Neural Networks For Hydrological Modeling

Author : Robert Abrahart
Publisher : CRC Press
ISBN 13 : 0203024117
Total Pages : 316 pages
Book Rating : 4.19/5 ( download)

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Download or read book Neural Networks for Hydrological Modeling written by Robert Abrahart and published by CRC Press. This book was released on 2004-05-15 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 b

Author : R.S. Govindaraju
Publisher : Springer Science & Business Media
ISBN 13 : 9401593418
Total Pages : 338 pages
Book Rating : 4.10/5 ( download)

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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.

Author : Wojciech Samek
Publisher : Springer Nature
ISBN 13 : 3030289540
Total Pages : 435 pages
Book Rating : 4.46/5 ( download)

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Download or read book Explainable AI: Interpreting, Explaining and Visualizing Deep Learning written by Wojciech Samek and published by Springer Nature. This book was released on 2019-09-10 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development of “intelligent” systems that can take decisions and perform autonomously might lead to faster and more consistent decisions. A limiting factor for a broader adoption of AI technology is the inherent risks that come with giving up human control and oversight to “intelligent” machines. For sensitive tasks involving critical infrastructures and affecting human well-being or health, it is crucial to limit the possibility of improper, non-robust and unsafe decisions and actions. Before deploying an AI system, we see a strong need to validate its behavior, and thus establish guarantees that it will continue to perform as expected when deployed in a real-world environment. In pursuit of that objective, ways for humans to verify the agreement between the AI decision structure and their own ground-truth knowledge have been explored. Explainable AI (XAI) has developed as a subfield of AI, focused on exposing complex AI models to humans in a systematic and interpretable manner. The 22 chapters included in this book provide a timely snapshot of algorithms, theory, and applications of interpretable and explainable AI and AI techniques that have been proposed recently reflecting the current discourse in this field and providing directions of future development. The book is organized in six parts: towards AI transparency; methods for interpreting AI systems; explaining the decisions of AI systems; evaluating interpretability and explanations; applications of explainable AI; and software for explainable AI.

Author : Robert Abrahart
Publisher : CRC Press
ISBN 13 : 9789058096197
Total Pages : 324 pages
Book Rating : 4.9X/5 ( download)

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Download or read book Neural Networks for Hydrological Modeling written by Robert Abrahart and published by CRC Press. This book was released on 2004-05-15 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 : Bellie Sivakumar
Publisher : World Scientific
ISBN 13 : 9814464759
Total Pages : 542 pages
Book Rating : 4.58/5 ( download)

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Download or read book Advances In Data-based Approaches For Hydrologic Modeling And Forecasting written by Bellie Sivakumar and published by World Scientific. This book was released on 2010-08-10 with total page 542 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprehensively accounts the advances in data-based approaches for hydrologic modeling and forecasting. Eight major and most popular approaches are selected, with a chapter for each — stochastic methods, parameter estimation techniques, scaling and fractal methods, remote sensing, artificial neural networks, evolutionary computing, wavelets, and nonlinear dynamics and chaos methods. These approaches are chosen to address a wide range of hydrologic system characteristics, processes, and the associated problems. Each of these eight approaches includes a comprehensive review of the fundamental concepts, their applications in hydrology, and a discussion on potential future directions.

Author : Renji Remesan
Publisher : Springer
ISBN 13 : 3319092359
Total Pages : 250 pages
Book Rating : 4.55/5 ( download)

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Download or read book Hydrological Data Driven Modelling written by Renji Remesan and published by Springer. This book was released on 2014-11-03 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 : Srinivasa Lingireddy
Publisher : ASCE Publications
ISBN 13 : 9780784475607
Total Pages : 196 pages
Book Rating : 4.01/5 ( download)

