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Author: Paresh Chandra Deka
Publisher:
ISBN: 9783846542248
Category :
Languages : en
Pages : 184
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Book Description
Author: Paresh Chandra Deka
Publisher:
ISBN: 9783846542248
Category :
Languages : en
Pages : 184
Get Book Here
Book Description
Author: Renji Remesan
Publisher: Springer
ISBN: 3319092359
Category : Science
Languages : en
Pages : 261
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Book Description
This book explores a new realm in data-based modeling with applications to hydrology. Pursuing a case study approach, it presents a rigorous evaluation of state-of-the-art input selection methods on the basis of detailed and comprehensive experimentation and comparative studies that employ emerging hybrid techniques for modeling and analysis. Advanced computing offers a range of new options for hydrologic modeling with the help of mathematical and data-based approaches like wavelets, neural networks, fuzzy logic, and support vector machines. Recently machine learning/artificial intelligence techniques have come to be used for time series modeling. However, though initial studies have shown this approach to be effective, there are still concerns about their accuracy and ability to make predictions on a selected input space.
Author: Robert Abrahart
Publisher: CRC Press
ISBN: 9789058096197
Category : Science
Languages : en
Pages : 324
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Book Description
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 water sciences, civil engineering, hydrology and physical geography. Each chapter has been written by one or more eminent experts working in various fields of hydrological modelling. The book covers an introduction to the concepts and technology involved, numerous case-studies with practical applications and methods, and finishes with suggestions for future research directions. Wide in scope, this book offers both significant new theoretical challenges and an examination of real-world problem-solving in all areas of hydrological modelling interest.
Author: R.S. Govindaraju
Publisher: Springer Science & Business Media
ISBN: 9401593418
Category : Science
Languages : en
Pages : 338
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Book Description
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.
Author: G. Tayfur
Publisher:
ISBN: 9781845646370
Category : Computers
Languages : en
Pages : 289
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Book Description
Engineers have attempted to solve water resources engineering problems with the help of empirical, regression-based and numerical models. Empirical models are not universal, nor are regression-based models. The numerical models are, on the other hand, physics-based but require substantial data measurement and parameter estimation. Hence, there is a need to employ models that are robust, user-friendly, and practical and that do not have the shortcomings of the existing methods. Artificial intelligence methods meet this need. Soft Computing in Water Resources Engineering introduces the basics of artificial neural networks (ANN), fuzzy logic (FL) and genetic algorithms (GA). It gives details on the feed forward back propagation algorithm and also introduces neuro-fuzzy modelling to readers. Artificial intelligence method applications covered in the book include predicting and forecasting floods, predicting suspended sediment, predicting event-based flow hydrographs and sedimentographs, locating seepage path in an earth-fill dam body, and the predicting dispersion coefficient in natural channels. The author also provides an analysis comparing the artificial intelligence models and contemporary non-artificial intelligence methods (empirical, numerical, regression, etc.). The ANN, FL, and GA are fairly new methods in water resources engineering. The first publications appeared in the early 1990s and quite a few studies followed in the early 2000s. Although these methods are currently widely known in journal publications, they are still very new for many scientific readers and they are totally new for students, especially undergraduates. Numerical methods were first taught at the graduate level but are now taught at the undergraduate level. There are already a few graduate courses developed on AI methods in engineering and included in the graduate curriculum of some universities. It is expected that these courses, too, will soon be taught at the undergraduate levels.
Author: Robert J. Abrahart
Publisher: Springer Science & Business Media
ISBN: 3540798811
Category : Science
Languages : en
Pages : 495
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Book Description
Hydroinformatics is an emerging subject that is expected to gather speed, momentum and critical mass throughout the forthcoming decades of the 21st century. This book provides a broad account of numerous advances in that field - a rapidly developing discipline covering the application of information and communication technologies, modelling and computational intelligence in aquatic environments. A systematic survey, classified according to the methods used (neural networks, fuzzy logic and evolutionary optimization, in particular) is offered, together with illustrated practical applications for solving various water-related issues. ...
