Artificial Neural Networks in Hydrology

Artificial Neural Networks in Hydrology
Author :
Publisher : Springer Science & Business Media
Total Pages : 338
Release :
ISBN-10 : 9789401593410
ISBN-13 : 9401593418
Rating : 4/5 (418 Downloads)

Book Synopsis Artificial Neural Networks in Hydrology by : R.S. Govindaraju

Download or read book Artificial Neural Networks in Hydrology written by R.S. Govindaraju and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.


Artificial Neural Networks in Hydrology Related Books

Artificial Neural Networks in Hydrology
Language: en
Pages: 338
Authors: R.S. Govindaraju
Categories: Science
Type: BOOK - Published: 2013-03-09 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

R. S. GOVINDARAJU and ARAMACHANDRA RAO School of Civil Engineering Purdue University West Lafayette, IN. , USA Background and Motivation The basic notion of art
Stochastic and Statistical Methods in Hydrology and Environmental Engineering
Language: en
Pages: 469
Authors: Keith W. Hipel
Categories: Science
Type: BOOK - Published: 2013-04-17 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

International experts from around the globe present a rich variety of intriguing developments in time series analysis in hydrology and environmental engineering
Deep Learning for Hydrometeorology and Environmental Science
Language: en
Pages: 215
Authors: Taesam Lee
Categories: Science
Type: BOOK - Published: 2021-01-27 - Publisher: Springer Nature

DOWNLOAD EBOOK

This book provides a step-by-step methodology and derivation of deep learning algorithms as Long Short-Term Memory (LSTM) and Convolution Neural Network (CNN),
Neural Networks for Hydrological Modeling
Language: en
Pages: 324
Authors: Robert Abrahart
Categories: Science
Type: BOOK - Published: 2004-05-15 - Publisher: CRC Press

DOWNLOAD EBOOK

A new approach to the fast-developing world of neural hydrological modelling, this book is essential reading for academics and researchers in the fields of wate
Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
Language: en
Pages: 435
Authors: Wojciech Samek
Categories: Computers
Type: BOOK - Published: 2019-09-10 - Publisher: Springer Nature

DOWNLOAD EBOOK

The development of “intelligent” systems that can take decisions and perform autonomously might lead to faster and more consistent decisions. A limiting fac