Neural Networks For Hydrological Modeling

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Neural Networks for Hydrological Modeling

Author : Robert Abrahart
Publisher : CRC Press
ISBN 13 : 9789058096197
Total Pages : 324 pages
Book Rating : 4.0/5 (961 download)

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Book Synopsis Neural Networks for Hydrological Modeling by : Robert Abrahart

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.

Neural Networks for Hydrological Modeling

Author : Robert Abrahart
Publisher : CRC Press
ISBN 13 : 0203024117
Total Pages : 316 pages
Book Rating : 4.2/5 (3 download)

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Book Synopsis Neural Networks for Hydrological Modeling by : Robert Abrahart

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

Artificial Neural Networks in Hydrology

Author : R.S. Govindaraju
Publisher : Springer Science & Business Media
ISBN 13 : 9401593418
Total Pages : 338 pages
Book Rating : 4.4/5 (15 download)

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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.

Explainable AI: Interpreting, Explaining and Visualizing Deep Learning

Author : Wojciech Samek
Publisher : Springer Nature
ISBN 13 : 3030289540
Total Pages : 435 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Explainable AI: Interpreting, Explaining and Visualizing Deep Learning by : Wojciech Samek

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.

Advances In Data-based Approaches For Hydrologic Modeling And Forecasting

Author : Bellie Sivakumar
Publisher : World Scientific
ISBN 13 : 9814464759
Total Pages : 542 pages
Book Rating : 4.8/5 (144 download)

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Book Synopsis Advances In Data-based Approaches For Hydrologic Modeling And Forecasting by : Bellie Sivakumar

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.

Visualization of Neural Networks for Diagnostic Hydrological Modeling

Author : Ahmed Hassan
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (138 download)

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Book Synopsis Visualization of Neural Networks for Diagnostic Hydrological Modeling by : Ahmed Hassan

Download or read book Visualization of Neural Networks for Diagnostic Hydrological Modeling written by Ahmed Hassan and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Hydrological Data Driven Modelling

Author : Renji Remesan
Publisher : Springer
ISBN 13 : 3319092359
Total Pages : 261 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Hydrological Data Driven Modelling by : Renji Remesan

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 261 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.

Artificial Neural Networks in Water Supply Engineering

Author : Srinivasa Lingireddy
Publisher : ASCE Publications
ISBN 13 : 9780784475607
Total Pages : 196 pages
Book Rating : 4.4/5 (756 download)

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Book Synopsis Artificial Neural Networks in Water Supply Engineering by : Srinivasa Lingireddy

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.

Metaheuristic Algorithms and Neural Networks in Hydrology

Author : Kuok King Kuok
Publisher : Cambridge Scholars Publishing
ISBN 13 : 1036408051
Total Pages : 231 pages
Book Rating : 4.0/5 (364 download)

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Book Synopsis Metaheuristic Algorithms and Neural Networks in Hydrology by : Kuok King Kuok

Download or read book Metaheuristic Algorithms and Neural Networks in Hydrology written by Kuok King Kuok and published by Cambridge Scholars Publishing. This book was released on 2024-08-28 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book summarizes the latest research and developments related to the application of nature-inspired metaheuristic algorithms coupled with artificial neural networks (ANNs) in hydrology. The book covers the theoretical foundations, models and methods, structure, frameworks and analysis of applying novel ANNs in hydrology. It starts with the introduction of ANNs as a black box model, followed by the coupling of various metaheuristic algorithms with ANNs to form novel neural network models for solving real-world problems in hydrology, including Particle Swarm Optimization (PSO) for rainfall-runoff modeling, Bat Optimization (Bat) and Cuckoo Search Optimization (CSO) for future rainfall prediction, the Whale Optimization Algorithm (WOA) and Salp Swarm Optimization (SSO) for future water level prediction, Grey Wolf Optimization (GWO), Multi-Verse Optimization (MVO), the Sine Cosine Algorithm (SCA) and the Hybrid Sine Cosine and Fitness Dependent Optimizer (SC-FDO) for imputing missing rainfall data.

Hydrologic Modeling

Author : Vijay P Singh
Publisher : Springer
ISBN 13 : 9811058016
Total Pages : 718 pages
Book Rating : 4.8/5 (11 download)

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Book Synopsis Hydrologic Modeling by : Vijay P Singh

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 718 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.

Deep Learning for Hydrometeorology and Environmental Science

Author : Taesam Lee
Publisher : Springer Nature
ISBN 13 : 3030647773
Total Pages : 215 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Deep Learning for Hydrometeorology and Environmental Science by : Taesam Lee

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.

State of the Art in Neural Networks and Their Applications

Author : Ayman S. El-Baz
Publisher : Academic Press
ISBN 13 : 0128218495
Total Pages : 326 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis State of the Art in Neural Networks and Their Applications by : Ayman S. El-Baz

Download or read book State of the Art in Neural Networks and Their Applications written by Ayman S. El-Baz and published by Academic Press. This book was released on 2021-07-21 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: State of the Art in Neural Networks and Their Applications presents the latest advances in artificial neural networks and their applications across a wide range of clinical diagnoses. Advances in the role of machine learning, artificial intelligence, deep learning, cognitive image processing and suitable data analytics useful for clinical diagnosis and research applications are covered, including relevant case studies. The application of Neural Network, Artificial Intelligence, and Machine Learning methods in biomedical image analysis have resulted in the development of computer-aided diagnostic (CAD) systems that aim towards the automatic early detection of several severe diseases. State of the Art in Neural Networks and Their Applications is presented in two volumes. Volume 1 covers the state-of-the-art deep learning approaches for the detection of renal, retinal, breast, skin, and dental abnormalities and more. Includes applications of neural networks, AI, machine learning, and deep learning techniques to a variety of imaging technologies Provides in-depth technical coverage of computer-aided diagnosis (CAD), with coverage of computer-aided classification, Unified Deep Learning Frameworks, mammography, fundus imaging, optical coherence tomography, cryo-electron tomography, 3D MRI, CT, and more Covers deep learning for several medical conditions including renal, retinal, breast, skin, and dental abnormalities, Medical Image Analysis, as well as detection, segmentation, and classification via AI