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Download or read book Artificial Neural Networks in Water Supply Engineering written by Srinivasa Lingireddy and published by ASCE Publications. This book was released on 2005-01-01 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: Prepared by the Water Supply Engineering Technical Committee of the Infrastructure Council of the Environmental and Water Resources Institute of ASCE. This report examines the application of artificial neural network (ANN) technology to water supply engineering problems. Although ANN has rarely been used in in this area, those who have done so report findings that were beyond the capability of traditional statistical and mathematical modeling tools. This report describes the availability of diverse applications, along with the basics of neural network modeling, and summarizes the experiences of groups of researchers around the world who successfully demonstrated significant benefits from using ANN technology in water supply engineering. Topics include: Forecasting salinity levels in River Murray, South Australia; Predicting gastroenteritis rates and waterborne outbreaks; Modeling pH levels in a eutrophic Middle Loire River, France; and ANNs as function approximation tools replacing rigorous mathematical simulation models for analyzing water distribution networks.

Author : Taesam Lee
Publisher : Springer Nature
ISBN 13 : 3030647773
Total Pages : 215 pages
Book Rating : 4.73/5 ( download)

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Download or read book Deep Learning for Hydrometeorology and Environmental Science written by Taesam Lee and published by Springer Nature. This book was released on 2021-01-27 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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), especially for estimating parameters, with back-propagation as well as examples with real datasets of hydrometeorology (e.g. streamflow and temperature) and environmental science (e.g. water quality). Deep learning is known as part of machine learning methodology based on the artificial neural network. Increasing data availability and computing power enhance applications of deep learning to hydrometeorological and environmental fields. However, books that specifically focus on applications to these fields are limited. Most of deep learning books demonstrate theoretical backgrounds and mathematics. However, examples with real data and step-by-step explanations to understand the algorithms in hydrometeorology and environmental science are very rare. This book focuses on the explanation of deep learning techniques and their applications to hydrometeorological and environmental studies with real hydrological and environmental data. This book covers the major deep learning algorithms as Long Short-Term Memory (LSTM) and Convolution Neural Network (CNN) as well as the conventional artificial neural network model.

Author : Vijay P Singh
Publisher : Springer
ISBN 13 : 9811058016
Total Pages : 731 pages
Book Rating : 4.11/5 ( download)

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Download or read book Hydrologic Modeling written by Vijay P Singh and published by Springer. This book was released on 2018-01-19 with total page 731 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains seven parts. The first part deals with some aspects of rainfall analysis, including rainfall probability distribution, local rainfall interception, and analysis for reservoir release. Part 2 is on evapotranspiration and discusses development of neural network models, errors, and sensitivity. Part 3 focuses on various aspects of urban runoff, including hydrologic impacts, storm water management, and drainage systems. Part 4 deals with soil erosion and sediment, covering mineralogical composition, geostatistical analysis, land use impacts, and land use mapping. Part 5 treats remote sensing and geographic information system (GIS) applications to different hydrologic problems. Watershed runoff and floods are discussed in Part 6, encompassing hydraulic, experimental, and theoretical aspects. Water modeling constitutes the concluding Part 7. Soil and Water Assessment Tool (SWAT), Xinanjiang, and Soil Conservation Service-Curve Number (SCS-CN) models are discussed. The book is of interest to researchers and practitioners in the field of water resources, hydrology, environmental resources, agricultural engineering, watershed management, earth sciences, as well as those engaged in natural resources planning and management. Graduate students and those wishing to conduct further research in water and environment and their development and management find the book to be of value.

Author : Leszek Rutkowski
Publisher : Springer Science & Business Media
ISBN 13 : 3540221239
Total Pages : 1233 pages
Book Rating : 4.34/5 ( download)

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Download or read book Artificial Intelligence and Soft Computing — ICAISC 2004 written by Leszek Rutkowski and published by Springer Science & Business Media. This book was released on 2004-06-01 with total page 1233 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 7th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2004, held in Zakopane, Poland in June 2004. The 172 revised contributed papers presented together with 17 invited papers were carefully reviewed and selected from 250 submissions. The papers are organized in topical sections on neural networks, fuzzy systems, evolutionary algorithms, rough sets, soft computing in classification, image processing, robotics, multiagent systems, problems in AI, intelligent control, modeling and system identification, medical applications, mechanical applications, and applications in various fields.