall Estimation From Satellite Imagery; K.-L. Hsu, et al. 12. Streamflow Data Infilling Techniques Based on Concepts of Groups and Neural Networks; U.S. Panu, et al. 13. Spatial Analysis of Hydrologic and Environmental Data Based on Artificial Neural Networks; H.-S. Shin, J.D. Salas. 14. Application of Artificial Neural Networks to Forecasting of Surface Water Quality Variables: Issues, Applications and Challenges; H.R. Maier, G.C. Dandy. 15. Long Range Precipitation Prediction in California: A Look Inside the 'Black Box' of a Trained Network; D. Silverman, J.A. Dracup.
Artificial Neural Networks in Hydrology (Water Science and Technology Library) (2000)
ISBN: 9780792362265 bzw. 0792362268, in Englisch, Springer, gebundenes Buch, neu.
Von Händler/Antiquariat, Book Deals [60506629], Lewiston, NY, U.S.A.
Brand New, Unread Copy in Perfect Condition. A+ Customer Service! Summary: Acknowledgements. List of Contributors. Introduction; R.S. Govindaraju, A. Ramachandra Rao. 1. Effective and Efficient Modeling for Streamflow Forecasting; H.V. Gupta, et al. 2. Streamflow Forecasting Based on Artificial Neural Networks; J.D. Salas, et al. 3. Real Time Forecasting Using Neural Networks; M.C. Deo, K. Thirumalaiah. 4. Modular Neural Networks for Watershed Runoff; B. Zhang, R.S. Govindaraju. 5. Radial-Basis Function Networks; R.S. Govindaraju, B. Zhang. 6. Artificial Neural Networks in Subsurface Characterization; D.M. Rizzo, D.E. Dougherty. 7. Optimal Groundwater Remediation Using Artificial Neural Networks; L.L. Rogers, et al. 8. Adaptive Neural Networks in Regulation of River Flows; J.M. Reddy, B.M. Wilamowski. 9. Identification of Pollution Sources Via Neural Networks; G.M. Brion, S. Lingireddy. 10. Spatial Organization and Characterization of Soil Physical Properties Using Self-Organizing Maps; S. Islam, R. Kothari. 11. Rainfall Estimation From Satellite Imagery; K.-L. Hsu, et al. 12. Streamflow Data Infilling Techniques Based on Concepts of Groups and Neural Networks; U.S. Panu, et al. 13. Spatial Analysis of Hydrologic and Environmental Data Based on Artificial Neural Networks; H.-S. Shin, J.D. Salas. 14. Application of Artificial Neural Networks to Forecasting of Surface Water Quality Variables: Issues, Applications and Challenges; H.R. Maier, G.C. Dandy. 15. Long Range Precipitation Prediction in California: A Look Inside the 'Black Box' of a Trained Network; D. Silverman, J.A. Dracup.
Artificial Neural Networks in Hydrology (Water Science and Technology Library) (2000)
ISBN: 9780792362265 bzw. 0792362268, in Englisch, Springer, gebundenes Buch, gebraucht.
This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition.
Artificial Neural Networks in Hydrology (2010)
ISBN: 9789048154210 bzw. 9048154219, in Holländisch, Springer, Taschenbuch, neu.
bol.com.
R. S. GOVINDARAJU and ARAMACHANDRA RAO School of Civil Engineering Purdue University West Lafayette, IN. , USA Background and Motivation The basic notion of artificial neural networks (ANNs), as we understand them today, was perhaps first formalized by McCulloch and Pitts (1943) in their model of an artificial neuron. Research in this field remained somewhat dormant in the early years, perhaps because of the limited capabilities of this method and because there was no clear indication of its pot... R. S. GOVINDARAJU and ARAMACHANDRA RAO School of Civil Engineering Purdue University West Lafayette, IN. , USA Background and Motivation The basic notion of artificial neural networks (ANNs), as we understand them today, was perhaps first formalized by McCulloch and Pitts (1943) in their model of an artificial neuron. Research in this field remained somewhat dormant in the early years, perhaps because of the limited capabilities of this method and because there was no clear indication of its potential uses. However, interest in this area picked up momentum in a dramatic fashion with the works of Hopfield (1982) and Rumelhart et al. (1986). Not only did these studies place artificial neural networks on a firmer mathematical footing, but also opened the dOOf to a host of potential applications for this computational tool. Consequently, neural network computing has progressed rapidly along all fronts: theoretical development of different learning algorithms, computing capabilities, and applications to diverse areas from neurophysiology to the stock market. . Initial studies on artificial neural networks were prompted by adesire to have computers mimic human learning. As a result, the jargon associated with the technical literature on this subject is replete with expressions such as excitation and inhibition of neurons, strength of synaptic connections, learning rates, training, and network experience. ANNs have also been referred to as neurocomputers by people who want to preserve this analogy.Taal: Engels;Afmetingen: 18x234x156 mm;Gewicht: 597,00 gram;Verschijningsdatum: december 2010;ISBN10: 9048154219;ISBN13: 9789048154210; Engelstalig | Paperback | 2010.