Flood Forecasting Using Artificial Neural Networks

Author : P. Varoonchotikul
Publisher : CRC Press
ISBN 13 : 9781138475076
Total Pages : pages
Book Rating : 4.4/5 (75 download)

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Book Synopsis Flood Forecasting Using Artificial Neural Networks by : P. Varoonchotikul

Download or read book Flood Forecasting Using Artificial Neural Networks written by P. Varoonchotikul and published by CRC Press. This book was released on 2017-10-02 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation considers various questions with respect to the effects of salinity on nutrification: what are the main inhibiting factors causing the effects, do all salts have similar effects, what is the maximum acceptable salt level, are ammonia oxidisers or nitrite oxidizers most sensitive to salt stress, can nitrifiers adapt to long term salt stress and are some specific nitrifiers more resistant to salt stress than others? Research was carried out at laboratory scale and in full-scale plants and modelling was employed in both phases to provide a mathematical description for salt inhibition on nitrification and to facilitate the comparison. The result has led to an improved understanding of the effect of salinity on nitrification. The results can be used to improve the sustainability of the exisisting wastewater treatment plants operated under salt stress.

Fuzzy Logic and Artificial Neural Network for Hydrological Modeling

Author : Paresh Chandra Deka
Publisher :
ISBN 13 : 9783846542248
Total Pages : 184 pages
Book Rating : 4.5/5 (422 download)

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Book Synopsis Fuzzy Logic and Artificial Neural Network for Hydrological Modeling by : Paresh Chandra Deka

Download or read book Fuzzy Logic and Artificial Neural Network for Hydrological Modeling written by Paresh Chandra Deka and published by . This book was released on 2011-11 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Flood Forecasting Using Machine Learning Methods

Author : Fi-John Chang
Publisher : MDPI
ISBN 13 : 3038975486
Total Pages : 376 pages
Book Rating : 4.0/5 (389 download)

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Book Synopsis Flood Forecasting Using Machine Learning Methods by : Fi-John Chang

Download or read book Flood Forecasting Using Machine Learning Methods written by Fi-John Chang and published by MDPI. This book was released on 2019-02-28 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nowadays, the degree and scale of flood hazards has been massively increasing as a result of the changing climate, and large-scale floods jeopardize lives and properties, causing great economic losses, in the inundation-prone areas of the world. Early flood warning systems are promising countermeasures against flood hazards and losses. A collaborative assessment according to multiple disciplines, comprising hydrology, remote sensing, and meteorology, of the magnitude and impacts of flood hazards on inundation areas significantly contributes to model the integrity and precision of flood forecasting. Methodologically oriented countermeasures against flood hazards may involve the forecasting of reservoir inflows, river flows, tropical cyclone tracks, and flooding at different lead times and/or scales. Analyses of impacts, risks, uncertainty, resilience, and scenarios coupled with policy-oriented suggestions will give information for flood hazard mitigation. Emerging advances in computing technologies coupled with big-data mining have boosted data-driven applications, among which Machine Learning technology, with its flexibility and scalability in pattern extraction, has modernized not only scientific thinking but also predictive applications. This book explores recent Machine Learning advances on flood forecast and management in a timely manner and presents interdisciplinary approaches to modelling the complexity of flood hazards-related issues, with contributions to integrative solutions from a local, regional or global perspective.

Artificial Neural Networks

Author : Joao Luis Garcia Rosa
Publisher : BoD – Books on Demand
ISBN 13 : 9535127047
Total Pages : 416 pages
Book Rating : 4.5/5 (351 download)

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Book Synopsis Artificial Neural Networks by : Joao Luis Garcia Rosa

Download or read book Artificial Neural Networks written by Joao Luis Garcia Rosa and published by BoD – Books on Demand. This book was released on 2016-10-19 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: The idea of simulating the brain was the goal of many pioneering works in Artificial Intelligence. The brain has been seen as a neural network, or a set of nodes, or neurons, connected by communication lines. Currently, there has been increasing interest in the use of neural network models. This book contains chapters on basic concepts of artificial neural networks, recent connectionist architectures and several successful applications in various fields of knowledge, from assisted speech therapy to remote sensing of hydrological parameters, from fabric defect classification to application in civil engineering. This is a current book on Artificial Neural Networks and Applications, bringing recent advances in the area to the reader interested in this always-evolving machine learning technique.

Mathematical Models of Small Watershed Hydrology and Applications

Author : Vijay P. Singh
Publisher : Water Resources Publication
ISBN 13 : 9781887201353
Total Pages : 984 pages
Book Rating : 4.2/5 (13 download)

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Book Synopsis Mathematical Models of Small Watershed Hydrology and Applications by : Vijay P. Singh

Download or read book Mathematical Models of Small Watershed Hydrology and Applications written by Vijay P. Singh and published by Water Resources Publication. This book was released on 2002 with total page 984 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprehensive account of some of the most popular models of small watershed hydrology and application ~~ of interest to all hydrologic modelers and model users and a welcome and timely edition to any modeling library