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.

Download or read book Hydrological Modelling and the Water Cycle written by Soroosh Sorooshian and published by Springer Science & Business Media. This book was released on 2008-07-18 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is a collection of a selected number of articles based on presentations at the 2005 L’Aquila (Italy) Summer School on the topic of “Hydrologic Modeling and Water Cycle: Coupling of the Atmosphere and Hydrological Models”. The p- mary focus of this volume is on hydrologic modeling and their data requirements, especially precipitation. As the eld of hydrologic modeling is experiencing rapid development and transition to application of distributed models, many challenges including overcoming the requirements of compatible observations of inputs and outputs must be addressed. A number of papers address the recent advances in the State-of-the-art distributed precipitation estimation from satellites. A number of articles address the issues related to the data merging and use of geo-statistical techniques for addressing data limitations at spatial resolutions to capture the h- erogeneity of physical processes. The participants at the School came from diverse backgrounds and the level of - terest and active involvement in the discussions clearly demonstrated the importance the scienti c community places on challenges related to the coupling of atmospheric and hydrologic models. Along with my colleagues Dr. Erika Coppola and Dr. Kuolin Hsu, co-directors of the School, we greatly appreciate the invited lectures and all the participants. The members of the local organizing committee, Drs Barbara Tomassetti; Marco Verdecchia and Guido Visconti were instrumental in the success of the school and their contributions, both scienti cally and organizationally are much appreciated.

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.

Download or read book River Flow 2016 written by George Constantinescu and published by CRC Press. This book was released on 2016-06-22 with total page 3703 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understanding and being able to predict fluvial processes is one of the biggest challenges for hydraulics and environmental engineers, hydrologists and other scientists interested in preserving and restoring the diverse functions of rivers. The interactions among flow, turbulence, vegetation, macroinvertebrates and other organisms, as well as the transport and retention of particulate matter, have important consequences on the ecological health of rivers. Managing rivers in an ecologically friendly way is a major component of sustainable engineering design, maintenance and restoration of ecological habitats. To address these challenges, a major focus of River Flow 2016 was to highlight the latest advances in experimental, computational and theoretical approaches that can be used to deepen our understanding and capacity to predict flow and the associated fluid-driven ecological processes, anthropogenic influences, sediment transport and morphodynamic processes. River Flow 2016 was organized under the auspices of the Committee for Fluvial Hydraulics of the International Association for Hydro-Environment Engineering and Research (IAHR). Since its first edition in 2002, the River Flow conference series has become the main international event focusing on river hydrodynamics, sediment transport, river engineering and restoration. Some of the highlights of the 8th International Conference on Fluvial Hydraulics were to focus on inter-disciplinary research involving, among others, ecological and biological aspects relevant to river flows and processes and to emphasize broader themes dealing with river sustainability. River Flow 2016 contains the contributions presented during the regular sessions covering the main conference themes and the special sessions focusing on specific hot topics of river flow research, and will be of interest to academics interested in hydraulics, hydrology and environmental engineering.

Download or read book River Flow 2014 written by Anton J. Schleiss and published by CRC Press. This book was released on 2014-08-12 with total page 2579 pages. Available in PDF, EPUB and Kindle. Book excerpt: The behaviour of river systems is a result of the complex interaction between flow, sediments, morphology and habitats. Furthermore, rivers are often used as a source of water supply and energy production as well as a waterway for transportation. The main challenge faced by river engineers today, in collaboration with environmental and ecological scientists, is to restore the channelized rivers under the constraints of high urbanization and limited space, as well as sustainable water use. During the seventh International Conference on Fluvial Hydraulics “River Flow 2014” at École Polytechnique Fédérale de Lausanne (EPFL), Switzerland, scientists and professionals from all over the world addressed this challenge and exchanged their knowledge regarding fluvial hydraulics and river morphology. This book comprises the proceedings of the high quality contributions of the participants, which reflect the state-of-the-art in the fields of river hydrodynamics, morphodynamics, sediment transport, river engineering and restoration. The conference was organized under the auspices of the Committee on Fluvial Hydraulics of the International Association for Hydro-Environment Engineering and Research (IAHR). Past River Flow conferences have witnessed a significant increase in participation of our community of river engineers and researchers, confirming the need for such a forum.