Artificial Neural Networks in Hydrology (Water Science and Technology Library) (2009)
ISBN: 9789048154210 bzw. 9048154219, in Englisch, 352 Seiten, Springer Netherlands, Taschenbuch, gebraucht.
Von Händler/Antiquariat, Herb Tandree Philosophy Books.
The past decade has 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 wide 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 unique focus towards hydrologic applications, this book will serve as a valuable reference for graduate students, research workers, and professionals interested in learning more about this computational tool. The goal of this book is to help ANNs find greater acceptability among researchers and practising hydrologists alike. Paperback, Editie: Softcover reprint of hardcover 1st ed. 2000, Label: Springer Netherlands, Springer Netherlands, Productgroep: Book, Gepubliceerd: 2009-12-28, Releasedatum: 2009-12-28, Studio: Springer Netherlands.
Artificial Neural Networks in Hydrology (Water Science and Technology Library) (2009)
ISBN: 9789048154210 bzw. 9048154219, in Englisch, 352 Seiten, Springer Netherlands, Taschenbuch, neu.
Von Händler/Antiquariat, UKPaperbackshop.
The past decade has 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 wide 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 unique focus towards hydrologic applications, this book will serve as a valuable reference for graduate students, research workers, and professionals interested in learning more about this computational tool. The goal of this book is to help ANNs find greater acceptability among researchers and practising hydrologists alike. Paperback, Editie: Softcover reprint of hardcover 1st ed. 2000, Label: Springer Netherlands, Springer Netherlands, Productgroep: Book, Gepubliceerd: 2009-12-28, Releasedatum: 2009-12-28, Studio: Springer Netherlands.
Artificial Neural Networks in Hydrology (Water Science and Technology Library) (2000)
ISBN: 9780792362265 bzw. 0792362268, in Englisch, 332 Seiten, 2000. Ausgabe, Springer, gebundenes Buch, neu.
Von Händler/Antiquariat, oddesseyy.
R. S. GOVINDARAJU and ARAMACHANDRA RAO School of Civil Engineering Purdue University West Lafayette, IN. , USA Background and Motivation The basic notion of artificial neural networks (ANNs), as we understand them today, was perhaps first formalized by McCulloch and Pitts (1943) in their model of an artificial neuron. Research in this field remained somewhat dormant in the early years, perhaps because of the limited capabilities of this method and because there was no clear indication of its potential uses. However, interest in this area picked up momentum in a dramatic fashion with the works of Hopfield (1982) and Rumelhart et al. (1986). Not only did these studies place artificial neural networks on a firmer mathematical footing, but also opened the dOOf to a host of potential applications for this computational tool. Consequently, neural network computing has progressed rapidly along all fronts: theoretical development of different learning algorithms, computing capabilities, and applications to diverse areas from neurophysiology to the stock market. . Initial studies on artificial neural networks were prompted by adesire to have computers mimic human learning. As a result, the jargon associated with the technical literature on this subject is replete with expressions such as excitation and inhibition of neurons, strength of synaptic connections, learning rates, training, and network experience. ANNs have also been referred to as neurocomputers by people who want to preserve this analogy. Hardcover, Ausgabe: 2000, Label: Springer, Springer, Produktgruppe: Book, Publiziert: 2000-05-31, Studio: Springer, Verkaufsrang: 5527503.
Artificial Neural Networks in Hydrology
ISBN: 9780792362265 bzw. 0792362268, in Englisch, Springer, neu.
Artificial Neural Networks in Hydrology, R. S. GOVINDARAJU and ARAMACHANDRA RAO School of Civil Engineering Purdue University West Lafayette, IN. , USA Background and Motivation The basic notion of artificial neural networks (ANNs), as we understand them today, was perhaps first formalized by McCulloch and Pitts (1943) in their model of an artificial neuron. Research in this field remained somewhat dormant in the early years, perhaps because of the limited capabilities of this method and because there was no clear indication of its potential uses. However, interest in this area picked up momentum in a dramatic fashion with the works of Hopfield (1982) and Rumelhart et al. (1986). Not only did these studies place artificial neural networks on a firmer mathematical footing, but also opened the dOOf to a host of potential applications for this computational tool. Consequently, neural network computing has progressed rapidly along all fronts: theoretical development of different learning algorithms, computing capabilities, and applications to diverse areas from neurophysiology to the stock market. . Initial studies on artificial neural networks were prompted by adesire to have computers mimic human learning. As a result, the jargon associated with the technical literature on this subject is replete with expressions such as excitation and inhibition of neurons, strength of synaptic connections, learning rates, training, and network experience. ANNs have also been referred to as neurocomputers by people who want to preserve this analogy.