Author: G. Tayfur
Publisher: WIT Press
ISBN: 1845646363
Category : Technology & Engineering
Languages : en
Pages : 289
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Book Description
Engineers have attempted to solve water resources engineering problems with the help of empirical, regression-based and numerical models. Empirical models are not universal, nor are regression-based models. The numerical models are, on the other hand, physics-based but require substantial data measurement and parameter estimation. Hence, there is a need to employ models that are robust, user-friendly, and practical and that do not have the shortcomings of the existing methods. Artificial intelligence methods meet this need. Soft Computing in Water Resources Engineering introduces the basics of artificial neural networks (ANN), fuzzy logic (FL) and genetic algorithms (GA). It gives details on the feed forward back propagation algorithm and also introduces neuro-fuzzy modelling to readers. Artificial intelligence method applications covered in the book include predicting and forecasting floods, predicting suspended sediment, predicting event-based flow hydrographs and sedimentographs, locating seepage path in an earth-fill dam body, and the predicting dispersion coefficient in natural channels. The author also provides an analysis comparing the artificial intelligence models and contemporary non-artificial intelligence methods (empirical, numerical, regression, etc.). The ANN, FL, and GA are fairly new methods in water resources engineering. The first publications appeared in the early 1990s and quite a few studies followed in the early 2000s. Although these methods are currently widely known in journal publications, they are still very new for many scientific readers and they are totally new for students, especially undergraduates. Numerical methods were first taught at the graduate level but are now taught at the undergraduate level. There are already a few graduate courses developed on AI methods in engineering and included in the graduate curriculum of some universities. It is expected that these courses, too, will soon be taught at the undergraduate levels.
Author: A W Jayawardena
Publisher: CRC Press
ISBN: 041546532X
Category : Technology & Engineering
Languages : en
Pages : 540
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Book Description
Mathematical modelling has become an indispensable tool for engineers, scientists, planners, decision makers and many other professionals to make predictions of future scenarios as well as real impending events. As the modelling approach and the model to be used are problem specific, no single model or approach can be used to solve all problems, and there are constraints in each situation. Modellers therefore need to have a choice when confronted with constraints such as lack of sufficient data, resources, expertise and time. Environmental and Hydrological Systems Modelling provides the tools needed by presenting different approaches to modelling the water environment over a range of spatial and temporal scales. Their applications are shown with a series of case studies, taken mainly from the Asia-Pacific Region. Coverage includes: Population dynamics Reaction kinetics Water quality systems Longitudinal dispersion Time series analysis and forecasting Artificial neural networks Fractals and chaos Dynamical systems Support vector machines Fuzzy logic systems Genetic algorithms and genetic programming This book will be of great value to advanced students, professionals, academics and researchers working in the water environment.
Author: Paresh Chandra Deka
Publisher: LAP Lambert Academic Publishing
ISBN: 9783845477060
Category :
Languages : en
Pages : 68
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Book Description
The problem of accurately determining river flows from rainfall, evaporation and other factors, occupies an important place in hydrology as the rainfall-runoff process is believed to be highly non-linear, time varying, spatially distributed and not easily described by simple model. The combination of Artificial Neural Network and Fuzzy Logic are probably the most attractive techniques among the researchers which is capable of handling non-linear, imprecise, fuzzy, noisy and probabilistic information to solve complex problem in efficient manner. This book, therefore, provide a comprehensive and integrated approach using Fuzzy logic and Artificial neural network techniques in estimating the daily runoff at the outlet of Koga catchment within Blue Nile river basin in Ethiopia. The methodology and results were analysed for different input scenarios. The analysis should be especially useful to the Hydrologist, civil engineering students, field engineers and researchers who may be considering utilizing latest soft computing techniques for runoff estimation in limited data, uncertainty and partially understood hydrological processes of a catchment.
Author: Zekai Sen
Publisher: CRC Press
ISBN: 1439809402
Category : Science
Languages : en
Pages : 354
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Book Description
The hydrological sciences typically present grey or fuzzy information, making them quite messy and a choice challenge for fuzzy logic application. Providing readers with the first book to cover fuzzy logic modeling as it relates to water science, the author takes an approach that incorporates verbal expert views and other parameters that allow