Download or read book Neural Information Processing written by Long Cheng and published by Springer. This book was released on 2018-12-03 with total page 590 pages. Available in PDF, EPUB and Kindle. Book excerpt: The seven-volume set of LNCS 11301-11307 constitutes the proceedings of the 25th International Conference on Neural Information Processing, ICONIP 2018, held in Siem Reap, Cambodia, in December 2018. The 401 full papers presented were carefully reviewed and selected from 575 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains. The 5th volume, LNCS 11305, is organized in topical sections on prediction; pattern recognition; and word, text and document processing.

Download or read book Hydrology written by Martin P. Wanielista and published by John Wiley & Sons. This book was released on 1996-09-28 with total page 598 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edition of its popular predecessor has been significantly revised to increase flexibility in the presentation and maintain greater continuity of the material. Combining both theory and practical applications of empirical equations the text contains expanded treatment of water quantity and quality control, a detailed presentation of basic principles and use in analysis and design, hydrograph topics including synthetic and convolution techniques, practical and realistic case studies relating to design problems, and additional end-of-chapter problems. It provides new computer programs to explain complex concepts and solve large data-based problems. An additional appendix offers suggestions for classroom or lab problems.

Download or read book Neural Information Processing Research and Development written by Jagath Chandana Rajapakse and published by Springer. This book was released on 2012-12-06 with total page 487 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of neural information processing has two main objects: investigation into the functioning of biological neural networks and use of artificial neural networks to sol ve real world problems. Even before the reincarnation of the field of artificial neural networks in mid nineteen eighties, researchers have attempted to explore the engineering of human brain function. After the reincarnation, we have seen an emergence of a large number of neural network models and their successful applications to solve real world problems. This volume presents a collection of recent research and developments in the field of neural information processing. The book is organized in three Parts, i.e., (1) architectures, (2) learning algorithms, and (3) applications. Artificial neural networks consist of simple processing elements called neurons, which are connected by weights. The number of neurons and how they are connected to each other defines the architecture of a particular neural network. Part 1 of the book has nine chapters, demonstrating some of recent neural network architectures derived either to mimic aspects of human brain function or applied in some real world problems. Muresan provides a simple neural network model, based on spiking neurons that make use of shunting inhibition, which is capable of resisting small scale changes of stimulus. Hoshino and Zheng simulate a neural network of the auditory cortex to investigate neural basis for encoding and perception of vowel sounds.

Download or read book Broadening the Use of Machine Learning in Hydrology written by Chaopeng Shen and published by Frontiers Media SA. This book was released on 2021-07-08 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Applied Mechanics Reviews written by and published by . This book was released on 1993 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book NETLAB written by Ian Nabney and published by Springer Science & Business Media. This book was released on 2002 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: Getting the most out of neural networks and related data modelling techniques is the purpose of this book. The text, with the accompanying Netlab toolbox, provides all the necessary tools and knowledge. Throughout, the emphasis is on methods that are relevant to the practical application of neural networks to pattern analysis problems. All parts of the toolbox interact in a coherent way, and implementations and descriptions of standard statistical techniques are provided so that they can be used as benchmarks against which more sophisticated algorithms can be evaluated. Plenty of examples and demonstration programs illustrate the theory and help the reader understand the algorithms and how to apply them.

Download or read book Bayesian Learning for Neural Networks written by Radford M. Neal and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial "neural networks" are widely used as flexible models for classification and regression applications, but questions remain about how the power of these models can be safely exploited when training data is limited. This book demonstrates how Bayesian methods allow complex neural network models to be used without fear of the "overfitting" that can occur with traditional training methods. Insight into the nature of these complex Bayesian models is provided by a theoretical investigation of the priors over functions that underlie them. A practical implementation of Bayesian neural network learning using Markov chain Monte Carlo methods is also described, and software for it is freely available over the Internet. Presupposing only basic knowledge of probability and statistics, this book should be of interest to researchers in statistics, engineering, and artificial intelligence.

Download or read book Intelligent Systems written by Siba K. Udgata and published by Springer Nature. This book was released on 2022-05-03 with total page 691 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features best selected research papers presented at the International Conference on Machine Learning, Internet of Things, and Big Data (ICMIB 2021) held at Indira Gandhi Institute of Technology, Sarang, India, during December 2021. It comprises high-quality research work by academicians and industrial experts in the field of machine learning, mobile computing, natural language processing, fuzzy computing, green computing, human–computer interaction, information retrieval, intelligent control, data mining and knowledge discovery, evolutionary computing, IoT and applications in smart environments, smart health, smart city, wireless networks, big data, cloud computing, business intelligence, Internet security, pattern recognition, predictive analytics applications in healthcare, sensor networks and social sensing, and statistical analysis of search techniques.

Download or read book Watershed Management and Applications of AI written by Sandeep Samantaray and published by CRC Press. This book was released on 2021-05-16 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Land use and water resources are two major environmental issues which necessitate conservation, management, and maintenance practices through the use of various engineering techniques. Water scientists and environmental engineers must address the various aspects of flood control, soil conservation, rainfall-runoff processes, and groundwater hydrology. Watershed Management and Applications of AI provides the necessary principles of hydrology to provide practical strategies useful for the planning, design, and management of watersheds. The book also synthesizes novel new approaches, such as hydrological applications of machine learning using neural networks to predict runoff and using artificial intelligence for the prediction of groundwater fluctuations. Features: Presents hydrologic analysis and design along with soil conservation practices through proper watershed management techniques Provides analysis of land erosion and sediment transport in watersheds from small to large scale Includes estimations for runoff using different methodologies with systematic approaches for each Discusses water harvesting and development of water yield catchments This book will be a valuable resource for students in hydrology courses, environmental consultants, water resource engineers, and researchers in related water science and engineering fields.

Download or read book Deep Learning with Python written by Nikhil Ketkar and published by Apress. This book was released on 2017-04-18 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover the practical aspects of implementing deep-learning solutions using the rich Python ecosystem. This book bridges the gap between the academic state-of-the-art and the industry state-of-the-practice by introducing you to deep learning frameworks such as Keras, Theano, and Caffe. The practicalities of these frameworks is often acquired by practitioners by reading source code, manuals, and posting questions on community forums, which tends to be a slow and a painful process. Deep Learning with Python allows you to ramp up to such practical know-how in a short period of time and focus more on the domain, models, and algorithms. This book briefly covers the mathematical prerequisites and fundamentals of deep learning, making this book a good starting point for software developers who want to get started in deep learning. A brief survey of deep learning architectures is also included. Deep Learning with Python also introduces you to key concepts of automatic differentiation and GPU computation which, while not central to deep learning, are critical when it comes to conducting large scale experiments. What You Will Learn Leverage deep learning frameworks in Python namely, Keras, Theano, and Caffe Gain the fundamentals of deep learning with mathematical prerequisites Discover the practical considerations of large scale experiments Take deep learning models to production Who This Book Is For Software developers who want to try out deep learning as a practical solution to a particular problem. Software developers in a data science team who want to take deep learning models developed by data scientists to production.

Download or read book Uncertainty and Forecasting of Water Quality written by M.B. Beck and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the International Institute for Applied Systems Analysis began its study of water quality modeling and management in 1977, it has been interested in the relations between uncertainty and the problems of model calibration and prediction. The work has focused on the theme of modeling poorly defined environmental systems, a principal topic of the effort devoted to environmental quality control and management. Accounting for the effects of uncertainty was also of central concern to our two case studies of lake eutrophication management, one dealing with Lake Balaton in Hungary and the other with several Austrian lake systems. Thus, in November 1979 we held a meeting at Laxenburg to discuss recent method ological developments in addressing problems associated with uncertainty and forecasting of water quality. This book is based on the proceedings of that meeting. The last few years have seen an increase in awareness of the issue of uncertainty in water quality and ecological modeling. This book is relevant not only to contemporary issues but also to those of the future. A lack of field data will not always be the dominant problem for water quality modeling and management; more sophisticated measuring techniques and more comprehensive monitoring networks will come to be more widely applied. Rather, the important problems of the future are much more likely to emerge from the enhanced facility of data processing and to concern the meaningful interpretation, assimilation., and use of the information thus obtained.

Download or read book Artificial Neural Networks for Renewable Energy Systems and Real World Applications written by Ammar Hamed Elsheikh and published by Academic Press. This book was released on 2022-09-08 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Neural Networks for Renewable Energy Systems and Real-World Applications presents current trends for the solution of complex engineering problems in the application, modeling, analysis, and optimization of different energy systems and manufacturing processes. With growing research catering to the applications of neural networks in specific industrial applications, this reference provides a single resource catering to a broader perspective of ANN in renewable energy systems and manufacturing processes. ANN-based methods have attracted the attention of scientists and researchers in different engineering and industrial disciplines, making this book a useful reference for all researchers and engineers interested in artificial networks, renewable energy systems, and manufacturing process analysis. - Includes illustrative examples on the design and development of ANNS for renewable and manufacturing applications - Features computer-aided simulations presented as algorithms, pseudocodes and flowcharts - Covers ANN theory for easy reference in subsequent technology specific sections